Performance/accuracy exploration with 12 object detection models, 5 TensorFlow backends and 6 batch sizes.
This Jupyter Notebook studies performance (execution time per image, images per seconds) vs accuracy (mAP, Recall) of several Object Detection models on different size objects (large, medium and small). The experiments are performed via TensorFlow with several execution options on the CPU and the GPU.
Model | Unique CK Tags (<tags> ) |
Is Custom? | mAP in % |
---|---|---|---|
faster_rcnn_nas_lowproposals_coco |
rcnn,nas,lowproposals,vcoco |
0 | 44.340195 |
faster_rcnn_resnet50_lowproposals_coco |
rcnn,resnet50,lowproposals |
0 | 24.241037 |
faster_rcnn_resnet101_lowproposals_coco |
rcnn,resnet101,lowproposals |
0 | 32.594327 |
faster_rcnn_inception_resnet_v2_atrous_lowproposals_coco |
rcnn,inception-resnet-v2,lowproposals |
0 | 36.520117 |
faster_rcnn_inception_v2_coco |
rcnn,inception-v2 |
0 | 28.309626 |
ssd_inception_v2_coco |
ssd,inception-v2 |
0 | 27.765988 |
ssd_mobilenet_v1_coco |
ssd,mobilenet-v1,non-quantized,mlperf,tf |
0 | 23.111170 |
ssd_mobilenet_v1_quantized_coco |
ssd,mobilenet-v1,quantized,mlperf,tf |
0 | 23.591693 |
ssd_mobilenet_v1_fpn_coco |
ssd,mobilenet-v1,fpn |
0 | 35.353170 |
ssd_resnet_50_fpn_coco |
ssd,resnet50,fpn |
0 | 38.341120 |
ssdlite_mobilenet_v2_coco |
ssdlite,mobilenet-v2,vcoco |
0 | 24.281540 |
yolo_v3_coco |
yolo-v3 |
1 | 28.532508 |
See our Docker container for more information on the software configuration.
NB: Please ignore this section if you are not interested in re-running or modifying this notebook.
import os
import sys
import json
import re
If some of the scientific packages are missing, please install them using:
$ python -m pip install jupyter pandas numpy matplotlib --user
import IPython as ip
import pandas as pd
import numpy as np
import matplotlib as mp
import seaborn as sb
print ('IPython version: %s' % ip.__version__)
print ('Pandas version: %s' % pd.__version__)
print ('NumPy version: %s' % np.__version__)
print ('Matplotlib version: %s' % mp.__version__)
print ('Seaborn version: %s' % sb.__version__)
IPython version: 7.5.0 Pandas version: 0.25.1 NumPy version: 1.17.2 Matplotlib version: 3.1.1 Seaborn version: 0.9.0
from IPython.display import Image, display
def display_in_full(df):
pd.options.display.max_columns = len(df.columns)
pd.options.display.max_rows = len(df.index)
display(df)
import matplotlib.pyplot as plt
from matplotlib import cm
%matplotlib inline
default_colormap = cm.autumn
default_fontsize = 16
default_barwidth = 0.8
default_figwidth = 24
default_figheight = 3
default_figdpi = 200
default_figsize = [default_figwidth, default_figheight]
if mp.__version__[0]=='2': mp.style.use('classic')
mp.rcParams['figure.max_open_warning'] = 200
mp.rcParams['figure.dpi'] = default_figdpi
mp.rcParams['font.size'] = default_fontsize
mp.rcParams['legend.fontsize'] = 'medium'
save_fig_ext = 'png'
save_fig_dir = os.path.join(os.path.expanduser("~"), 'omnibench')
if not os.path.exists(save_fig_dir):
os.mkdir(save_fig_dir)
from pprint import pprint
If CK is not installed, please install it using:
$ python -m pip install ck --user
import ck.kernel as ck
print ('CK version: %s' % ck.__version__)
CK version: 1.10.3.1
Download experimental data and add CK repositories as follows:
$ wget https://www.dropbox.com/s/g0bc1exh1621k1q/ckr-dse-demo-object-detection-accuracy.zip --no-check-certificate
$ ck add repo --zip=ckr-dse-demo-object-detection-accuracy.zip
$ wget https://www.dropbox.com/s/g0bc1exh1621k1q/ckr-dse-demo-object-detection-performance-docker.zip --no-check-certificate
$ ck add repo --zip=ckr-dse-demo-object-detection-performance-docker.zip
$ wget https://www.dropbox.com/s/g0bc1exh1621k1q/ckr-dse-demo-object-detection-performance-native.zip --no-check-certificate
$ ck add repo --zip=ckr-dse-demo-object-detection-performance-native.zip
repo_uoa = 'dse-demo-object-detection-accuracy'
print ("*"*80)
print (repo_uoa)
print ("*"*80)
!ck list $repo_uoa:experiment:* | sort
print ("")
perf_docker_repo_uoa = 'dse-demo-object-detection-performance-docker'
print ("*"*80)
print (perf_docker_repo_uoa)
print ("*"*80)
!ck list $perf_docker_repo_uoa:experiment:* | sort
print ("")
perf_native_repo_uoa = 'dse-demo-object-detection-performance-native'
print ("*"*80)
print (perf_native_repo_uoa)
print ("*"*80)
!ck list $perf_native_repo_uoa:experiment:* | sort
******************************************************************************** dse-demo-object-detection-accuracy ******************************************************************************** mlperf-object-detection-rcnn-inception-resnet-v2-lowproposals-tf-py-accuracy-model-width-height mlperf-object-detection-rcnn-inception-resnet-v2-lowproposals-tf-py-accuracy-no-batch mlperf-object-detection-rcnn-inception-v2-tf-py-accuracy-model-width-height mlperf-object-detection-rcnn-inception-v2-tf-py-accuracy-no-batch mlperf-object-detection-rcnn-nas-lowproposals-tf-py-accuracy-model-width-height mlperf-object-detection-rcnn-nas-lowproposals-tf-py-accuracy-no-batch mlperf-object-detection-rcnn-resnet101-lowproposals-tf-py-accuracy-model-width-height mlperf-object-detection-rcnn-resnet101-lowproposals-tf-py-accuracy-no-batch mlperf-object-detection-rcnn-resnet50-lowproposals-tf-py-accuracy-model-width-height mlperf-object-detection-rcnn-resnet50-lowproposals-tf-py-accuracy-no-batch mlperf-object-detection-ssd-inception-v2-tf-py-accuracy-model-width-height mlperf-object-detection-ssd-inception-v2-tf-py-accuracy-no-batch mlperf-object-detection-ssdlite-mobilenet-v2-tf-py-accuracy-model-width-height mlperf-object-detection-ssdlite-mobilenet-v2-tf-py-accuracy-no-batch mlperf-object-detection-ssd-mobilenet-v1-fpn-tf-py-accuracy-model-width-height mlperf-object-detection-ssd-mobilenet-v1-fpn-tf-py-accuracy-no-batch mlperf-object-detection-ssd-mobilenet-v1-non-quantized-mlperf-tf-py-accuracy-model-width-height mlperf-object-detection-ssd-mobilenet-v1-non-quantized-mlperf-tf-py-accuracy-no-batch mlperf-object-detection-ssd-mobilenet-v1-quantized-mlperf-tf-py-accuracy-model-width-height mlperf-object-detection-ssd-mobilenet-v1-quantized-mlperf-tf-py-accuracy-no-batch mlperf-object-detection-ssd-resnet50-fpn-tf-py-accuracy-model-width-height mlperf-object-detection-ssd-resnet50-fpn-tf-py-accuracy-no-batch mlperf-object-detection-yolo-v3-tf-py-accuracy-no-batch ******************************************************************************** dse-demo-object-detection-performance-docker ******************************************************************************** mlperf-object-detection-rcnn-inception-resnet-v2-lowproposals-tf-py-performance-cpu-batch-size1 mlperf-object-detection-rcnn-inception-resnet-v2-lowproposals-tf-py-performance-cpu-batch-size16 mlperf-object-detection-rcnn-inception-resnet-v2-lowproposals-tf-py-performance-cpu-batch-size2 mlperf-object-detection-rcnn-inception-resnet-v2-lowproposals-tf-py-performance-cpu-batch-size32 mlperf-object-detection-rcnn-inception-resnet-v2-lowproposals-tf-py-performance-cpu-batch-size4 mlperf-object-detection-rcnn-inception-resnet-v2-lowproposals-tf-py-performance-cpu-batch-size8 mlperf-object-detection-rcnn-inception-resnet-v2-lowproposals-tf-py-performance-cpu-prebuilt-batch-size1 mlperf-object-detection-rcnn-inception-resnet-v2-lowproposals-tf-py-performance-cpu-prebuilt-batch-size16 mlperf-object-detection-rcnn-inception-resnet-v2-lowproposals-tf-py-performance-cpu-prebuilt-batch-size2 mlperf-object-detection-rcnn-inception-resnet-v2-lowproposals-tf-py-performance-cpu-prebuilt-batch-size32 mlperf-object-detection-rcnn-inception-resnet-v2-lowproposals-tf-py-performance-cpu-prebuilt-batch-size4 mlperf-object-detection-rcnn-inception-resnet-v2-lowproposals-tf-py-performance-cpu-prebuilt-batch-size8 mlperf-object-detection-rcnn-inception-resnet-v2-lowproposals-tf-py-performance-cuda-batch-size1 mlperf-object-detection-rcnn-inception-resnet-v2-lowproposals-tf-py-performance-cuda-batch-size16 mlperf-object-detection-rcnn-inception-resnet-v2-lowproposals-tf-py-performance-cuda-batch-size2 mlperf-object-detection-rcnn-inception-resnet-v2-lowproposals-tf-py-performance-cuda-batch-size4 mlperf-object-detection-rcnn-inception-resnet-v2-lowproposals-tf-py-performance-cuda-batch-size8 mlperf-object-detection-rcnn-inception-resnet-v2-lowproposals-tf-py-performance-tensorrt-batch-size1 mlperf-object-detection-rcnn-inception-resnet-v2-lowproposals-tf-py-performance-tensorrt-batch-size16 mlperf-object-detection-rcnn-inception-resnet-v2-lowproposals-tf-py-performance-tensorrt-batch-size2 mlperf-object-detection-rcnn-inception-resnet-v2-lowproposals-tf-py-performance-tensorrt-batch-size4 mlperf-object-detection-rcnn-inception-resnet-v2-lowproposals-tf-py-performance-tensorrt-batch-size8 mlperf-object-detection-rcnn-inception-v2-tf-py-performance-cpu-batch-size1 mlperf-object-detection-rcnn-inception-v2-tf-py-performance-cpu-batch-size16 mlperf-object-detection-rcnn-inception-v2-tf-py-performance-cpu-batch-size2 mlperf-object-detection-rcnn-inception-v2-tf-py-performance-cpu-batch-size32 mlperf-object-detection-rcnn-inception-v2-tf-py-performance-cpu-batch-size4 mlperf-object-detection-rcnn-inception-v2-tf-py-performance-cpu-batch-size8 mlperf-object-detection-rcnn-inception-v2-tf-py-performance-cpu-prebuilt-batch-size1 mlperf-object-detection-rcnn-inception-v2-tf-py-performance-cpu-prebuilt-batch-size16 mlperf-object-detection-rcnn-inception-v2-tf-py-performance-cpu-prebuilt-batch-size2 mlperf-object-detection-rcnn-inception-v2-tf-py-performance-cpu-prebuilt-batch-size32 mlperf-object-detection-rcnn-inception-v2-tf-py-performance-cpu-prebuilt-batch-size4 mlperf-object-detection-rcnn-inception-v2-tf-py-performance-cpu-prebuilt-batch-size8 mlperf-object-detection-rcnn-inception-v2-tf-py-performance-cuda-batch-size1 mlperf-object-detection-rcnn-inception-v2-tf-py-performance-cuda-batch-size16 mlperf-object-detection-rcnn-inception-v2-tf-py-performance-cuda-batch-size2 mlperf-object-detection-rcnn-inception-v2-tf-py-performance-cuda-batch-size32 mlperf-object-detection-rcnn-inception-v2-tf-py-performance-cuda-batch-size4 mlperf-object-detection-rcnn-inception-v2-tf-py-performance-cuda-batch-size8 mlperf-object-detection-rcnn-inception-v2-tf-py-performance-tensorrt-batch-size1 mlperf-object-detection-rcnn-inception-v2-tf-py-performance-tensorrt-batch-size16 mlperf-object-detection-rcnn-inception-v2-tf-py-performance-tensorrt-batch-size2 mlperf-object-detection-rcnn-inception-v2-tf-py-performance-tensorrt-batch-size32 mlperf-object-detection-rcnn-inception-v2-tf-py-performance-tensorrt-batch-size4 mlperf-object-detection-rcnn-inception-v2-tf-py-performance-tensorrt-batch-size8 mlperf-object-detection-rcnn-inception-v2-tf-py-performance-tensorrt-dynamic-batch-size1 mlperf-object-detection-rcnn-inception-v2-tf-py-performance-tensorrt-dynamic-batch-size16 mlperf-object-detection-rcnn-inception-v2-tf-py-performance-tensorrt-dynamic-batch-size2 mlperf-object-detection-rcnn-inception-v2-tf-py-performance-tensorrt-dynamic-batch-size4 mlperf-object-detection-rcnn-inception-v2-tf-py-performance-tensorrt-dynamic-batch-size8 mlperf-object-detection-rcnn-nas-lowproposals-tf-py-performance-cpu-batch-size1 mlperf-object-detection-rcnn-nas-lowproposals-tf-py-performance-cpu-batch-size16 mlperf-object-detection-rcnn-nas-lowproposals-tf-py-performance-cpu-batch-size2 mlperf-object-detection-rcnn-nas-lowproposals-tf-py-performance-cpu-batch-size32 mlperf-object-detection-rcnn-nas-lowproposals-tf-py-performance-cpu-batch-size4 mlperf-object-detection-rcnn-nas-lowproposals-tf-py-performance-cpu-batch-size8 mlperf-object-detection-rcnn-nas-lowproposals-tf-py-performance-cpu-prebuilt-batch-size1 mlperf-object-detection-rcnn-nas-lowproposals-tf-py-performance-cpu-prebuilt-batch-size16 mlperf-object-detection-rcnn-nas-lowproposals-tf-py-performance-cpu-prebuilt-batch-size2 mlperf-object-detection-rcnn-nas-lowproposals-tf-py-performance-cpu-prebuilt-batch-size32 mlperf-object-detection-rcnn-nas-lowproposals-tf-py-performance-cpu-prebuilt-batch-size4 mlperf-object-detection-rcnn-nas-lowproposals-tf-py-performance-cpu-prebuilt-batch-size8 mlperf-object-detection-rcnn-nas-lowproposals-tf-py-performance-cuda-batch-size1 mlperf-object-detection-rcnn-nas-lowproposals-tf-py-performance-cuda-batch-size2 mlperf-object-detection-rcnn-nas-lowproposals-tf-py-performance-cuda-batch-size4 mlperf-object-detection-rcnn-nas-lowproposals-tf-py-performance-cuda-batch-size8 mlperf-object-detection-rcnn-nas-lowproposals-tf-py-performance-tensorrt-batch-size1 mlperf-object-detection-rcnn-nas-lowproposals-tf-py-performance-tensorrt-batch-size2 mlperf-object-detection-rcnn-nas-lowproposals-tf-py-performance-tensorrt-batch-size4 mlperf-object-detection-rcnn-nas-lowproposals-tf-py-performance-tensorrt-batch-size8 mlperf-object-detection-rcnn-nas-lowproposals-tf-py-performance-tensorrt-dynamic-batch-size1 mlperf-object-detection-rcnn-resnet101-lowproposals-tf-py-performance-cpu-batch-size1 mlperf-object-detection-rcnn-resnet101-lowproposals-tf-py-performance-cpu-batch-size16 mlperf-object-detection-rcnn-resnet101-lowproposals-tf-py-performance-cpu-batch-size2 mlperf-object-detection-rcnn-resnet101-lowproposals-tf-py-performance-cpu-batch-size32 mlperf-object-detection-rcnn-resnet101-lowproposals-tf-py-performance-cpu-batch-size4 mlperf-object-detection-rcnn-resnet101-lowproposals-tf-py-performance-cpu-batch-size8 mlperf-object-detection-rcnn-resnet101-lowproposals-tf-py-performance-cpu-prebuilt-batch-size1 mlperf-object-detection-rcnn-resnet101-lowproposals-tf-py-performance-cpu-prebuilt-batch-size16 mlperf-object-detection-rcnn-resnet101-lowproposals-tf-py-performance-cpu-prebuilt-batch-size2 mlperf-object-detection-rcnn-resnet101-lowproposals-tf-py-performance-cpu-prebuilt-batch-size32 mlperf-object-detection-rcnn-resnet101-lowproposals-tf-py-performance-cpu-prebuilt-batch-size4 mlperf-object-detection-rcnn-resnet101-lowproposals-tf-py-performance-cpu-prebuilt-batch-size8 mlperf-object-detection-rcnn-resnet101-lowproposals-tf-py-performance-cuda-batch-size1 mlperf-object-detection-rcnn-resnet101-lowproposals-tf-py-performance-cuda-batch-size16 mlperf-object-detection-rcnn-resnet101-lowproposals-tf-py-performance-cuda-batch-size2 mlperf-object-detection-rcnn-resnet101-lowproposals-tf-py-performance-cuda-batch-size32 mlperf-object-detection-rcnn-resnet101-lowproposals-tf-py-performance-cuda-batch-size4 mlperf-object-detection-rcnn-resnet101-lowproposals-tf-py-performance-cuda-batch-size8 mlperf-object-detection-rcnn-resnet101-lowproposals-tf-py-performance-tensorrt-batch-size1 mlperf-object-detection-rcnn-resnet101-lowproposals-tf-py-performance-tensorrt-batch-size16 mlperf-object-detection-rcnn-resnet101-lowproposals-tf-py-performance-tensorrt-batch-size2 mlperf-object-detection-rcnn-resnet101-lowproposals-tf-py-performance-tensorrt-batch-size32 mlperf-object-detection-rcnn-resnet101-lowproposals-tf-py-performance-tensorrt-batch-size4 mlperf-object-detection-rcnn-resnet101-lowproposals-tf-py-performance-tensorrt-batch-size8 mlperf-object-detection-rcnn-resnet101-lowproposals-tf-py-performance-tensorrt-dynamic-batch-size1 mlperf-object-detection-rcnn-resnet101-lowproposals-tf-py-performance-tensorrt-dynamic-batch-size16 mlperf-object-detection-rcnn-resnet101-lowproposals-tf-py-performance-tensorrt-dynamic-batch-size2 mlperf-object-detection-rcnn-resnet101-lowproposals-tf-py-performance-tensorrt-dynamic-batch-size4 mlperf-object-detection-rcnn-resnet101-lowproposals-tf-py-performance-tensorrt-dynamic-batch-size8 mlperf-object-detection-rcnn-resnet50-lowproposals-tf-py-performance-cpu-batch-size1 mlperf-object-detection-rcnn-resnet50-lowproposals-tf-py-performance-cpu-batch-size16 mlperf-object-detection-rcnn-resnet50-lowproposals-tf-py-performance-cpu-batch-size2 mlperf-object-detection-rcnn-resnet50-lowproposals-tf-py-performance-cpu-batch-size32 mlperf-object-detection-rcnn-resnet50-lowproposals-tf-py-performance-cpu-batch-size4 mlperf-object-detection-rcnn-resnet50-lowproposals-tf-py-performance-cpu-batch-size8 mlperf-object-detection-rcnn-resnet50-lowproposals-tf-py-performance-cpu-prebuilt-batch-size1 mlperf-object-detection-rcnn-resnet50-lowproposals-tf-py-performance-cpu-prebuilt-batch-size16 mlperf-object-detection-rcnn-resnet50-lowproposals-tf-py-performance-cpu-prebuilt-batch-size2 mlperf-object-detection-rcnn-resnet50-lowproposals-tf-py-performance-cpu-prebuilt-batch-size32 mlperf-object-detection-rcnn-resnet50-lowproposals-tf-py-performance-cpu-prebuilt-batch-size4 mlperf-object-detection-rcnn-resnet50-lowproposals-tf-py-performance-cpu-prebuilt-batch-size8 mlperf-object-detection-rcnn-resnet50-lowproposals-tf-py-performance-cuda-batch-size1 mlperf-object-detection-rcnn-resnet50-lowproposals-tf-py-performance-cuda-batch-size16 mlperf-object-detection-rcnn-resnet50-lowproposals-tf-py-performance-cuda-batch-size2 mlperf-object-detection-rcnn-resnet50-lowproposals-tf-py-performance-cuda-batch-size32 mlperf-object-detection-rcnn-resnet50-lowproposals-tf-py-performance-cuda-batch-size4 mlperf-object-detection-rcnn-resnet50-lowproposals-tf-py-performance-cuda-batch-size8 mlperf-object-detection-rcnn-resnet50-lowproposals-tf-py-performance-tensorrt-batch-size1 mlperf-object-detection-rcnn-resnet50-lowproposals-tf-py-performance-tensorrt-batch-size16 mlperf-object-detection-rcnn-resnet50-lowproposals-tf-py-performance-tensorrt-batch-size2 mlperf-object-detection-rcnn-resnet50-lowproposals-tf-py-performance-tensorrt-batch-size32 mlperf-object-detection-rcnn-resnet50-lowproposals-tf-py-performance-tensorrt-batch-size4 mlperf-object-detection-rcnn-resnet50-lowproposals-tf-py-performance-tensorrt-batch-size8 mlperf-object-detection-rcnn-resnet50-lowproposals-tf-py-performance-tensorrt-dynamic-batch-size1 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object-detection-ssd-mobilenet-v1-fpn-tf-py-performance-source-cuda-batch-size8 object-detection-ssd-mobilenet-v1-fpn-tf-py-performance-tensorRT-batch-size1 object-detection-ssd-mobilenet-v1-fpn-tf-py-performance-tensorRT-batch-size16 object-detection-ssd-mobilenet-v1-fpn-tf-py-performance-tensorRT-batch-size2 object-detection-ssd-mobilenet-v1-fpn-tf-py-performance-tensorRT-batch-size32 object-detection-ssd-mobilenet-v1-fpn-tf-py-performance-tensorRT-batch-size4 object-detection-ssd-mobilenet-v1-fpn-tf-py-performance-tensorRT-batch-size8 object-detection-ssd-mobilenet-v1-fpn-tf-py-performance-tensorRT-dynamic-batch-size1 object-detection-ssd-mobilenet-v1-fpn-tf-py-performance-tensorRT-dynamic-batch-size16 object-detection-ssd-mobilenet-v1-fpn-tf-py-performance-tensorRT-dynamic-batch-size2 object-detection-ssd-mobilenet-v1-fpn-tf-py-performance-tensorRT-dynamic-batch-size32 object-detection-ssd-mobilenet-v1-fpn-tf-py-performance-tensorRT-dynamic-batch-size4 object-detection-ssd-mobilenet-v1-fpn-tf-py-performance-tensorRT-dynamic-batch-size8 object-detection-ssd-mobilenet-v1-quantized-mlperf-tf-py-performance-prebuilt-cpu-batch-size1 object-detection-ssd-mobilenet-v1-quantized-mlperf-tf-py-performance-prebuilt-cpu-batch-size16 object-detection-ssd-mobilenet-v1-quantized-mlperf-tf-py-performance-prebuilt-cpu-batch-size2 object-detection-ssd-mobilenet-v1-quantized-mlperf-tf-py-performance-prebuilt-cpu-batch-size32 object-detection-ssd-mobilenet-v1-quantized-mlperf-tf-py-performance-prebuilt-cpu-batch-size4 object-detection-ssd-mobilenet-v1-quantized-mlperf-tf-py-performance-prebuilt-cpu-batch-size8 object-detection-ssd-mobilenet-v1-quantized-mlperf-tf-py-performance-source-cpu-batch-size1 object-detection-ssd-mobilenet-v1-quantized-mlperf-tf-py-performance-source-cpu-batch-size16 object-detection-ssd-mobilenet-v1-quantized-mlperf-tf-py-performance-source-cpu-batch-size2 object-detection-ssd-mobilenet-v1-quantized-mlperf-tf-py-performance-source-cpu-batch-size32 object-detection-ssd-mobilenet-v1-quantized-mlperf-tf-py-performance-source-cpu-batch-size4 object-detection-ssd-mobilenet-v1-quantized-mlperf-tf-py-performance-source-cpu-batch-size8 object-detection-ssd-mobilenet-v1-quantized-mlperf-tf-py-performance-source-cuda-batch-size1 object-detection-ssd-mobilenet-v1-quantized-mlperf-tf-py-performance-source-cuda-batch-size16 object-detection-ssd-mobilenet-v1-quantized-mlperf-tf-py-performance-source-cuda-batch-size2 object-detection-ssd-mobilenet-v1-quantized-mlperf-tf-py-performance-source-cuda-batch-size32 object-detection-ssd-mobilenet-v1-quantized-mlperf-tf-py-performance-source-cuda-batch-size4 object-detection-ssd-mobilenet-v1-quantized-mlperf-tf-py-performance-source-cuda-batch-size8 object-detection-ssd-mobilenet-v1-quantized-mlperf-tf-py-performance-tensorRT-batch-size1 object-detection-ssd-mobilenet-v1-quantized-mlperf-tf-py-performance-tensorRT-batch-size16 object-detection-ssd-mobilenet-v1-quantized-mlperf-tf-py-performance-tensorRT-batch-size2 object-detection-ssd-mobilenet-v1-quantized-mlperf-tf-py-performance-tensorRT-batch-size32 object-detection-ssd-mobilenet-v1-quantized-mlperf-tf-py-performance-tensorRT-batch-size4 object-detection-ssd-mobilenet-v1-quantized-mlperf-tf-py-performance-tensorRT-batch-size8 object-detection-ssd-mobilenet-v1-quantized-mlperf-tf-py-performance-tensorRT-dynamic-batch-size1 object-detection-ssd-mobilenet-v1-quantized-mlperf-tf-py-performance-tensorRT-dynamic-batch-size16 object-detection-ssd-mobilenet-v1-quantized-mlperf-tf-py-performance-tensorRT-dynamic-batch-size2 object-detection-ssd-mobilenet-v1-quantized-mlperf-tf-py-performance-tensorRT-dynamic-batch-size32 object-detection-ssd-mobilenet-v1-quantized-mlperf-tf-py-performance-tensorRT-dynamic-batch-size4 object-detection-ssd-mobilenet-v1-quantized-mlperf-tf-py-performance-tensorRT-dynamic-batch-size8 object-detection-ssd-resnet50-fpn-tf-py-performance-prebuilt-cpu-batch-size1 object-detection-ssd-resnet50-fpn-tf-py-performance-prebuilt-cpu-batch-size16 object-detection-ssd-resnet50-fpn-tf-py-performance-prebuilt-cpu-batch-size2 object-detection-ssd-resnet50-fpn-tf-py-performance-prebuilt-cpu-batch-size32 object-detection-ssd-resnet50-fpn-tf-py-performance-prebuilt-cpu-batch-size4 object-detection-ssd-resnet50-fpn-tf-py-performance-prebuilt-cpu-batch-size8 object-detection-ssd-resnet50-fpn-tf-py-performance-source-cpu-batch-size1 object-detection-ssd-resnet50-fpn-tf-py-performance-source-cpu-batch-size16 object-detection-ssd-resnet50-fpn-tf-py-performance-source-cpu-batch-size2 object-detection-ssd-resnet50-fpn-tf-py-performance-source-cpu-batch-size32 object-detection-ssd-resnet50-fpn-tf-py-performance-source-cpu-batch-size4 object-detection-ssd-resnet50-fpn-tf-py-performance-source-cpu-batch-size8 object-detection-ssd-resnet50-fpn-tf-py-performance-source-cuda-batch-size1 object-detection-ssd-resnet50-fpn-tf-py-performance-source-cuda-batch-size16 object-detection-ssd-resnet50-fpn-tf-py-performance-source-cuda-batch-size2 object-detection-ssd-resnet50-fpn-tf-py-performance-source-cuda-batch-size32 object-detection-ssd-resnet50-fpn-tf-py-performance-source-cuda-batch-size4 object-detection-ssd-resnet50-fpn-tf-py-performance-source-cuda-batch-size8 object-detection-ssd-resnet50-fpn-tf-py-performance-tensorRT-batch-size1 object-detection-ssd-resnet50-fpn-tf-py-performance-tensorRT-batch-size16 object-detection-ssd-resnet50-fpn-tf-py-performance-tensorRT-batch-size2 object-detection-ssd-resnet50-fpn-tf-py-performance-tensorRT-batch-size32 object-detection-ssd-resnet50-fpn-tf-py-performance-tensorRT-batch-size4 object-detection-ssd-resnet50-fpn-tf-py-performance-tensorRT-batch-size8 object-detection-ssd-resnet50-fpn-tf-py-performance-tensorRT-dynamic-batch-size1 object-detection-ssd-resnet50-fpn-tf-py-performance-tensorRT-dynamic-batch-size16 object-detection-ssd-resnet50-fpn-tf-py-performance-tensorRT-dynamic-batch-size2 object-detection-ssd-resnet50-fpn-tf-py-performance-tensorRT-dynamic-batch-size32 object-detection-ssd-resnet50-fpn-tf-py-performance-tensorRT-dynamic-batch-size4 object-detection-ssd-resnet50-fpn-tf-py-performance-tensorRT-dynamic-batch-size8 object-detection-yolo-v3-tf-py-performance-prebuilt-cpu-batch-size1 object-detection-yolo-v3-tf-py-performance-prebuilt-cpu-batch-size16 object-detection-yolo-v3-tf-py-performance-prebuilt-cpu-batch-size2 object-detection-yolo-v3-tf-py-performance-prebuilt-cpu-batch-size32 object-detection-yolo-v3-tf-py-performance-prebuilt-cpu-batch-size4 object-detection-yolo-v3-tf-py-performance-prebuilt-cpu-batch-size8 object-detection-yolo-v3-tf-py-performance-source-cpu-batch-size1 object-detection-yolo-v3-tf-py-performance-source-cpu-batch-size16 object-detection-yolo-v3-tf-py-performance-source-cpu-batch-size2 object-detection-yolo-v3-tf-py-performance-source-cpu-batch-size32 object-detection-yolo-v3-tf-py-performance-source-cpu-batch-size4 object-detection-yolo-v3-tf-py-performance-source-cpu-batch-size8 object-detection-yolo-v3-tf-py-performance-source-cuda-batch-size1 object-detection-yolo-v3-tf-py-performance-source-cuda-batch-size16 object-detection-yolo-v3-tf-py-performance-source-cuda-batch-size2 object-detection-yolo-v3-tf-py-performance-source-cuda-batch-size32 object-detection-yolo-v3-tf-py-performance-source-cuda-batch-size4 object-detection-yolo-v3-tf-py-performance-source-cuda-batch-size8 object-detection-yolo-v3-tf-py-performance-tensorRT-batch-size1 object-detection-yolo-v3-tf-py-performance-tensorRT-batch-size16 object-detection-yolo-v3-tf-py-performance-tensorRT-batch-size2 object-detection-yolo-v3-tf-py-performance-tensorRT-batch-size32 object-detection-yolo-v3-tf-py-performance-tensorRT-batch-size4 object-detection-yolo-v3-tf-py-performance-tensorRT-batch-size8 object-detection-yolo-v3-tf-py-performance-tensorRT-dynamic-batch-size1 object-detection-yolo-v3-tf-py-performance-tensorRT-dynamic-batch-size16 object-detection-yolo-v3-tf-py-performance-tensorRT-dynamic-batch-size2 object-detection-yolo-v3-tf-py-performance-tensorRT-dynamic-batch-size32 object-detection-yolo-v3-tf-py-performance-tensorRT-dynamic-batch-size4 object-detection-yolo-v3-tf-py-performance-tensorRT-dynamic-batch-size8
def get_experimental_results(repo_uoa, module_uoa='experiment', tags='', accuracy=True):
r = ck.access({'action':'search', 'repo_uoa':repo_uoa, 'module_uoa':module_uoa, 'tags':tags})
#pprint (r)
if r['return']>0:
print('Error: %s' % r['error'])
exit(1)
experiments = r['lst']
dfs = []
for experiment in experiments:
data_uoa = experiment['data_uoa']
r = ck.access({'action':'list_points', 'repo_uoa':repo_uoa, 'module_uoa':module_uoa, 'data_uoa':data_uoa})
pipeline_file_path = os.path.join(r['path'], 'pipeline.json')
with open(pipeline_file_path) as pipeline_file:
pipeline_data_raw = json.load(pipeline_file)
weights_env = pipeline_data_raw['dependencies']['weights']['dict']['env']
image_width = np.int64(weights_env.get('CK_ENV_TENSORFLOW_MODEL_DEFAULT_WIDTH',-1))
image_height = np.int64(weights_env.get('CK_ENV_TENSORFLOW_MODEL_DEFAULT_HEIGHT',-1))
tags = r['dict']['tags']
#print (tags)
for point in r['points']:
point_file_path = os.path.join(r['path'], 'ckp-%s.0001.json' % point)
with open(point_file_path) as point_file:
point_data_raw = json.load(point_file)
#pprint (point_data_raw['choices']['env'])
characteristics_list = point_data_raw['characteristics_list']
num_repetitions = len(characteristics_list)
#platform = point_data_raw['features']['platform']['platform']['model']
if np.int64(point_data_raw['choices']['env'].get('CK_ENABLE_BATCH',-1))==1:
batch_enabled = True
batch_size = np.int64(point_data_raw['choices']['env'].get('CK_BATCH_SIZE',-1))
batch_count = np.int64(point_data_raw['choices']['env'].get('CK_BATCH_COUNT',-1))
else:
batch_enabled = False
batch_size = 1
batch_count = np.int64(point_data_raw['choices']['env'].get('CK_BATCH_COUNT',-1)) * \
np.int64(point_data_raw['choices']['env'].get('CK_BATCH_SIZE',-1))
characteristics = characteristics_list[0]
if accuracy:
data = [
{
'model': tags[0],
'backend':'cuda',
'batch_size': batch_size,
'batch_count': batch_count,
'batch_enabled': batch_enabled,
'image_height': image_height,
'image_width': image_width,
'num_reps':1,
# runtime characteristics
'Recall': characteristics['run'].get('recall',0)*100,
'mAP': characteristics['run'].get('mAP',0)*100,
'mAP_large': characteristics['run']['metrics'].get('DetectionBoxes_Recall/AR@100 (large)', 0)*100,
'mAP_medium': characteristics['run']['metrics'].get('DetectionBoxes_Recall/AR@100 (medium)', 0)*100,
'mAP_small': characteristics['run']['metrics'].get('DetectionBoxes_Recall/AR@100 (small)', 0)*100,
}
]
# print(data[0]['model'])
else: # performance
####### this conversion is still needed because some of the result have the old naming convention
backend = 'default'
trt = point_data_raw['choices']['env'].get('CK_ENABLE_TENSORRT',0)
trt_dyn = point_data_raw['choices']['env'].get('CK_TENSORRT_DYNAMIC',0)
if trt_dyn == '1':
backend = 'tensorrt-dynamic'
elif trt == '1':
backend = 'tensorrt'
elif tags[0] == 'tensorrt' or tags[0] =='source-cuda':
backend = 'cuda'
elif tags[0] == 'tf-src-cpu' or tags[0] =='source-cpu':
backend = 'cpu'
elif tags[0] == 'tf-prebuild-cpu' or tags[0] == 'prebuilt-cpu':
backend = 'cpu-prebuilt'
else:
backend = tags[0]
model = tags[1]
data = [
{
'model': model,
'backend': backend,
'batch_size': batch_size,
'batch_count': batch_count,
'batch_enabled': batch_enabled,
'image_height': image_height,
'image_width': image_width,
'num_reps' : num_repetitions,
# statistical repetition
'repetition_id': repetition_id,
# runtime characteristics
'avg_fps': characteristics['run'].get('avg_fps', 'n/a')*batch_size,
'avg_time_ms': characteristics['run']['avg_time_ms']/batch_size,
'graph_load_time_ms': characteristics['run']['graph_load_time_s']*1e+3,
'images_load_time_avg_ms': characteristics['run']['images_load_time_avg_s']*1e+3,
}
for (repetition_id, characteristics) in zip(range(num_repetitions), characteristics_list)
]
index = [
'model', 'backend', 'batch_size', 'batch_count', 'batch_enabled', 'image_height', 'image_width', 'num_reps'
]
# Construct a DataFrame.
df = pd.DataFrame(data)
df = df.set_index(index)
# Append to the list of similarly constructed DataFrames.
dfs.append(df)
if dfs:
# Concatenate all thus constructed DataFrames (i.e. stack on top of each other).
result = pd.concat(dfs)
result.sort_index(ascending=True, inplace=True)
else:
# Construct a dummy DataFrame the success status of which can be safely checked.
result = pd.DataFrame(columns=['success?'])
return result
#!ck recache repo
dfs = get_experimental_results(repo_uoa, accuracy=True)
dfs_perf = get_experimental_results(perf_docker_repo_uoa, accuracy=False)
dfs_perf_native = get_experimental_results(perf_native_repo_uoa, accuracy=False)
display_in_full(dfs)
display_in_full(dfs_perf)
Recall | mAP | mAP_large | mAP_medium | mAP_small | ||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|
model | backend | batch_size | batch_count | batch_enabled | image_height | image_width | num_reps | |||||
rcnn-inception-resnet-v2-lowproposals | cuda | 1 | 5000 | False | 1024 | 600 | 1 | 40.071771 | 36.521150 | 67.007142 | 44.677563 | 12.482768 |
True | 1024 | 600 | 1 | 27.998174 | 24.014985 | 49.457345 | 28.361812 | 6.580855 | ||||
rcnn-inception-v2 | cuda | 1 | 5000 | False | 600 | 1024 | 1 | 34.596863 | 28.307326 | 57.903100 | 37.694893 | 9.948821 |
True | 600 | 1024 | 1 | 30.593184 | 23.891029 | 50.423664 | 32.742465 | 9.234102 | ||||
rcnn-nas-lowproposals | cuda | 1 | 5000 | False | 1200 | 1200 | 1 | 47.510012 | 44.339995 | 73.981437 | 54.376904 | 19.925600 |
True | 1200 | 1200 | 1 | 47.204636 | 43.983223 | 74.631044 | 53.876561 | 20.074105 | ||||
rcnn-resnet101-lowproposals | cuda | 1 | 5000 | False | 600 | 1024 | 1 | 36.399789 | 32.586659 | 59.472751 | 38.935294 | 12.325213 |
True | 600 | 1024 | 1 | 29.981835 | 25.969248 | 48.480626 | 30.466308 | 10.261601 | ||||
rcnn-resnet50-lowproposals | cuda | 1 | 5000 | False | 600 | 1024 | 1 | 27.724275 | 24.233987 | 46.253149 | 27.783111 | 8.761679 |
True | 600 | 1024 | 1 | 22.780471 | 19.241366 | 36.731852 | 21.222552 | 7.495941 | ||||
ssd-inception-v2 | cuda | 1 | 5000 | False | 300 | 300 | 1 | 30.804457 | 27.766736 | 69.530638 | 23.179061 | 3.473937 |
True | 300 | 300 | 1 | 30.708289 | 27.629812 | 69.414337 | 23.051823 | 3.399932 | ||||
ssd-mobilenet-v1-fpn | cuda | 1 | 5000 | False | 640 | 640 | 1 | 42.661767 | 35.352120 | 63.507365 | 47.378434 | 17.679955 |
True | 640 | 640 | 1 | 42.752999 | 35.362516 | 63.959455 | 47.239999 | 18.090466 | ||||
ssd-mobilenet-v1-non-quantized-mlperf | cuda | 1 | 5000 | False | 300 | 300 | 1 | 26.303653 | 23.110169 | 60.405184 | 19.015698 | 2.285248 |
True | 300 | 300 | 1 | 26.419481 | 23.173033 | 60.542022 | 19.144721 | 2.251986 | ||||
ssd-mobilenet-v1-quantized-mlperf | cuda | 1 | 5000 | False | 300 | 300 | 1 | 26.817126 | 23.577185 | 61.845886 | 19.045377 | 2.524694 |
True | 300 | 300 | 1 | 26.818268 | 23.551670 | 61.963231 | 19.108292 | 2.419133 | ||||
ssd-resnet50-fpn | cuda | 1 | 5000 | False | 640 | 640 | 1 | 45.780129 | 38.340936 | 68.218358 | 51.151692 | 19.788320 |
True | 640 | 640 | 1 | 45.894732 | 38.380971 | 69.016501 | 51.384803 | 19.662063 | ||||
ssdlite-mobilenet-v2 | cuda | 1 | 5000 | False | 300 | 300 | 1 | 27.226449 | 24.283266 | 64.482049 | 18.944375 | 2.304731 |
True | 300 | 300 | 1 | 27.094365 | 24.130926 | 63.986969 | 18.824788 | 2.281154 | ||||
yolo-v3 | cuda | 1 | 5000 | False | 416 | 416 | 1 | 32.493981 | 28.532508 | 52.285166 | 34.432202 | 13.186537 |
repetition_id | avg_fps | avg_time_ms | graph_load_time_ms | images_load_time_avg_ms | ||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|
model | backend | batch_size | batch_count | batch_enabled | image_height | image_width | num_reps | |||||
rcnn-inception-resnet-v2-lowproposals | cpu | 1 | 2 | True | 1024 | 600 | 10 | 0 | 0.475711 | 2102.114439 | 4840.737104 | 9.465098 |
10 | 1 | 0.476848 | 2097.102880 | 4681.562185 | 9.582043 | |||||||
10 | 2 | 0.473222 | 2113.173485 | 4745.374680 | 9.340763 | |||||||
10 | 3 | 0.476904 | 2096.859932 | 4693.865299 | 9.480476 | |||||||
10 | 4 | 0.482557 | 2072.292805 | 4820.402861 | 9.406209 | |||||||
10 | 5 | 0.471203 | 2122.228384 | 4716.161489 | 9.643555 | |||||||
10 | 6 | 0.475858 | 2101.465940 | 4778.688192 | 9.382725 | |||||||
10 | 7 | 0.481224 | 2078.035831 | 4674.257755 | 9.570599 | |||||||
10 | 8 | 0.479677 | 2084.735870 | 4727.047205 | 9.313703 | |||||||
10 | 9 | 0.475473 | 2103.169441 | 4704.491615 | 9.448886 | |||||||
2 | 2 | True | 1024 | 600 | 10 | 0 | 0.469123 | 2131.637096 | 4871.593714 | 7.836342 | ||
10 | 1 | 0.472183 | 2117.823720 | 4632.369041 | 7.794440 | |||||||
10 | 2 | 0.471514 | 2120.829582 | 4661.816835 | 7.792830 | |||||||
10 | 3 | 0.472720 | 2115.418553 | 4615.066528 | 7.801950 | |||||||
10 | 4 | 0.466531 | 2143.481016 | 4670.040846 | 7.791817 | |||||||
10 | 5 | 0.474493 | 2107.514739 | 4742.186785 | 7.782817 | |||||||
10 | 6 | 0.473662 | 2111.207962 | 4678.366899 | 7.603705 | |||||||
10 | 7 | 0.471409 | 2121.299028 | 4791.217089 | 7.847309 | |||||||
10 | 8 | 0.468963 | 2132.363558 | 4789.848566 | 7.508039 | |||||||
10 | 9 | 0.476291 | 2099.555254 | 4646.384478 | 7.767916 | |||||||
4 | 2 | True | 1024 | 600 | 10 | 0 | 0.465838 | 2146.670341 | 4637.297392 | 7.425994 | ||
10 | 1 | 0.459510 | 2176.231623 | 4771.982908 | 7.702440 | |||||||
10 | 2 | 0.457189 | 2187.279761 | 4693.547964 | 7.557511 | |||||||
10 | 3 | 0.463155 | 2159.104466 | 4686.470509 | 7.461697 | |||||||
10 | 4 | 0.459437 | 2176.578999 | 4653.425932 | 7.388800 | |||||||
10 | 5 | 0.461189 | 2168.306887 | 4649.534702 | 7.405192 | |||||||
10 | 6 | 0.459851 | 2174.616516 | 4677.816391 | 7.625759 | |||||||
10 | 7 | 0.460292 | 2172.532856 | 4699.117422 | 7.416129 | |||||||
10 | 8 | 0.458029 | 2183.267474 | 4749.050379 | 7.668465 | |||||||
10 | 9 | 0.457250 | 2186.987460 | 4728.041887 | 7.394373 | |||||||
8 | 2 | True | 1024 | 600 | 10 | 0 | 0.448426 | 2230.021060 | 4881.022930 | 6.358564 | ||
10 | 1 | 0.447450 | 2234.884620 | 4833.306551 | 6.405845 | |||||||
10 | 2 | 0.447692 | 2233.678490 | 4714.081526 | 6.411314 | |||||||
10 | 3 | 0.449703 | 2223.688662 | 4727.843761 | 6.498590 | |||||||
10 | 4 | 0.446264 | 2240.827024 | 4821.063042 | 6.466031 | |||||||
10 | 5 | 0.447525 | 2234.509915 | 4763.653517 | 6.378964 | |||||||
10 | 6 | 0.446304 | 2240.626216 | 4656.491518 | 6.479472 | |||||||
10 | 7 | 0.448708 | 2228.622943 | 4701.173306 | 6.423131 | |||||||
10 | 8 | 0.447020 | 2237.035245 | 4839.536905 | 6.500378 | |||||||
10 | 9 | 0.446514 | 2239.570051 | 4725.246906 | 6.514519 | |||||||
16 | 2 | True | 1024 | 600 | 10 | 0 | 0.443040 | 2257.131487 | 4761.220932 | 6.160311 | ||
10 | 1 | 0.444964 | 2247.375011 | 4645.025969 | 6.135449 | |||||||
10 | 2 | 0.445719 | 2243.564099 | 4739.571333 | 6.117813 | |||||||
10 | 3 | 0.445926 | 2242.522523 | 4691.355467 | 6.323762 | |||||||
10 | 4 | 0.444730 | 2248.555779 | 4867.135763 | 6.114915 | |||||||
10 | 5 | 0.441781 | 2263.564557 | 4699.393034 | 6.088033 | |||||||
10 | 6 | 0.442053 | 2262.172401 | 4729.875088 | 6.122828 | |||||||
10 | 7 | 0.443121 | 2256.722227 | 4730.833530 | 6.306559 | |||||||
10 | 8 | 0.441437 | 2265.327543 | 4706.488609 | 6.191246 | |||||||
10 | 9 | 0.442450 | 2260.142982 | 4633.033752 | 6.211273 | |||||||
32 | 2 | True | 1024 | 600 | 10 | 0 | 0.441659 | 2264.188550 | 7046.988964 | 5.898494 | ||
10 | 1 | 0.443310 | 2255.756468 | 4752.347708 | 6.041717 | |||||||
10 | 2 | 0.441976 | 2262.563989 | 4757.130861 | 5.883444 | |||||||
10 | 3 | 0.443412 | 2255.240895 | 4838.208675 | 5.935721 | |||||||
10 | 4 | 0.442814 | 2258.284524 | 4626.413584 | 5.847793 | |||||||
10 | 5 | 0.441853 | 2263.196304 | 4953.391552 | 5.801924 | |||||||
10 | 6 | 0.443172 | 2256.461382 | 4938.735247 | 6.233998 | |||||||
10 | 7 | 0.442252 | 2261.153892 | 4810.835838 | 5.887762 | |||||||
10 | 8 | 0.441839 | 2263.269097 | 4680.061817 | 5.924489 | |||||||
10 | 9 | 0.443198 | 2256.326482 | 4646.239042 | 6.009314 | |||||||
cpu-prebuilt | 1 | 2 | True | 1024 | 600 | 10 | 0 | 0.476430 | 2098.946333 | 6911.992073 | 9.578943 | |
10 | 1 | 0.479329 | 2086.250067 | 4802.347898 | 9.509683 | |||||||
10 | 2 | 0.479133 | 2087.101221 | 4653.066397 | 9.565115 | |||||||
10 | 3 | 0.480091 | 2082.938433 | 4607.165098 | 9.295821 | |||||||
10 | 4 | 0.477704 | 2093.345881 | 4627.895355 | 9.655595 | |||||||
10 | 5 | 0.478506 | 2089.837074 | 4740.164995 | 9.519935 | |||||||
10 | 6 | 0.473604 | 2111.468315 | 4751.509905 | 9.440780 | |||||||
10 | 7 | 0.475716 | 2102.094650 | 4671.503067 | 9.498119 | |||||||
10 | 8 | 0.476884 | 2096.944571 | 4664.308548 | 9.598494 | |||||||
10 | 9 | 0.476331 | 2099.380016 | 4684.918880 | 9.502530 | |||||||
2 | 2 | True | 1024 | 600 | 10 | 0 | 0.468431 | 2134.788275 | 4732.982874 | 7.852614 | ||
10 | 1 | 0.472935 | 2114.454389 | 4649.711609 | 7.798254 | |||||||
10 | 2 | 0.470190 | 2126.798034 | 4643.195629 | 7.697940 | |||||||
10 | 3 | 0.471013 | 2123.083591 | 4773.692131 | 7.840872 | |||||||
10 | 4 | 0.475274 | 2104.051471 | 4850.495815 | 7.591724 | |||||||
10 | 5 | 0.472168 | 2117.888451 | 4685.405493 | 7.899523 | |||||||
10 | 6 | 0.468009 | 2136.710882 | 4751.292706 | 7.935166 | |||||||
10 | 7 | 0.472980 | 2114.253998 | 4710.348606 | 8.239985 | |||||||
10 | 8 | 0.474203 | 2108.802080 | 4819.133282 | 7.782161 | |||||||
10 | 9 | 0.473089 | 2113.765717 | 4710.736036 | 8.140326 | |||||||
4 | 2 | True | 1024 | 600 | 10 | 0 | 0.456413 | 2190.999448 | 4674.053669 | 7.327020 | ||
10 | 1 | 0.456003 | 2192.967653 | 4681.468010 | 7.452399 | |||||||
10 | 2 | 0.459294 | 2177.252531 | 4655.152798 | 7.265180 | |||||||
10 | 3 | 0.461772 | 2165.570319 | 4762.456894 | 7.626474 | |||||||
10 | 4 | 0.461604 | 2166.359723 | 4708.060980 | 7.452428 | |||||||
10 | 5 | 0.460823 | 2170.032084 | 4666.865587 | 7.605553 | |||||||
10 | 6 | 0.459412 | 2176.693141 | 4695.546150 | 7.397562 | |||||||
10 | 7 | 0.460089 | 2173.491180 | 4695.769548 | 7.499397 | |||||||
10 | 8 | 0.460982 | 2169.284046 | 4728.900194 | 7.480860 | |||||||
10 | 9 | 0.458869 | 2179.272771 | 4866.041183 | 7.490665 | |||||||
8 | 2 | True | 1024 | 600 | 10 | 0 | 0.445128 | 2246.544719 | 4824.887991 | 6.349862 | ||
10 | 1 | 0.446106 | 2241.620868 | 4814.151287 | 6.454602 | |||||||
10 | 2 | 0.446176 | 2241.268754 | 4751.685143 | 6.356791 | |||||||
10 | 3 | 0.445251 | 2245.923698 | 4764.530420 | 6.336719 | |||||||
10 | 4 | 0.446161 | 2241.344512 | 4746.541023 | 6.455719 | |||||||
10 | 5 | 0.446886 | 2237.708509 | 4695.195913 | 6.394356 | |||||||
10 | 6 | 0.446231 | 2240.990847 | 4730.701923 | 6.395116 | |||||||
10 | 7 | 0.444921 | 2247.592241 | 4701.094151 | 6.470054 | |||||||
10 | 8 | 0.444265 | 2250.911266 | 4799.312592 | 6.382376 | |||||||
10 | 9 | 0.444193 | 2251.275152 | 4890.583754 | 6.191820 | |||||||
16 | 2 | True | 1024 | 600 | 10 | 0 | 0.442694 | 2258.895636 | 4723.585844 | 6.115980 | ||
10 | 1 | 0.443003 | 2257.322982 | 4619.927168 | 6.121911 | |||||||
10 | 2 | 0.443031 | 2257.177547 | 4690.367460 | 6.208442 | |||||||
10 | 3 | 0.442958 | 2257.551774 | 4842.099667 | 6.250903 | |||||||
10 | 4 | 0.441984 | 2262.527600 | 4723.618031 | 6.095320 | |||||||
10 | 5 | 0.441009 | 2267.529160 | 4709.165812 | 6.330647 | |||||||
10 | 6 | 0.443174 | 2256.451771 | 4732.079029 | 6.190538 | |||||||
10 | 7 | 0.443248 | 2256.072521 | 4688.783884 | 6.279618 | |||||||
10 | 8 | 0.442761 | 2258.555487 | 4755.360603 | 6.120138 | |||||||
10 | 9 | 0.443000 | 2257.334948 | 4673.398972 | 6.245270 | |||||||
32 | 2 | True | 1024 | 600 | 10 | 0 | 0.445693 | 2243.696325 | 4708.714724 | 5.976126 | ||
10 | 1 | 0.444501 | 2249.715857 | 4799.293756 | 5.980864 | |||||||
10 | 2 | 0.443733 | 2253.608018 | 4812.208176 | 5.862933 | |||||||
10 | 3 | 0.444597 | 2249.227196 | 4619.879246 | 5.906854 | |||||||
10 | 4 | 0.442427 | 2260.260180 | 4708.615303 | 5.930688 | |||||||
10 | 5 | 0.442084 | 2262.011275 | 4752.560377 | 6.009258 | |||||||
10 | 6 | 0.441787 | 2263.532028 | 4742.196798 | 6.043244 | |||||||
10 | 7 | 0.444153 | 2251.477160 | 4678.473949 | 6.093286 | |||||||
10 | 8 | 0.443272 | 2255.950890 | 4655.450106 | 5.904902 | |||||||
10 | 9 | 0.443241 | 2256.108768 | 4884.309292 | 6.025005 | |||||||
cuda | 1 | 2 | True | 1024 | 600 | 10 | 0 | 3.312149 | 301.918745 | 4553.108692 | 9.642363 | |
10 | 1 | 3.239443 | 308.695078 | 4603.839397 | 9.423256 | |||||||
10 | 2 | 3.318541 | 301.337242 | 4610.033751 | 9.488583 | |||||||
10 | 3 | 3.272390 | 305.587053 | 4625.099421 | 9.373426 | |||||||
10 | 4 | 3.288376 | 304.101467 | 4622.536659 | 9.427190 | |||||||
10 | 5 | 3.278278 | 305.038214 | 4729.156017 | 9.627342 | |||||||
10 | 6 | 3.244148 | 308.247328 | 4665.069103 | 9.451509 | |||||||
10 | 7 | 3.312236 | 301.910877 | 4691.882610 | 9.592414 | |||||||
10 | 8 | 3.261540 | 306.603670 | 4566.406250 | 9.423494 | |||||||
10 | 9 | 3.224632 | 310.112953 | 4607.881784 | 9.596944 | |||||||
2 | 2 | True | 1024 | 600 | 10 | 0 | 3.552907 | 281.459689 | 4668.402672 | 7.642150 | ||
10 | 1 | 3.518340 | 284.224987 | 4657.329798 | 7.844627 | |||||||
10 | 2 | 3.532334 | 283.098936 | 4700.743914 | 7.920146 | |||||||
10 | 3 | 3.539500 | 282.525778 | 4598.049879 | 7.964015 | |||||||
10 | 4 | 3.500998 | 285.632849 | 4626.263142 | 7.676423 | |||||||
10 | 5 | 3.551309 | 281.586289 | 4683.004141 | 7.845938 | |||||||
10 | 6 | 3.545740 | 282.028556 | 4633.757591 | 7.518411 | |||||||
10 | 7 | 3.523758 | 283.787966 | 4607.816696 | 7.668674 | |||||||
10 | 8 | 3.550711 | 281.633735 | 4610.222101 | 7.816374 | |||||||
10 | 9 | 3.518227 | 284.234047 | 4659.436464 | 7.707119 | |||||||
4 | 2 | True | 1024 | 600 | 10 | 0 | 3.674564 | 272.141159 | 4589.384079 | 7.491559 | ||
10 | 1 | 3.675187 | 272.094965 | 4600.687265 | 7.456094 | |||||||
10 | 2 | 3.668294 | 272.606254 | 4670.823097 | 7.364601 | |||||||
10 | 3 | 3.659768 | 273.241341 | 4663.695574 | 7.741481 | |||||||
10 | 4 | 3.680945 | 271.669388 | 4619.314671 | 7.494420 | |||||||
10 | 5 | 3.701009 | 270.196557 | 4702.200174 | 7.385522 | |||||||
10 | 6 | 3.685486 | 271.334648 | 4649.031162 | 7.692933 | |||||||
10 | 7 | 3.695861 | 270.572960 | 4589.505911 | 7.417113 | |||||||
10 | 8 | 3.682430 | 271.559834 | 4730.802298 | 7.475913 | |||||||
10 | 9 | 3.688631 | 271.103263 | 4620.339155 | 7.459700 | |||||||
8 | 2 | True | 1024 | 600 | 10 | 0 | 3.728697 | 268.190205 | 4689.132690 | 6.411090 | ||
10 | 1 | 3.733332 | 267.857254 | 4633.130074 | 6.382719 | |||||||
10 | 2 | 3.721300 | 268.723279 | 4610.522270 | 6.602168 | |||||||
10 | 3 | 3.712861 | 269.334078 | 4680.472374 | 6.342486 | |||||||
10 | 4 | 3.729187 | 268.154949 | 4663.403511 | 6.322131 | |||||||
10 | 5 | 3.715667 | 269.130677 | 4674.349308 | 6.383047 | |||||||
10 | 6 | 3.735976 | 267.667681 | 4610.460997 | 6.335691 | |||||||
10 | 7 | 3.728257 | 268.221825 | 4592.166662 | 6.378040 | |||||||
10 | 8 | 3.714321 | 269.228220 | 4643.437147 | 6.308481 | |||||||
10 | 9 | 3.718817 | 268.902749 | 4688.884020 | 6.420180 | |||||||
16 | 2 | True | 1024 | 600 | 10 | 0 | 3.713056 | 269.319922 | 4676.514626 | 6.128848 | ||
10 | 1 | 3.710434 | 269.510269 | 4574.917793 | 6.112933 | |||||||
10 | 2 | 3.715925 | 269.112006 | 4717.499256 | 6.175146 | |||||||
10 | 3 | 3.717626 | 268.988878 | 4645.964146 | 6.201915 | |||||||
10 | 4 | 3.717039 | 269.031346 | 4708.994865 | 6.256603 | |||||||
10 | 5 | 3.714478 | 269.216806 | 4657.868862 | 6.165959 | |||||||
10 | 6 | 3.704128 | 269.969091 | 4651.146889 | 6.379701 | |||||||
10 | 7 | 3.693570 | 270.740747 | 4633.554697 | 6.231189 | |||||||
10 | 8 | 3.710271 | 269.522071 | 4608.161926 | 6.170891 | |||||||
10 | 9 | 3.704759 | 269.923061 | 4632.548571 | 6.360725 | |||||||
tensorrt | 1 | 2 | True | 1024 | 600 | 10 | 0 | 3.376907 | 296.128988 | 71773.906469 | 9.302139 | |
10 | 1 | 3.348232 | 298.665047 | 71333.559275 | 9.582281 | |||||||
10 | 2 | 3.366134 | 297.076702 | 71861.565590 | 9.280920 | |||||||
10 | 3 | 3.369728 | 296.759844 | 71676.164389 | 9.327054 | |||||||
10 | 4 | 3.351475 | 298.376083 | 71406.909466 | 9.361982 | |||||||
10 | 5 | 3.369701 | 296.762228 | 71786.504984 | 9.517074 | |||||||
10 | 6 | 3.382741 | 295.618296 | 72182.452917 | 9.416580 | |||||||
10 | 7 | 3.356584 | 297.921896 | 72012.970686 | 9.425163 | |||||||
10 | 8 | 3.342434 | 299.183130 | 72414.334059 | 9.431243 | |||||||
10 | 9 | 3.362265 | 297.418594 | 71405.121565 | 9.265065 | |||||||
2 | 2 | True | 1024 | 600 | 10 | 0 | 3.598338 | 277.906060 | 72460.325241 | 7.761598 | ||
10 | 1 | 3.619488 | 276.282191 | 73288.720846 | 7.611036 | |||||||
10 | 2 | 3.625512 | 275.823116 | 73017.344475 | 7.620037 | |||||||
10 | 3 | 3.600910 | 277.707577 | 71886.828661 | 7.649243 | |||||||
10 | 4 | 3.609189 | 277.070522 | 72389.738083 | 7.569075 | |||||||
10 | 5 | 3.614754 | 276.643991 | 73603.370428 | 7.697105 | |||||||
10 | 6 | 3.626780 | 275.726676 | 72315.528631 | 7.667959 | |||||||
10 | 7 | 3.610072 | 277.002811 | 71280.921936 | 7.760704 | |||||||
10 | 8 | 3.603602 | 277.500153 | 72457.260370 | 7.785320 | |||||||
10 | 9 | 3.616836 | 276.484728 | 72930.105448 | 7.605672 | |||||||
4 | 2 | True | 1024 | 600 | 10 | 0 | 3.749659 | 266.690910 | 63406.803846 | 7.282495 | ||
10 | 1 | 3.770994 | 265.182078 | 62365.354538 | 7.390857 | |||||||
10 | 2 | 3.764669 | 265.627623 | 63301.706314 | 7.337838 | |||||||
10 | 3 | 3.779923 | 264.555633 | 62900.637388 | 7.436097 | |||||||
10 | 4 | 3.758543 | 266.060531 | 62595.251083 | 7.462770 | |||||||
10 | 5 | 3.739821 | 267.392457 | 62498.919249 | 7.585466 | |||||||
10 | 6 | 3.760241 | 265.940428 | 63171.914101 | 7.459760 | |||||||
10 | 7 | 3.767618 | 265.419662 | 63504.255295 | 7.384747 | |||||||
10 | 8 | 3.765990 | 265.534461 | 62592.798471 | 7.361025 | |||||||
10 | 9 | 3.764941 | 265.608430 | 63832.051754 | 7.310838 | |||||||
8 | 2 | True | 1024 | 600 | 10 | 0 | 3.790856 | 263.792664 | 63456.116199 | 6.390765 | ||
10 | 1 | 3.792566 | 263.673693 | 63586.563826 | 6.568715 | |||||||
10 | 2 | 3.796260 | 263.417184 | 62492.844582 | 6.305456 | |||||||
10 | 3 | 3.786046 | 264.127791 | 63372.258663 | 6.388098 | |||||||
10 | 4 | 3.813703 | 262.212336 | 62674.717426 | 6.489903 | |||||||
10 | 5 | 3.796162 | 263.423920 | 63579.843760 | 6.310716 | |||||||
10 | 6 | 3.815625 | 262.080282 | 61867.995501 | 6.435558 | |||||||
10 | 7 | 3.782634 | 264.366031 | 64045.851231 | 6.348684 | |||||||
10 | 8 | 3.802486 | 262.985826 | 62815.172434 | 6.436229 | |||||||
10 | 9 | 3.805993 | 262.743503 | 62830.606461 | 6.401584 | |||||||
16 | 2 | True | 1024 | 600 | 10 | 0 | 3.809337 | 262.512863 | 63666.782379 | 6.077066 | ||
10 | 1 | 3.801270 | 263.069987 | 62935.933828 | 6.170094 | |||||||
10 | 2 | 3.789768 | 263.868377 | 64053.315401 | 6.218269 | |||||||
10 | 3 | 3.800880 | 263.096988 | 63089.780092 | 6.116427 | |||||||
10 | 4 | 3.798629 | 263.252839 | 63936.655283 | 6.117716 | |||||||
10 | 5 | 3.793507 | 263.608307 | 62832.702875 | 6.145746 | |||||||
10 | 6 | 3.674101 | 272.175416 | 62334.528685 | 6.276503 | |||||||
10 | 7 | 3.796823 | 263.378084 | 63668.829679 | 6.201357 | |||||||
10 | 8 | 3.811932 | 262.334198 | 63301.749706 | 6.155752 | |||||||
10 | 9 | 3.799858 | 263.167739 | 63519.116163 | 6.351136 | |||||||
rcnn-inception-v2 | cpu | 1 | 2 | True | 600 | 1024 | 10 | 0 | 5.014147 | 199.435711 | 1498.870850 | 9.715676 |
10 | 1 | 5.042867 | 198.299885 | 1505.791903 | 9.608984 | |||||||
10 | 2 | 4.946498 | 202.163219 | 1473.861456 | 10.332584 | |||||||
10 | 3 | 4.990290 | 200.389147 | 1584.379911 | 10.267496 | |||||||
10 | 4 | 4.931754 | 202.767611 | 1560.732603 | 9.686112 | |||||||
10 | 5 | 5.009362 | 199.626207 | 1587.606430 | 9.686351 | |||||||
10 | 6 | 4.903904 | 203.919172 | 1524.977446 | 9.994268 | |||||||
10 | 7 | 5.082360 | 196.758986 | 1501.475334 | 9.787917 | |||||||
10 | 8 | 5.036479 | 198.551416 | 1551.583290 | 9.751916 | |||||||
10 | 9 | 4.905659 | 203.846216 | 1501.851797 | 9.498477 | |||||||
2 | 2 | True | 600 | 1024 | 10 | 0 | 5.272674 | 189.657092 | 1466.687441 | 7.930219 | ||
10 | 1 | 5.335643 | 187.418818 | 1585.123062 | 8.521616 | |||||||
10 | 2 | 5.316342 | 188.099265 | 1564.975500 | 7.825553 | |||||||
10 | 3 | 5.268346 | 189.812899 | 1525.840521 | 7.982373 | |||||||
10 | 4 | 5.404975 | 185.014725 | 1541.822433 | 8.040488 | |||||||
10 | 5 | 5.325708 | 187.768459 | 1537.496328 | 8.111715 | |||||||
10 | 6 | 5.331035 | 187.580824 | 1607.749939 | 8.147657 | |||||||
10 | 7 | 5.166681 | 193.547845 | 1590.650558 | 8.406579 | |||||||
10 | 8 | 5.356324 | 186.695218 | 1587.227345 | 8.009434 | |||||||
10 | 9 | 5.272217 | 189.673543 | 1561.925173 | 8.123875 | |||||||
4 | 2 | True | 600 | 1024 | 10 | 0 | 5.448908 | 183.522999 | 1501.704931 | 7.514775 | ||
10 | 1 | 5.369132 | 186.249852 | 1519.568443 | 7.727951 | |||||||
10 | 2 | 5.485446 | 182.300568 | 1513.799906 | 7.464796 | |||||||
10 | 3 | 5.385897 | 185.670078 | 1560.333729 | 7.785231 | |||||||
10 | 4 | 5.409991 | 184.843183 | 1547.524691 | 7.684201 | |||||||
10 | 5 | 5.359472 | 186.585546 | 1524.288654 | 7.822454 | |||||||
10 | 6 | 5.348534 | 186.967134 | 1518.525362 | 7.608354 | |||||||
10 | 7 | 5.386990 | 185.632408 | 1504.456282 | 7.741630 | |||||||
10 | 8 | 5.377758 | 185.951114 | 1522.876978 | 7.642746 | |||||||
10 | 9 | 5.329975 | 187.618136 | 1515.112877 | 7.878870 | |||||||
8 | 2 | True | 600 | 1024 | 10 | 0 | 5.349165 | 186.945051 | 1576.133728 | 6.847322 | ||
10 | 1 | 5.433229 | 184.052616 | 1562.856674 | 6.624192 | |||||||
10 | 2 | 5.406175 | 184.973657 | 1570.407391 | 6.713390 | |||||||
10 | 3 | 5.411611 | 184.787869 | 1529.011250 | 6.627277 | |||||||
10 | 4 | 5.377932 | 185.945094 | 1595.106125 | 6.435454 | |||||||
10 | 5 | 5.338694 | 187.311739 | 1603.112698 | 6.564945 | |||||||
10 | 6 | 5.435720 | 183.968276 | 1525.926113 | 6.634235 | |||||||
10 | 7 | 5.293217 | 188.921034 | 1562.609196 | 6.491125 | |||||||
10 | 8 | 5.461332 | 183.105528 | 1506.470919 | 6.450713 | |||||||
10 | 9 | 5.408010 | 184.910893 | 1497.475624 | 6.719351 | |||||||
16 | 2 | True | 600 | 1024 | 10 | 0 | 5.954560 | 167.938516 | 1557.972193 | 6.492734 | ||
10 | 1 | 5.845675 | 171.066642 | 1513.023138 | 6.231360 | |||||||
10 | 2 | 5.926130 | 168.744192 | 1549.762249 | 6.216884 | |||||||
10 | 3 | 5.939444 | 168.365926 | 1494.459629 | 6.225139 | |||||||
10 | 4 | 5.939874 | 168.353751 | 1589.697361 | 6.574623 | |||||||
10 | 5 | 5.921630 | 168.872416 | 1563.881397 | 6.486021 | |||||||
10 | 6 | 5.886893 | 169.868901 | 1493.456364 | 6.590150 | |||||||
10 | 7 | 5.919163 | 168.942794 | 1541.707277 | 6.275326 | |||||||
10 | 8 | 5.886155 | 169.890180 | 1614.044666 | 6.533414 | |||||||
10 | 9 | 5.948207 | 168.117896 | 1519.454002 | 6.238572 | |||||||
32 | 2 | True | 600 | 1024 | 10 | 0 | 5.867390 | 170.433529 | 2000.246286 | 5.991984 | ||
10 | 1 | 5.872519 | 170.284688 | 1568.295002 | 6.092377 | |||||||
10 | 2 | 5.864556 | 170.515902 | 1531.263351 | 6.254148 | |||||||
10 | 3 | 5.855742 | 170.772560 | 1511.621475 | 6.313439 | |||||||
10 | 4 | 5.863773 | 170.538656 | 1523.082495 | 6.220240 | |||||||
10 | 5 | 5.846251 | 171.049796 | 1498.371840 | 6.043233 | |||||||
10 | 6 | 5.807043 | 172.204696 | 1503.453970 | 6.258313 | |||||||
10 | 7 | 5.836637 | 171.331540 | 1472.190380 | 6.224837 | |||||||
10 | 8 | 5.823156 | 171.728186 | 1582.651854 | 6.172523 | |||||||
10 | 9 | 5.840139 | 171.228804 | 1499.148607 | 5.944114 | |||||||
cpu-prebuilt | 1 | 2 | True | 600 | 1024 | 10 | 0 | 4.731297 | 211.358547 | 1956.808805 | 9.831071 | |
10 | 1 | 4.785440 | 208.967209 | 1418.408871 | 9.634018 | |||||||
10 | 2 | 4.714778 | 212.099075 | 1499.061346 | 9.669900 | |||||||
10 | 3 | 4.635287 | 215.736389 | 1422.900200 | 9.493232 | |||||||
10 | 4 | 4.725668 | 211.610317 | 1446.428299 | 9.874105 | |||||||
10 | 5 | 4.667941 | 214.227200 | 1424.752712 | 9.541869 | |||||||
10 | 6 | 4.722773 | 211.740017 | 1425.207853 | 9.795189 | |||||||
10 | 7 | 4.651227 | 214.997053 | 1425.072908 | 9.863138 | |||||||
10 | 8 | 4.666653 | 214.286327 | 1459.944725 | 10.440350 | |||||||
10 | 9 | 4.664204 | 214.398861 | 1451.465368 | 9.746313 | |||||||
2 | 2 | True | 600 | 1024 | 10 | 0 | 5.019488 | 199.223518 | 1448.516369 | 8.101106 | ||
10 | 1 | 4.988228 | 200.471997 | 1423.604965 | 7.747293 | |||||||
10 | 2 | 5.131576 | 194.871902 | 1449.007034 | 7.976055 | |||||||
10 | 3 | 5.084748 | 196.666598 | 1437.984705 | 7.960260 | |||||||
10 | 4 | 5.058507 | 197.686791 | 1450.055122 | 8.035362 | |||||||
10 | 5 | 5.166586 | 193.551421 | 1482.403040 | 7.938087 | |||||||
10 | 6 | 5.127191 | 195.038557 | 1474.911928 | 8.123815 | |||||||
10 | 7 | 5.093358 | 196.334124 | 1440.686941 | 8.092284 | |||||||
10 | 8 | 4.970026 | 201.206207 | 1430.893183 | 7.984698 | |||||||
10 | 9 | 5.016672 | 199.335337 | 1441.020012 | 7.787883 | |||||||
4 | 2 | True | 600 | 1024 | 10 | 0 | 5.132435 | 194.839299 | 1462.011337 | 7.741839 | ||
10 | 1 | 5.169760 | 193.432570 | 1556.849003 | 7.588327 | |||||||
10 | 2 | 5.116872 | 195.431888 | 1509.188175 | 7.510215 | |||||||
10 | 3 | 5.180694 | 193.024337 | 1464.471579 | 7.693589 | |||||||
10 | 4 | 5.169763 | 193.432450 | 1450.300455 | 7.868409 | |||||||
10 | 5 | 5.223467 | 191.443741 | 1451.604366 | 7.518381 | |||||||
10 | 6 | 5.092083 | 196.383297 | 1449.978352 | 7.638454 | |||||||
10 | 7 | 5.120138 | 195.307255 | 1467.447281 | 7.812858 | |||||||
10 | 8 | 5.224269 | 191.414356 | 1443.993807 | 7.774144 | |||||||
10 | 9 | 5.209573 | 191.954315 | 1465.530634 | 7.917315 | |||||||
8 | 2 | True | 600 | 1024 | 10 | 0 | 5.211387 | 191.887498 | 1460.234880 | 6.753191 | ||
10 | 1 | 5.159525 | 193.816274 | 1445.772171 | 6.473005 | |||||||
10 | 2 | 5.188005 | 192.752331 | 1429.254770 | 6.613567 | |||||||
10 | 3 | 5.072365 | 197.146684 | 1428.463459 | 6.731093 | |||||||
10 | 4 | 5.132520 | 194.836080 | 1440.501451 | 6.570667 | |||||||
10 | 5 | 5.213028 | 191.827089 | 1431.637764 | 6.464541 | |||||||
10 | 6 | 5.189467 | 192.698032 | 1463.212490 | 6.386876 | |||||||
10 | 7 | 5.161262 | 193.751067 | 1430.485964 | 6.712347 | |||||||
10 | 8 | 5.206055 | 192.084014 | 1523.363590 | 6.445169 | |||||||
10 | 9 | 5.188151 | 192.746907 | 1486.027479 | 6.785393 | |||||||
16 | 2 | True | 600 | 1024 | 10 | 0 | 5.687760 | 175.816134 | 1450.564861 | 6.334804 | ||
10 | 1 | 5.649171 | 177.017137 | 1505.919218 | 6.413735 | |||||||
10 | 2 | 5.678731 | 176.095694 | 1453.777075 | 6.276630 | |||||||
10 | 3 | 5.713200 | 175.033256 | 1452.397585 | 6.360650 | |||||||
10 | 4 | 5.671152 | 176.331028 | 1435.543537 | 6.207824 | |||||||
10 | 5 | 5.663570 | 176.567063 | 1430.095434 | 6.297491 | |||||||
10 | 6 | 5.634694 | 177.471921 | 1447.620392 | 6.262504 | |||||||
10 | 7 | 5.656261 | 176.795244 | 1424.173355 | 6.572500 | |||||||
10 | 8 | 5.683345 | 175.952703 | 1447.904348 | 6.459363 | |||||||
10 | 9 | 5.674009 | 176.242232 | 1467.178345 | 6.471470 | |||||||
32 | 2 | True | 600 | 1024 | 10 | 0 | 5.609742 | 178.261332 | 1435.495138 | 5.966764 | ||
10 | 1 | 5.630896 | 177.591622 | 1439.628124 | 6.052073 | |||||||
10 | 2 | 5.626136 | 177.741870 | 1482.169390 | 6.120678 | |||||||
10 | 3 | 5.601327 | 178.529128 | 1444.671154 | 6.279349 | |||||||
10 | 4 | 5.624987 | 177.778199 | 1466.797113 | 6.110840 | |||||||
10 | 5 | 5.621275 | 177.895591 | 1456.978559 | 6.175332 | |||||||
10 | 6 | 5.631302 | 177.578814 | 1439.316511 | 6.169483 | |||||||
10 | 7 | 5.643570 | 177.192807 | 1456.930637 | 6.114166 | |||||||
10 | 8 | 5.649665 | 177.001648 | 1444.205761 | 6.016966 | |||||||
10 | 9 | 5.616136 | 178.058371 | 1442.853689 | 6.239720 | |||||||
cuda | 1 | 2 | True | 600 | 1024 | 10 | 0 | 18.356620 | 54.476261 | 1416.687250 | 9.582996 | |
10 | 1 | 18.061380 | 55.366755 | 1434.233189 | 9.861350 | |||||||
10 | 2 | 17.978157 | 55.623055 | 1429.165602 | 10.132551 | |||||||
10 | 3 | 18.031176 | 55.459499 | 1437.551975 | 9.672880 | |||||||
10 | 4 | 18.085601 | 55.292606 | 1444.493055 | 9.456038 | |||||||
10 | 5 | 17.938175 | 55.747032 | 1448.664904 | 9.703994 | |||||||
10 | 6 | 18.289861 | 54.675102 | 1463.722229 | 9.909034 | |||||||
10 | 7 | 18.024202 | 55.480957 | 1454.885721 | 9.685397 | |||||||
10 | 8 | 17.665583 | 56.607246 | 1457.566261 | 10.692358 | |||||||
10 | 9 | 17.817093 | 56.125879 | 1427.454233 | 9.729981 | |||||||
2 | 2 | True | 600 | 1024 | 10 | 0 | 22.388726 | 44.665337 | 1432.064295 | 8.013248 | ||
10 | 1 | 22.363598 | 44.715524 | 1457.754374 | 8.409679 | |||||||
10 | 2 | 22.093308 | 45.262575 | 1428.236723 | 8.197665 | |||||||
10 | 3 | 22.525135 | 44.394851 | 1435.927868 | 7.975638 | |||||||
10 | 4 | 22.912057 | 43.645144 | 1431.225300 | 7.717252 | |||||||
10 | 5 | 22.225364 | 44.993639 | 1423.159599 | 7.735074 | |||||||
10 | 6 | 22.307221 | 44.828534 | 1454.227448 | 8.231044 | |||||||
10 | 7 | 22.606842 | 44.234395 | 1440.490723 | 8.176088 | |||||||
10 | 8 | 21.805697 | 45.859575 | 1473.582029 | 7.986307 | |||||||
10 | 9 | 22.413911 | 44.615149 | 1448.654175 | 8.064926 | |||||||
4 | 2 | True | 600 | 1024 | 10 | 0 | 24.050839 | 41.578591 | 1468.189001 | 7.651746 | ||
10 | 1 | 23.947507 | 41.758001 | 1457.059383 | 7.923931 | |||||||
10 | 2 | 25.217937 | 39.654315 | 1450.780630 | 7.563680 | |||||||
10 | 3 | 24.222864 | 41.283309 | 1444.934607 | 7.651985 | |||||||
10 | 4 | 24.246003 | 41.243911 | 1442.461967 | 7.494748 | |||||||
10 | 5 | 25.259550 | 39.588988 | 1447.603941 | 7.571995 | |||||||
10 | 6 | 24.393750 | 40.994108 | 1461.820126 | 7.508159 | |||||||
10 | 7 | 24.508888 | 40.801525 | 1444.098473 | 7.941574 | |||||||
10 | 8 | 25.118075 | 39.811969 | 1459.584475 | 7.815182 | |||||||
10 | 9 | 23.906694 | 41.829288 | 1459.226847 | 7.691115 | |||||||
8 | 2 | True | 600 | 1024 | 10 | 0 | 25.647059 | 38.990825 | 1424.114227 | 6.726891 | ||
10 | 1 | 25.092116 | 39.853156 | 1445.759535 | 6.453142 | |||||||
10 | 2 | 25.419004 | 39.340645 | 1446.643353 | 6.523430 | |||||||
10 | 3 | 25.541015 | 39.152712 | 1458.364010 | 6.682336 | |||||||
10 | 4 | 25.473944 | 39.255798 | 1430.957079 | 6.775945 | |||||||
10 | 5 | 25.806734 | 38.749576 | 1454.945564 | 6.586790 | |||||||
10 | 6 | 25.963829 | 38.515121 | 1448.742151 | 6.435499 | |||||||
10 | 7 | 25.178860 | 39.715856 | 1445.089817 | 6.762639 | |||||||
10 | 8 | 25.524986 | 39.177299 | 1455.610275 | 6.430954 | |||||||
10 | 9 | 25.785197 | 38.781941 | 1440.744162 | 6.651729 | |||||||
16 | 2 | True | 600 | 1024 | 10 | 0 | 25.987668 | 38.479790 | 1426.766396 | 6.466702 | ||
10 | 1 | 25.034530 | 39.944828 | 1419.351578 | 6.508283 | |||||||
10 | 2 | 25.371050 | 39.415002 | 1438.000917 | 6.564394 | |||||||
10 | 3 | 25.619527 | 39.032727 | 1467.727900 | 6.300062 | |||||||
10 | 4 | 25.525073 | 39.177164 | 1437.742710 | 6.188750 | |||||||
10 | 5 | 25.435363 | 39.315343 | 1448.985815 | 6.509133 | |||||||
10 | 6 | 25.863934 | 38.663879 | 1453.492165 | 6.320909 | |||||||
10 | 7 | 25.066211 | 39.894342 | 1441.774607 | 6.310403 | |||||||
10 | 8 | 25.542512 | 39.150417 | 1431.310892 | 6.462514 | |||||||
10 | 9 | 25.422470 | 39.335281 | 1459.959507 | 6.622389 | |||||||
32 | 2 | True | 600 | 1024 | 10 | 0 | 25.799874 | 38.759880 | 1449.286938 | 6.259121 | ||
10 | 1 | 25.739995 | 38.850047 | 1447.102070 | 6.001525 | |||||||
10 | 2 | 25.682806 | 38.936555 | 1433.722258 | 6.029718 | |||||||
10 | 3 | 25.064315 | 39.897360 | 1440.608501 | 6.020978 | |||||||
10 | 4 | 25.591951 | 39.074786 | 1452.372074 | 6.021012 | |||||||
10 | 5 | 25.341169 | 39.461479 | 1455.724001 | 5.995147 | |||||||
10 | 6 | 25.481194 | 39.244629 | 1432.259560 | 6.000403 | |||||||
10 | 7 | 25.517978 | 39.188057 | 1446.592093 | 6.137870 | |||||||
10 | 8 | 25.394582 | 39.378479 | 1452.353001 | 6.222215 | |||||||
10 | 9 | 25.738702 | 38.851999 | 1431.207895 | 6.265253 | |||||||
tensorrt | 1 | 2 | True | 600 | 1024 | 10 | 0 | 18.262863 | 54.755926 | 17054.683208 | 9.464860 | |
10 | 1 | 17.575053 | 56.898832 | 17040.428877 | 9.784460 | |||||||
10 | 2 | 18.187157 | 54.983854 | 16899.039745 | 9.646773 | |||||||
10 | 3 | 17.890735 | 55.894852 | 16674.649715 | 9.531498 | |||||||
10 | 4 | 17.856993 | 56.000471 | 16875.169754 | 9.568095 | |||||||
10 | 5 | 17.947232 | 55.718899 | 16942.353725 | 9.413719 | |||||||
10 | 6 | 17.661938 | 56.618929 | 17089.957237 | 9.646893 | |||||||
10 | 7 | 18.166047 | 55.047750 | 17048.625946 | 9.444356 | |||||||
10 | 8 | 17.906699 | 55.845022 | 16540.392637 | 9.705305 | |||||||
10 | 9 | 18.136433 | 55.137634 | 17052.166224 | 9.509802 | |||||||
2 | 2 | True | 600 | 1024 | 10 | 0 | 21.331977 | 46.877980 | 17464.916706 | 7.911503 | ||
10 | 1 | 22.205243 | 45.034409 | 17496.206284 | 7.734179 | |||||||
10 | 2 | 22.556570 | 44.332981 | 17304.871798 | 7.731199 | |||||||
10 | 3 | 21.681144 | 46.123028 | 17672.189474 | 7.677436 | |||||||
10 | 4 | 21.953500 | 45.550823 | 17278.563499 | 7.756829 | |||||||
10 | 5 | 21.282295 | 46.987414 | 17386.888504 | 7.874489 | |||||||
10 | 6 | 21.715999 | 46.048999 | 17380.331516 | 7.769227 | |||||||
10 | 7 | 21.653329 | 46.182275 | 17525.537491 | 7.760108 | |||||||
10 | 8 | 21.685740 | 46.113253 | 17375.267029 | 7.783175 | |||||||
10 | 9 | 21.975642 | 45.504928 | 17431.662321 | 7.817864 | |||||||
4 | 2 | True | 600 | 1024 | 10 | 0 | 23.671323 | 42.245209 | 13168.403149 | 7.465363 | ||
10 | 1 | 24.453910 | 40.893257 | 12983.771563 | 7.571787 | |||||||
10 | 2 | 24.499725 | 40.816784 | 12947.808743 | 7.530928 | |||||||
10 | 3 | 24.303007 | 41.147172 | 12901.455641 | 7.413596 | |||||||
10 | 4 | 24.247440 | 41.241467 | 13094.930172 | 7.633865 | |||||||
10 | 5 | 24.366717 | 41.039586 | 12983.961821 | 7.611096 | |||||||
10 | 6 | 24.121311 | 41.457117 | 13073.016167 | 7.443249 | |||||||
10 | 7 | 24.264378 | 41.212678 | 12953.689337 | 7.479340 | |||||||
10 | 8 | 24.217584 | 41.292310 | 13024.133205 | 7.487029 | |||||||
10 | 9 | 24.309592 | 41.136026 | 12940.512657 | 7.497519 | |||||||
8 | 2 | True | 600 | 1024 | 10 | 0 | 25.155812 | 39.752245 | 12938.249826 | 6.490529 | ||
10 | 1 | 25.961157 | 38.519084 | 12916.830063 | 6.556660 | |||||||
10 | 2 | 25.765259 | 38.811952 | 12981.657505 | 6.506383 | |||||||
10 | 3 | 25.533183 | 39.164722 | 12793.953180 | 6.464794 | |||||||
10 | 4 | 25.083525 | 39.866805 | 12827.604294 | 6.476507 | |||||||
10 | 5 | 26.215690 | 38.145095 | 12949.955940 | 6.514266 | |||||||
10 | 6 | 24.136615 | 41.430831 | 13063.522577 | 6.440580 | |||||||
10 | 7 | 25.839187 | 38.700908 | 13103.403330 | 6.555989 | |||||||
10 | 8 | 25.376557 | 39.406449 | 12828.648806 | 6.730393 | |||||||
10 | 9 | 25.413209 | 39.349616 | 13046.003580 | 6.464243 | |||||||
16 | 2 | True | 600 | 1024 | 10 | 0 | 24.577518 | 40.687591 | 12772.939444 | 6.251216 | ||
10 | 1 | 25.484130 | 39.240107 | 12845.211029 | 6.521888 | |||||||
10 | 2 | 25.402281 | 39.366543 | 12757.096291 | 6.329700 | |||||||
10 | 3 | 25.397292 | 39.374277 | 12854.661465 | 6.233133 | |||||||
10 | 4 | 25.350627 | 39.446756 | 12700.048208 | 6.255448 | |||||||
10 | 5 | 25.673659 | 38.950428 | 12906.770468 | 6.240763 | |||||||
10 | 6 | 25.323058 | 39.489701 | 12794.317722 | 6.543636 | |||||||
10 | 7 | 25.715884 | 38.886473 | 12839.040041 | 6.350070 | |||||||
10 | 8 | 25.261461 | 39.585993 | 12848.332882 | 6.533489 | |||||||
10 | 9 | 25.589750 | 39.078146 | 12715.066671 | 6.267227 | |||||||
32 | 2 | True | 600 | 1024 | 10 | 0 | 25.458072 | 39.280273 | 12844.294071 | 6.059401 | ||
10 | 1 | 25.299764 | 39.526060 | 12783.873081 | 6.105229 | |||||||
10 | 2 | 25.604283 | 39.055966 | 12953.673840 | 6.216351 | |||||||
10 | 3 | 25.667001 | 38.960531 | 12744.321346 | 6.073479 | |||||||
10 | 4 | 25.410101 | 39.354429 | 12983.851194 | 6.130971 | |||||||
10 | 5 | 25.206263 | 39.672680 | 12954.895973 | 6.046593 | |||||||
10 | 6 | 25.566489 | 39.113700 | 12904.195309 | 6.289415 | |||||||
10 | 7 | 25.532818 | 39.165281 | 12871.153831 | 6.005283 | |||||||
10 | 8 | 25.389638 | 39.386146 | 12927.368402 | 6.088052 | |||||||
10 | 9 | 25.302254 | 39.522171 | 12840.082169 | 6.215300 | |||||||
tensorrt-dynamic | 1 | 2 | True | 600 | 1024 | 10 | 0 | 19.471711 | 51.356554 | 8882.416964 | 9.399652 | |
10 | 1 | 19.488358 | 51.312685 | 8742.156982 | 9.500861 | |||||||
10 | 2 | 19.741153 | 50.655603 | 8809.425831 | 9.415388 | |||||||
10 | 3 | 20.174040 | 49.568653 | 8727.215528 | 9.346485 | |||||||
10 | 4 | 19.717859 | 50.715446 | 8771.088362 | 9.436131 | |||||||
10 | 5 | 19.789120 | 50.532818 | 8779.867887 | 9.456873 | |||||||
10 | 6 | 19.347849 | 51.685333 | 8846.498489 | 9.612441 | |||||||
10 | 7 | 19.634232 | 50.931454 | 8748.760462 | 9.413242 | |||||||
10 | 8 | 20.592616 | 48.561096 | 8759.370089 | 9.451628 | |||||||
10 | 9 | 19.604223 | 51.009417 | 8846.726894 | 9.759068 | |||||||
2 | 2 | True | 600 | 1024 | 10 | 0 | 24.902283 | 40.156960 | 8845.126629 | 7.715225 | ||
10 | 1 | 25.927977 | 38.568377 | 8732.381105 | 7.721901 | |||||||
10 | 2 | 26.110610 | 38.298607 | 8835.674286 | 7.717729 | |||||||
10 | 3 | 24.664977 | 40.543318 | 8861.158371 | 7.768750 | |||||||
10 | 4 | 25.611802 | 39.044499 | 8831.889391 | 7.829726 | |||||||
10 | 5 | 25.324558 | 39.487362 | 8809.125185 | 7.814646 | |||||||
10 | 6 | 25.166000 | 39.736152 | 8763.042688 | 7.672012 | |||||||
10 | 7 | 26.793816 | 37.322044 | 8699.295521 | 8.072317 | |||||||
10 | 8 | 25.743851 | 38.844228 | 8853.743315 | 7.687807 | |||||||
10 | 9 | 25.975426 | 38.497925 | 8777.847528 | 7.730305 | |||||||
4 | 2 | True | 600 | 1024 | 10 | 0 | 27.345878 | 36.568582 | 8896.489620 | 7.618845 | ||
10 | 1 | 26.674027 | 37.489653 | 8785.809994 | 7.472098 | |||||||
10 | 2 | 26.936552 | 37.124276 | 9066.257954 | 7.429898 | |||||||
10 | 3 | 27.555808 | 36.289990 | 8813.172817 | 7.455707 | |||||||
10 | 4 | 27.355153 | 36.556184 | 8797.575474 | 7.526100 | |||||||
10 | 5 | 27.546443 | 36.302328 | 8893.589020 | 7.406443 | |||||||
10 | 6 | 27.583625 | 36.253393 | 8820.943117 | 7.642150 | |||||||
10 | 7 | 27.066007 | 36.946714 | 8782.052517 | 7.625014 | |||||||
10 | 8 | 26.869900 | 37.216365 | 8864.279985 | 7.550091 | |||||||
10 | 9 | 27.119075 | 36.874413 | 8867.530107 | 7.411540 | |||||||
8 | 2 | True | 600 | 1024 | 10 | 0 | 28.623931 | 34.935802 | 8802.629948 | 6.562367 | ||
10 | 1 | 28.367541 | 35.251558 | 8795.866966 | 6.728917 | |||||||
10 | 2 | 27.900761 | 35.841316 | 8880.637407 | 6.499916 | |||||||
10 | 3 | 28.437188 | 35.165220 | 8802.983761 | 6.835207 | |||||||
10 | 4 | 28.814652 | 34.704566 | 8907.945871 | 6.456673 | |||||||
10 | 5 | 28.359725 | 35.261273 | 8850.032091 | 6.420612 | |||||||
10 | 6 | 28.682311 | 34.864694 | 8850.908995 | 6.408900 | |||||||
10 | 7 | 28.899303 | 34.602910 | 8853.540421 | 6.455719 | |||||||
10 | 8 | 28.408875 | 35.200268 | 8787.514210 | 6.467193 | |||||||
10 | 9 | 29.035769 | 34.440279 | 8714.293718 | 6.656498 | |||||||
16 | 2 | True | 600 | 1024 | 10 | 0 | 29.717633 | 33.650056 | 8770.996571 | 6.254293 | ||
10 | 1 | 29.310185 | 34.117833 | 8788.775206 | 6.225012 | |||||||
10 | 2 | 29.064026 | 34.406796 | 8714.112520 | 6.343611 | |||||||
10 | 3 | 29.366414 | 34.052506 | 8808.066130 | 6.363176 | |||||||
10 | 4 | 29.439665 | 33.967778 | 8803.171635 | 6.349988 | |||||||
10 | 5 | 29.161981 | 34.291223 | 8801.988602 | 6.538227 | |||||||
10 | 6 | 29.290625 | 34.140617 | 8902.085066 | 6.226599 | |||||||
10 | 7 | 29.781423 | 33.577979 | 8854.831934 | 6.227456 | |||||||
10 | 8 | 29.434706 | 33.973500 | 8847.275496 | 6.330125 | |||||||
10 | 9 | 29.232406 | 34.208611 | 8767.259359 | 6.279066 | |||||||
rcnn-nas-lowproposals | cpu | 1 | 2 | True | 1200 | 1200 | 10 | 0 | 0.422802 | 2365.170717 | 2737.598181 | 9.857059 |
10 | 1 | 0.424297 | 2356.838703 | 2750.021696 | 10.446787 | |||||||
10 | 2 | 0.425269 | 2351.453304 | 2692.065239 | 9.801030 | |||||||
10 | 3 | 0.424194 | 2357.411623 | 2690.779448 | 9.919405 | |||||||
10 | 4 | 0.422270 | 2368.151188 | 2773.290396 | 9.843230 | |||||||
10 | 5 | 0.422163 | 2368.752956 | 2624.770880 | 9.850144 | |||||||
10 | 6 | 0.425744 | 2348.830462 | 2733.825207 | 10.105371 | |||||||
10 | 7 | 0.425861 | 2348.184109 | 2787.533522 | 10.225415 | |||||||
10 | 8 | 0.424353 | 2356.526852 | 2670.963526 | 9.792089 | |||||||
10 | 9 | 0.418898 | 2387.213230 | 2661.247730 | 10.092616 | |||||||
2 | 2 | True | 1200 | 1200 | 10 | 0 | 0.426305 | 2345.739245 | 2773.810387 | 7.925332 | ||
10 | 1 | 0.428993 | 2331.039786 | 2669.348717 | 8.184373 | |||||||
10 | 2 | 0.424239 | 2357.163906 | 2642.301559 | 8.188963 | |||||||
10 | 3 | 0.424178 | 2357.503533 | 2726.520061 | 8.347154 | |||||||
10 | 4 | 0.425631 | 2349.451661 | 2632.941961 | 8.068979 | |||||||
10 | 5 | 0.425474 | 2350.321770 | 2602.002144 | 8.147836 | |||||||
10 | 6 | 0.426202 | 2346.306801 | 2581.935644 | 8.292913 | |||||||
10 | 7 | 0.422632 | 2366.124988 | 2635.398865 | 8.129060 | |||||||
10 | 8 | 0.423764 | 2359.805942 | 2767.369032 | 8.429885 | |||||||
10 | 9 | 0.426602 | 2344.103336 | 2670.548439 | 8.455515 | |||||||
4 | 2 | True | 1200 | 1200 | 10 | 0 | 0.413391 | 2419.015110 | 2719.013691 | 7.812947 | ||
10 | 1 | 0.383810 | 2605.458200 | 2780.741453 | 8.239448 | |||||||
10 | 2 | 0.410710 | 2434.805334 | 2718.132496 | 7.932514 | |||||||
10 | 3 | 0.408973 | 2445.148945 | 2635.082483 | 7.753611 | |||||||
10 | 4 | 0.404520 | 2472.068489 | 2686.142921 | 8.064926 | |||||||
10 | 5 | 0.407546 | 2453.712821 | 2728.694439 | 7.603019 | |||||||
10 | 6 | 0.407012 | 2456.929028 | 2756.821156 | 7.875770 | |||||||
10 | 7 | 0.414891 | 2410.270452 | 2732.528687 | 7.674634 | |||||||
10 | 8 | 0.403977 | 2475.385547 | 2655.443192 | 7.812589 | |||||||
10 | 9 | 0.410397 | 2436.666965 | 2581.789732 | 7.780552 | |||||||
8 | 2 | True | 1200 | 1200 | 10 | 0 | 0.409692 | 2440.859675 | 2723.955870 | 6.748095 | ||
10 | 1 | 0.408224 | 2449.632823 | 2662.474394 | 6.819546 | |||||||
10 | 2 | 0.409923 | 2439.483613 | 2782.727242 | 6.641164 | |||||||
10 | 3 | 0.410774 | 2434.425950 | 2610.941410 | 6.880209 | |||||||
10 | 4 | 0.410323 | 2437.106162 | 2621.670246 | 6.747261 | |||||||
10 | 5 | 0.408022 | 2450.850636 | 2767.273664 | 6.716713 | |||||||
10 | 6 | 0.407304 | 2455.170274 | 2680.396080 | 6.646156 | |||||||
10 | 7 | 0.408581 | 2447.495490 | 2784.536600 | 6.836891 | |||||||
10 | 8 | 0.406530 | 2459.843129 | 2648.112774 | 6.584793 | |||||||
10 | 9 | 0.410899 | 2433.690846 | 2724.629641 | 6.609336 | |||||||
16 | 2 | True | 1200 | 1200 | 10 | 0 | 0.347720 | 2875.881150 | 2602.493048 | 6.734543 | ||
10 | 1 | 0.345282 | 2896.181986 | 2752.411366 | 6.995350 | |||||||
10 | 2 | 0.341455 | 2928.640544 | 2760.817528 | 6.562606 | |||||||
10 | 3 | 0.344686 | 2901.188508 | 2695.853710 | 6.522126 | |||||||
10 | 4 | 0.337652 | 2961.632535 | 2750.416994 | 6.470360 | |||||||
10 | 5 | 0.338795 | 2951.634616 | 2767.542124 | 6.454885 | |||||||
10 | 6 | 0.340214 | 2939.327523 | 2680.156946 | 6.556422 | |||||||
10 | 7 | 0.337539 | 2962.623239 | 2645.760298 | 6.512657 | |||||||
10 | 8 | 0.336814 | 2968.998060 | 2791.553736 | 6.606594 | |||||||
10 | 9 | 0.338992 | 2949.924231 | 2613.782883 | 6.593280 | |||||||
32 | 2 | True | 1200 | 1200 | 10 | 0 | 0.342457 | 2920.075461 | 2630.548000 | 6.267168 | ||
10 | 1 | 0.345298 | 2896.047853 | 2688.624620 | 6.448139 | |||||||
10 | 2 | 0.347817 | 2875.072852 | 2706.780910 | 6.241683 | |||||||
10 | 3 | 0.343870 | 2908.073343 | 2681.253910 | 6.221186 | |||||||
10 | 4 | 0.346743 | 2883.977517 | 2751.889467 | 6.322131 | |||||||
10 | 5 | 0.348021 | 2873.386696 | 2747.138500 | 6.238777 | |||||||
10 | 6 | 0.352098 | 2840.122133 | 2750.693798 | 6.202526 | |||||||
10 | 7 | 0.351400 | 2845.761634 | 2763.027191 | 6.425463 | |||||||
10 | 8 | 0.349093 | 2864.565723 | 2688.318491 | 6.224327 | |||||||
10 | 9 | 0.347885 | 2874.511279 | 2760.948896 | 6.199230 | |||||||
cpu-prebuilt | 1 | 2 | True | 1200 | 1200 | 10 | 0 | 0.412067 | 2426.792383 | 6361.849070 | 9.966373 | |
10 | 1 | 0.415427 | 2407.164574 | 2569.520712 | 10.451794 | |||||||
10 | 2 | 0.412061 | 2426.827908 | 2573.592901 | 9.870052 | |||||||
10 | 3 | 0.412336 | 2425.205469 | 2561.060429 | 9.855032 | |||||||
10 | 4 | 0.411725 | 2428.805351 | 2551.715851 | 9.871840 | |||||||
10 | 5 | 0.410960 | 2433.329105 | 2559.540749 | 9.883046 | |||||||
10 | 6 | 0.411715 | 2428.862333 | 2562.439680 | 9.879351 | |||||||
10 | 7 | 0.412013 | 2427.105427 | 2617.561102 | 9.896278 | |||||||
10 | 8 | 0.410353 | 2436.924219 | 2543.494463 | 9.835482 | |||||||
10 | 9 | 0.417485 | 2395.296812 | 2572.293997 | 9.902477 | |||||||
2 | 2 | True | 1200 | 1200 | 10 | 0 | 0.411213 | 2431.826830 | 2644.977331 | 7.978022 | ||
10 | 1 | 0.414424 | 2412.988544 | 2561.379671 | 8.155406 | |||||||
10 | 2 | 0.412171 | 2426.176071 | 2534.359455 | 8.223176 | |||||||
10 | 3 | 0.413062 | 2420.944810 | 2574.661016 | 7.916808 | |||||||
10 | 4 | 0.415174 | 2408.629894 | 2594.500303 | 8.090079 | |||||||
10 | 5 | 0.408385 | 2448.668957 | 2567.672968 | 8.264244 | |||||||
10 | 6 | 0.410635 | 2435.251117 | 2579.747677 | 8.628190 | |||||||
10 | 7 | 0.412063 | 2426.814079 | 2595.364809 | 8.284450 | |||||||
10 | 8 | 0.413065 | 2420.928001 | 2566.778660 | 8.005679 | |||||||
10 | 9 | 0.412055 | 2426.860809 | 2530.684233 | 7.984638 | |||||||
4 | 2 | True | 1200 | 1200 | 10 | 0 | 0.408507 | 2447.936237 | 2578.824520 | 7.659644 | ||
10 | 1 | 0.407047 | 2456.720412 | 2606.344223 | 7.800460 | |||||||
10 | 2 | 0.406182 | 2461.948037 | 2548.595190 | 7.712364 | |||||||
10 | 3 | 0.406351 | 2460.924327 | 2597.253084 | 7.743061 | |||||||
10 | 4 | 0.406853 | 2457.892478 | 2595.927000 | 7.790834 | |||||||
10 | 5 | 0.407891 | 2451.637506 | 2562.724352 | 7.844478 | |||||||
10 | 6 | 0.407127 | 2456.234574 | 2530.983925 | 7.697970 | |||||||
10 | 7 | 0.407628 | 2453.219116 | 2589.909554 | 7.688671 | |||||||
10 | 8 | 0.403611 | 2477.634072 | 2560.188293 | 8.168221 | |||||||
10 | 9 | 0.406113 | 2462.365985 | 2535.008907 | 7.906646 | |||||||
8 | 2 | True | 1200 | 1200 | 10 | 0 | 0.400541 | 2496.621668 | 2534.344435 | 6.722003 | ||
10 | 1 | 0.401684 | 2489.517391 | 2566.886187 | 6.748512 | |||||||
10 | 2 | 0.401358 | 2491.544008 | 2518.408298 | 6.893903 | |||||||
10 | 3 | 0.401129 | 2492.961645 | 2573.572874 | 6.724015 | |||||||
10 | 4 | 0.402803 | 2482.601255 | 2652.946472 | 6.739601 | |||||||
10 | 5 | 0.401491 | 2490.716219 | 2643.571377 | 6.681859 | |||||||
10 | 6 | 0.402963 | 2481.614977 | 2521.253109 | 6.667063 | |||||||
10 | 7 | 0.402671 | 2483.415842 | 2550.433159 | 6.755248 | |||||||
10 | 8 | 0.401592 | 2490.090817 | 2552.996635 | 6.816626 | |||||||
10 | 9 | 0.402486 | 2484.557211 | 2571.765423 | 6.753311 | |||||||
16 | 2 | True | 1200 | 1200 | 10 | 0 | 0.387576 | 2580.137551 | 2575.905085 | 6.615490 | ||
10 | 1 | 0.387670 | 2579.514548 | 2548.897743 | 6.499007 | |||||||
10 | 2 | 0.388693 | 2572.727650 | 2547.498941 | 6.509326 | |||||||
10 | 3 | 0.387914 | 2577.890739 | 2567.530155 | 6.485753 | |||||||
10 | 4 | 0.387272 | 2582.166836 | 2572.117090 | 6.529614 | |||||||
10 | 5 | 0.384598 | 2600.119963 | 2588.905811 | 6.639086 | |||||||
10 | 6 | 0.386767 | 2585.533246 | 2571.714163 | 6.554551 | |||||||
10 | 7 | 0.384615 | 2600.002646 | 2643.561602 | 6.482288 | |||||||
10 | 8 | 0.383358 | 2608.531043 | 2667.171478 | 6.447896 | |||||||
10 | 9 | 0.384187 | 2602.899581 | 2691.616535 | 6.454766 | |||||||
32 | 2 | True | 1200 | 1200 | 10 | 0 | 0.354244 | 2822.915569 | 2539.497375 | 6.164365 | ||
10 | 1 | 0.355216 | 2815.188333 | 2579.700947 | 6.294392 | |||||||
10 | 2 | 0.358326 | 2790.754512 | 2586.631536 | 6.237816 | |||||||
10 | 3 | 0.356251 | 2807.010278 | 2562.347651 | 6.228499 | |||||||
10 | 4 | 0.356326 | 2806.418195 | 2578.271866 | 6.219782 | |||||||
10 | 5 | 0.359503 | 2781.621151 | 2526.288271 | 6.199598 | |||||||
10 | 6 | 0.357065 | 2800.613753 | 2606.225014 | 6.242082 | |||||||
10 | 7 | 0.356330 | 2806.383803 | 2601.206541 | 6.294459 | |||||||
10 | 8 | 0.357374 | 2798.189528 | 2694.718838 | 6.200224 | |||||||
10 | 9 | 0.356896 | 2801.935650 | 2544.285059 | 6.437883 | |||||||
cuda | 1 | 2 | True | 1200 | 1200 | 10 | 0 | 2.771166 | 360.858917 | 2582.018852 | 9.901285 | |
10 | 1 | 2.759923 | 362.329006 | 2621.037960 | 9.940386 | |||||||
10 | 2 | 2.752753 | 363.272667 | 2593.099356 | 9.884000 | |||||||
10 | 3 | 2.785760 | 358.968496 | 2569.315672 | 9.851217 | |||||||
10 | 4 | 2.765374 | 361.614704 | 2605.367422 | 9.914398 | |||||||
10 | 5 | 2.764355 | 361.747980 | 2599.323988 | 9.861708 | |||||||
10 | 6 | 2.773869 | 360.507250 | 2576.275110 | 10.036945 | |||||||
10 | 7 | 2.807295 | 356.214762 | 2588.441133 | 9.733438 | |||||||
10 | 8 | 2.758403 | 362.528563 | 2604.491472 | 9.893537 | |||||||
10 | 9 | 2.801866 | 356.904984 | 2585.087776 | 9.777427 | |||||||
2 | 2 | True | 1200 | 1200 | 10 | 0 | 2.901275 | 344.676018 | 2553.175926 | 8.119166 | ||
10 | 1 | 2.911759 | 343.435049 | 2586.572170 | 7.959247 | |||||||
10 | 2 | 2.884723 | 346.653700 | 2593.060255 | 8.024752 | |||||||
10 | 3 | 2.882487 | 346.922636 | 2594.633341 | 8.210301 | |||||||
10 | 4 | 2.905655 | 344.156504 | 2577.397823 | 8.071303 | |||||||
10 | 5 | 2.911228 | 343.497634 | 2599.563122 | 8.045614 | |||||||
10 | 6 | 2.887740 | 346.291542 | 2599.616051 | 8.206189 | |||||||
10 | 7 | 2.883306 | 346.824050 | 2616.064787 | 8.101344 | |||||||
10 | 8 | 2.882180 | 346.959591 | 2600.432396 | 8.085310 | |||||||
10 | 9 | 2.902249 | 344.560385 | 2605.264902 | 8.053899 | |||||||
4 | 2 | True | 1200 | 1200 | 10 | 0 | 2.939045 | 340.246618 | 2593.539000 | 7.703245 | ||
10 | 1 | 2.939430 | 340.201974 | 2572.237730 | 7.715553 | |||||||
10 | 2 | 2.935078 | 340.706408 | 2599.338770 | 7.794261 | |||||||
10 | 3 | 2.928367 | 341.487229 | 2598.786592 | 7.855088 | |||||||
10 | 4 | 2.941871 | 339.919746 | 2559.435368 | 7.808298 | |||||||
10 | 5 | 2.929240 | 341.385484 | 2584.117413 | 8.010060 | |||||||
10 | 6 | 2.920138 | 342.449546 | 2590.898752 | 7.594705 | |||||||
10 | 7 | 2.933626 | 340.875089 | 2647.840023 | 7.929742 | |||||||
10 | 8 | 2.939078 | 340.242803 | 2572.406054 | 7.688046 | |||||||
10 | 9 | 2.945699 | 339.477956 | 2580.096245 | 7.626444 | |||||||
8 | 2 | True | 1200 | 1200 | 10 | 0 | 2.921746 | 342.261106 | 2567.271948 | 6.669730 | ||
10 | 1 | 2.922858 | 342.130870 | 2594.122410 | 6.800830 | |||||||
10 | 2 | 2.920415 | 342.417121 | 2614.639044 | 6.576866 | |||||||
10 | 3 | 2.916166 | 342.916012 | 2592.293024 | 6.676361 | |||||||
10 | 4 | 2.910517 | 343.581617 | 2605.363369 | 6.958082 | |||||||
10 | 5 | 2.913586 | 343.219697 | 2568.465710 | 6.664857 | |||||||
10 | 6 | 2.917625 | 342.744559 | 2600.780010 | 6.701812 | |||||||
10 | 7 | 2.910468 | 343.587399 | 2606.662035 | 6.885782 | |||||||
10 | 8 | 2.913056 | 343.282133 | 2630.887985 | 6.758094 | |||||||
10 | 9 | 2.912372 | 343.362689 | 2594.960928 | 6.767809 | |||||||
tensorrt | 1 | 2 | True | 1200 | 1200 | 10 | 0 | 2.767666 | 361.315250 | 110542.984009 | 10.462880 | |
10 | 1 | 2.871997 | 348.189831 | 109657.408476 | 9.759068 | |||||||
10 | 2 | 2.852808 | 350.531816 | 110034.388065 | 9.696245 | |||||||
10 | 3 | 2.865664 | 348.959208 | 112439.590454 | 9.766340 | |||||||
10 | 4 | 2.841985 | 351.866722 | 111788.014889 | 9.869456 | |||||||
10 | 5 | 2.849151 | 350.981712 | 110608.415127 | 9.820223 | |||||||
10 | 6 | 2.840501 | 352.050543 | 107608.706713 | 9.712338 | |||||||
10 | 7 | 2.771097 | 360.867977 | 107305.213928 | 9.750366 | |||||||
10 | 8 | 2.866138 | 348.901510 | 106971.927166 | 9.839058 | |||||||
10 | 9 | 2.777872 | 359.987736 | 107022.459745 | 9.825230 | |||||||
2 | 2 | True | 1200 | 1200 | 10 | 0 | 2.948138 | 339.197159 | 107917.767048 | 8.176148 | ||
10 | 1 | 2.975112 | 336.121798 | 108731.031179 | 8.060157 | |||||||
10 | 2 | 2.972867 | 336.375594 | 108791.134596 | 7.930100 | |||||||
10 | 3 | 2.973682 | 336.283445 | 107481.444597 | 8.275807 | |||||||
10 | 4 | 2.860864 | 349.544764 | 109171.261549 | 8.073807 | |||||||
10 | 5 | 2.978943 | 335.689545 | 108843.255043 | 8.079827 | |||||||
10 | 6 | 2.943017 | 339.787364 | 108837.707996 | 7.902384 | |||||||
10 | 7 | 2.971424 | 336.539030 | 108641.510248 | 8.103907 | |||||||
10 | 8 | 2.960844 | 337.741494 | 108594.880342 | 8.282661 | |||||||
10 | 9 | 2.971701 | 336.507559 | 108941.448450 | 7.781625 | |||||||
4 | 2 | True | 1200 | 1200 | 10 | 0 | 3.017677 | 331.380725 | 73027.454138 | 7.832050 | ||
10 | 1 | 3.012794 | 331.917822 | 72546.567678 | 7.671565 | |||||||
10 | 2 | 3.015492 | 331.620872 | 72918.371916 | 7.654369 | |||||||
10 | 3 | 3.023033 | 330.793619 | 73165.400982 | 7.994235 | |||||||
10 | 4 | 3.023469 | 330.745935 | 73355.324745 | 7.640839 | |||||||
10 | 5 | 3.007373 | 332.516074 | 72925.657511 | 7.917792 | |||||||
10 | 6 | 3.020975 | 331.018925 | 72917.241812 | 7.816106 | |||||||
10 | 7 | 3.027055 | 330.354095 | 72621.436119 | 8.030981 | |||||||
10 | 8 | 3.018988 | 331.236780 | 72900.611401 | 7.661909 | |||||||
10 | 9 | 3.024568 | 330.625713 | 73549.364567 | 7.837266 | |||||||
8 | 2 | True | 1200 | 1200 | 10 | 0 | 2.998040 | 333.551198 | 71839.100599 | 6.672293 | ||
10 | 1 | 2.996960 | 333.671480 | 71953.596115 | 6.899774 | |||||||
10 | 2 | 3.003266 | 332.970887 | 72201.970339 | 6.658748 | |||||||
10 | 3 | 3.007223 | 332.532734 | 71876.399755 | 6.796494 | |||||||
10 | 4 | 3.001819 | 333.131313 | 72039.752007 | 6.663635 | |||||||
10 | 5 | 3.000991 | 333.223283 | 71869.973898 | 6.706268 | |||||||
10 | 6 | 2.998712 | 333.476454 | 71487.551451 | 6.839141 | |||||||
10 | 7 | 2.995689 | 333.813041 | 72090.383053 | 6.699994 | |||||||
10 | 8 | 2.997357 | 333.627254 | 71656.096697 | 6.747678 | |||||||
10 | 9 | 3.008561 | 332.384825 | 71390.659571 | 6.660312 | |||||||
tensorrt-dynamic | 1 | 2 | True | 1200 | 1200 | 10 | 0 | 3.057757 | 327.037096 | 22028.067350 | 9.554386 | |
10 | 1 | 3.068450 | 325.897455 | 22086.875200 | 9.461403 | |||||||
10 | 2 | 3.051777 | 327.677965 | 22220.805407 | 9.710312 | |||||||
10 | 3 | 3.059780 | 326.820850 | 22105.169535 | 9.832859 | |||||||
10 | 4 | 3.068549 | 325.886965 | 21711.289167 | 9.576082 | |||||||
10 | 5 | 3.036279 | 329.350471 | 21837.047577 | 9.606481 | |||||||
10 | 6 | 3.043676 | 328.550100 | 22272.382021 | 9.786844 | |||||||
10 | 7 | 3.084932 | 324.156284 | 22317.816019 | 9.663343 | |||||||
10 | 8 | 3.051861 | 327.668905 | 21800.987244 | 9.696484 | |||||||
10 | 9 | 3.078246 | 324.860334 | 21827.045918 | 9.767771 | |||||||
rcnn-resnet101-lowproposals | cpu | 1 | 2 | True | 600 | 1024 | 10 | 0 | 2.304830 | 433.871508 | 1827.384472 | 9.684801 |
10 | 1 | 2.335542 | 428.166151 | 1877.870560 | 9.973526 | |||||||
10 | 2 | 2.323291 | 430.423975 | 1907.244205 | 9.956360 | |||||||
10 | 3 | 2.341737 | 427.033424 | 1797.054529 | 9.700894 | |||||||
10 | 4 | 2.303445 | 434.132338 | 1904.339314 | 9.792686 | |||||||
10 | 5 | 2.316462 | 431.692839 | 1895.573139 | 9.884715 | |||||||
10 | 6 | 2.332635 | 428.699732 | 1874.328613 | 9.527802 | |||||||
10 | 7 | 2.316138 | 431.753159 | 1868.458986 | 10.022640 | |||||||
10 | 8 | 2.324732 | 430.157185 | 1855.124235 | 9.516835 | |||||||
10 | 9 | 2.319349 | 431.155443 | 1874.348402 | 9.882808 | |||||||
2 | 2 | True | 600 | 1024 | 10 | 0 | 2.392571 | 417.960405 | 1934.826851 | 8.248568 | ||
10 | 1 | 2.369553 | 422.020555 | 1864.797354 | 8.019984 | |||||||
10 | 2 | 2.366152 | 422.627091 | 1837.976933 | 7.781029 | |||||||
10 | 3 | 2.352325 | 425.111413 | 1921.272755 | 7.981777 | |||||||
10 | 4 | 2.344138 | 426.596045 | 1819.552898 | 8.148909 | |||||||
10 | 5 | 2.397723 | 417.062402 | 1812.511444 | 8.311629 | |||||||
10 | 6 | 2.392005 | 418.059349 | 1924.170017 | 8.090615 | |||||||
10 | 7 | 2.382561 | 419.716477 | 1938.081741 | 8.445263 | |||||||
10 | 8 | 2.381802 | 419.850230 | 1980.180025 | 8.017421 | |||||||
10 | 9 | 2.372068 | 421.573162 | 1875.776291 | 7.830441 | |||||||
4 | 2 | True | 600 | 1024 | 10 | 0 | 2.336892 | 427.918851 | 1868.940830 | 7.598341 | ||
10 | 1 | 2.344501 | 426.529944 | 1935.627699 | 7.593155 | |||||||
10 | 2 | 2.330032 | 429.178715 | 1898.720503 | 7.677764 | |||||||
10 | 3 | 2.305983 | 433.654487 | 1910.155773 | 7.690132 | |||||||
10 | 4 | 2.348180 | 425.861716 | 1922.926188 | 7.581472 | |||||||
10 | 5 | 2.359492 | 423.820019 | 1815.843582 | 7.585049 | |||||||
10 | 6 | 2.324034 | 430.286229 | 1827.770472 | 7.804841 | |||||||
10 | 7 | 2.340035 | 427.343965 | 1935.333729 | 7.580370 | |||||||
10 | 8 | 2.323268 | 430.428207 | 1933.232069 | 7.671297 | |||||||
10 | 9 | 2.336914 | 427.914739 | 1979.201555 | 7.660180 | |||||||
8 | 2 | True | 600 | 1024 | 10 | 0 | 2.339513 | 427.439332 | 1906.532288 | 6.749809 | ||
10 | 1 | 2.308595 | 433.163851 | 1906.987190 | 6.635755 | |||||||
10 | 2 | 2.324493 | 430.201411 | 1838.825464 | 6.627470 | |||||||
10 | 3 | 2.322419 | 430.585563 | 1893.810034 | 6.669953 | |||||||
10 | 4 | 2.316868 | 431.617111 | 1839.324236 | 6.772801 | |||||||
10 | 5 | 2.338430 | 427.637279 | 1803.636789 | 6.496117 | |||||||
10 | 6 | 2.321023 | 430.844545 | 1816.417933 | 6.503448 | |||||||
10 | 7 | 2.335022 | 428.261399 | 1866.621733 | 6.521270 | |||||||
10 | 8 | 2.337814 | 427.750051 | 1857.588291 | 6.576374 | |||||||
10 | 9 | 2.333129 | 428.608984 | 1889.589310 | 6.512001 | |||||||
16 | 2 | True | 600 | 1024 | 10 | 0 | 2.342415 | 426.909819 | 1828.043222 | 6.163120 | ||
10 | 1 | 2.329757 | 429.229394 | 1817.310810 | 6.488718 | |||||||
10 | 2 | 2.347167 | 426.045462 | 1913.735867 | 6.387718 | |||||||
10 | 3 | 2.340523 | 427.254871 | 1836.093187 | 6.356589 | |||||||
10 | 4 | 2.333166 | 428.602129 | 1832.617521 | 6.242298 | |||||||
10 | 5 | 2.330831 | 429.031491 | 1834.811449 | 6.567240 | |||||||
10 | 6 | 2.330327 | 429.124296 | 1868.567705 | 6.202891 | |||||||
10 | 7 | 2.342290 | 426.932633 | 1880.446196 | 6.326608 | |||||||
10 | 8 | 2.335471 | 428.179160 | 1822.031498 | 6.301835 | |||||||
10 | 9 | 2.338979 | 427.536935 | 1963.088036 | 6.282225 | |||||||
32 | 2 | True | 600 | 1024 | 10 | 0 | 2.346851 | 426.102959 | 1896.929979 | 6.133009 | ||
10 | 1 | 2.346771 | 426.117368 | 1909.787178 | 6.159011 | |||||||
10 | 2 | 2.345309 | 426.383093 | 1862.657070 | 6.230399 | |||||||
10 | 3 | 2.349178 | 425.680831 | 1807.484150 | 6.064776 | |||||||
10 | 4 | 2.347325 | 426.016867 | 1946.138382 | 6.048486 | |||||||
10 | 5 | 2.346566 | 426.154599 | 1935.488462 | 6.421760 | |||||||
10 | 6 | 2.345271 | 426.389873 | 1891.182423 | 6.187461 | |||||||
10 | 7 | 2.343750 | 426.666580 | 1946.294308 | 6.042723 | |||||||
10 | 8 | 2.343750 | 426.666588 | 1940.818548 | 6.043978 | |||||||
10 | 9 | 2.343544 | 426.704139 | 1812.900066 | 6.035201 | |||||||
cpu-prebuilt | 1 | 2 | True | 600 | 1024 | 10 | 0 | 2.325807 | 429.958344 | 3526.874781 | 9.588480 | |
10 | 1 | 2.270778 | 440.377712 | 1796.475649 | 9.777665 | |||||||
10 | 2 | 2.315289 | 431.911469 | 1790.876150 | 9.529471 | |||||||
10 | 3 | 2.325723 | 429.973841 | 1776.808739 | 9.592175 | |||||||
10 | 4 | 2.334878 | 428.287983 | 1768.345118 | 9.633541 | |||||||
10 | 5 | 2.328097 | 429.535389 | 1796.634674 | 9.695768 | |||||||
10 | 6 | 2.295947 | 435.550213 | 1761.363983 | 9.647131 | |||||||
10 | 7 | 2.317605 | 431.479931 | 1774.100780 | 9.778976 | |||||||
10 | 8 | 2.306634 | 433.532238 | 1779.556274 | 9.850621 | |||||||
10 | 9 | 2.310858 | 432.739735 | 1789.674282 | 9.897470 | |||||||
2 | 2 | True | 600 | 1024 | 10 | 0 | 2.330590 | 429.075837 | 1780.204296 | 8.139193 | ||
10 | 1 | 2.329304 | 429.312706 | 1774.967194 | 8.168697 | |||||||
10 | 2 | 2.340682 | 427.225828 | 1788.007498 | 7.784605 | |||||||
10 | 3 | 2.328938 | 429.380298 | 1796.847105 | 7.883370 | |||||||
10 | 4 | 2.329753 | 429.229975 | 1793.567181 | 8.091271 | |||||||
10 | 5 | 2.340722 | 427.218676 | 1793.089628 | 7.717967 | |||||||
10 | 6 | 2.347164 | 426.046133 | 1801.154137 | 7.815659 | |||||||
10 | 7 | 2.315344 | 431.901217 | 1765.961885 | 7.840872 | |||||||
10 | 8 | 2.345038 | 426.432371 | 1770.402670 | 8.082330 | |||||||
10 | 9 | 2.328573 | 429.447651 | 1768.368959 | 7.858813 | |||||||
4 | 2 | True | 600 | 1024 | 10 | 0 | 2.318044 | 431.398153 | 1775.799513 | 7.703036 | ||
10 | 1 | 2.317155 | 431.563675 | 1758.645058 | 7.533014 | |||||||
10 | 2 | 2.318512 | 431.311131 | 1766.268730 | 7.707924 | |||||||
10 | 3 | 2.347870 | 425.918043 | 1754.207850 | 7.762402 | |||||||
10 | 4 | 2.331571 | 428.895354 | 1769.369602 | 7.625192 | |||||||
10 | 5 | 2.334888 | 428.286076 | 1824.254274 | 8.000851 | |||||||
10 | 6 | 2.318316 | 431.347668 | 1796.149492 | 7.516295 | |||||||
10 | 7 | 2.293173 | 436.076939 | 1791.581631 | 7.714301 | |||||||
10 | 8 | 2.300733 | 434.644163 | 1780.581951 | 7.791013 | |||||||
10 | 9 | 2.307829 | 433.307648 | 1800.542831 | 7.868201 | |||||||
8 | 2 | True | 600 | 1024 | 10 | 0 | 2.308230 | 433.232456 | 1830.583811 | 6.714031 | ||
10 | 1 | 2.322982 | 430.481076 | 1754.957438 | 6.623983 | |||||||
10 | 2 | 2.313316 | 432.279974 | 1763.799429 | 6.718278 | |||||||
10 | 3 | 2.311795 | 432.564318 | 1818.261623 | 6.643608 | |||||||
10 | 4 | 2.318583 | 431.297898 | 1796.255350 | 6.703928 | |||||||
10 | 5 | 2.302579 | 434.295654 | 1855.784655 | 6.638959 | |||||||
10 | 6 | 2.323247 | 430.432141 | 1753.847599 | 6.945089 | |||||||
10 | 7 | 2.303336 | 434.152931 | 1804.566622 | 6.446645 | |||||||
10 | 8 | 2.321016 | 430.845886 | 1780.231476 | 6.791070 | |||||||
10 | 9 | 2.304421 | 433.948398 | 1857.248783 | 6.564587 | |||||||
16 | 2 | True | 600 | 1024 | 10 | 0 | 2.319178 | 431.187347 | 1768.025875 | 6.277628 | ||
10 | 1 | 2.329284 | 429.316476 | 1784.183502 | 6.618336 | |||||||
10 | 2 | 2.322164 | 430.632800 | 1818.145752 | 6.284736 | |||||||
10 | 3 | 2.320084 | 431.018889 | 1772.001266 | 6.400876 | |||||||
10 | 4 | 2.308925 | 433.101922 | 1768.416643 | 6.351672 | |||||||
10 | 5 | 2.321651 | 430.727914 | 1793.220520 | 6.333083 | |||||||
10 | 6 | 2.327525 | 429.640979 | 1785.733938 | 6.494991 | |||||||
10 | 7 | 2.325310 | 430.050239 | 1808.824539 | 6.321713 | |||||||
10 | 8 | 2.326018 | 429.919228 | 1767.354250 | 6.455906 | |||||||
10 | 9 | 2.316092 | 431.761786 | 1779.067755 | 6.235562 | |||||||
32 | 2 | True | 600 | 1024 | 10 | 0 | 2.324147 | 430.265404 | 1888.056993 | 6.092943 | ||
10 | 1 | 2.330996 | 429.001175 | 1773.266315 | 5.997755 | |||||||
10 | 2 | 2.324931 | 430.120274 | 1768.773794 | 6.219804 | |||||||
10 | 3 | 2.326243 | 429.877706 | 1755.516529 | 6.305285 | |||||||
10 | 4 | 2.330322 | 429.125234 | 1770.206451 | 6.067540 | |||||||
10 | 5 | 2.330357 | 429.118887 | 1774.690866 | 6.300285 | |||||||
10 | 6 | 2.328126 | 429.530039 | 1794.872761 | 6.287884 | |||||||
10 | 7 | 2.323454 | 430.393636 | 1837.211609 | 6.190877 | |||||||
10 | 8 | 2.327724 | 429.604284 | 1790.501833 | 6.103795 | |||||||
10 | 9 | 2.329613 | 429.255851 | 1901.494026 | 6.256886 | |||||||
cuda | 1 | 2 | True | 600 | 1024 | 10 | 0 | 12.406357 | 80.603838 | 1780.699968 | 9.582043 | |
10 | 1 | 12.251652 | 81.621647 | 1794.161797 | 9.646416 | |||||||
10 | 2 | 12.455653 | 80.284834 | 1797.565699 | 9.800553 | |||||||
10 | 3 | 12.595318 | 79.394579 | 1823.054552 | 9.614229 | |||||||
10 | 4 | 12.471096 | 80.185413 | 1764.760017 | 9.642482 | |||||||
10 | 5 | 12.331328 | 81.094265 | 1788.885593 | 9.572625 | |||||||
10 | 6 | 12.367471 | 80.857277 | 1807.747602 | 9.576082 | |||||||
10 | 7 | 12.322235 | 81.154108 | 1790.563583 | 9.756565 | |||||||
10 | 8 | 12.468353 | 80.203056 | 1789.198875 | 9.592295 | |||||||
10 | 9 | 12.288948 | 81.373930 | 1838.732004 | 9.908557 | |||||||
2 | 2 | True | 600 | 1024 | 10 | 0 | 13.884102 | 72.024822 | 1794.478178 | 7.758796 | ||
10 | 1 | 13.846106 | 72.222471 | 1793.740749 | 7.920980 | |||||||
10 | 2 | 13.656312 | 73.226213 | 1811.664581 | 7.816315 | |||||||
10 | 3 | 14.140685 | 70.717931 | 1795.699835 | 7.919908 | |||||||
10 | 4 | 13.914802 | 71.865916 | 1769.134283 | 7.877946 | |||||||
10 | 5 | 13.854018 | 72.181225 | 1774.894953 | 8.070529 | |||||||
10 | 6 | 13.765921 | 72.643161 | 1787.384510 | 7.844150 | |||||||
10 | 7 | 13.737043 | 72.795868 | 1797.870159 | 8.096159 | |||||||
10 | 8 | 13.927324 | 71.801305 | 1759.881735 | 7.981837 | |||||||
10 | 9 | 13.958052 | 71.643233 | 1791.018724 | 8.197069 | |||||||
4 | 2 | True | 600 | 1024 | 10 | 0 | 15.190190 | 65.831959 | 1776.934385 | 7.706136 | ||
10 | 1 | 15.243838 | 65.600276 | 1777.024984 | 7.771075 | |||||||
10 | 2 | 15.098110 | 66.233456 | 1792.327404 | 7.554978 | |||||||
10 | 3 | 15.040275 | 66.488147 | 1809.364080 | 7.516950 | |||||||
10 | 4 | 15.200375 | 65.787852 | 1815.351009 | 7.396162 | |||||||
10 | 5 | 15.293446 | 65.387487 | 1769.275188 | 7.549137 | |||||||
10 | 6 | 15.397154 | 64.947069 | 1799.986839 | 7.576406 | |||||||
10 | 7 | 15.295468 | 65.378845 | 1776.325464 | 7.525742 | |||||||
10 | 8 | 15.077933 | 66.322088 | 1804.390907 | 7.936239 | |||||||
10 | 9 | 15.237096 | 65.629303 | 1808.810949 | 7.494003 | |||||||
8 | 2 | True | 600 | 1024 | 10 | 0 | 15.461981 | 64.674765 | 1766.000986 | 6.446227 | ||
10 | 1 | 15.051272 | 66.439569 | 1797.045469 | 6.708249 | |||||||
10 | 2 | 15.583301 | 64.171255 | 1795.336723 | 6.666273 | |||||||
10 | 3 | 15.675751 | 63.792795 | 1806.338787 | 6.792292 | |||||||
10 | 4 | 15.192460 | 65.822124 | 1789.094448 | 6.449252 | |||||||
10 | 5 | 15.368740 | 65.067142 | 1798.160791 | 6.783634 | |||||||
10 | 6 | 15.472476 | 64.630896 | 1788.929939 | 6.678030 | |||||||
10 | 7 | 15.579365 | 64.187467 | 1796.284676 | 6.702468 | |||||||
10 | 8 | 15.561165 | 64.262539 | 1804.042816 | 6.751165 | |||||||
10 | 9 | 15.482578 | 64.588726 | 1787.196159 | 6.467342 | |||||||
16 | 2 | True | 600 | 1024 | 10 | 0 | 15.844891 | 63.111827 | 1794.874191 | 6.226681 | ||
10 | 1 | 15.785117 | 63.350812 | 1797.908306 | 6.222032 | |||||||
10 | 2 | 15.863543 | 63.037619 | 1770.837784 | 6.245166 | |||||||
10 | 3 | 15.797339 | 63.301802 | 1781.039000 | 6.200060 | |||||||
10 | 4 | 15.756247 | 63.466892 | 1792.331934 | 6.264597 | |||||||
10 | 5 | 15.942631 | 62.724903 | 1819.593191 | 6.288953 | |||||||
10 | 6 | 15.947454 | 62.705934 | 1806.744814 | 6.427646 | |||||||
10 | 7 | 15.969829 | 62.618077 | 1803.507328 | 6.459050 | |||||||
10 | 8 | 15.943665 | 62.720835 | 1801.426888 | 6.716251 | |||||||
10 | 9 | 15.819410 | 63.213482 | 1814.743996 | 6.266527 | |||||||
32 | 2 | True | 600 | 1024 | 10 | 0 | 15.984870 | 62.559158 | 3650.776625 | 6.016515 | ||
10 | 1 | 15.851304 | 63.086294 | 1801.421165 | 6.203383 | |||||||
10 | 2 | 15.823961 | 63.195303 | 1777.224064 | 6.303597 | |||||||
10 | 3 | 15.931699 | 62.767945 | 1807.895422 | 6.169319 | |||||||
10 | 4 | 15.918470 | 62.820107 | 1787.414074 | 6.007489 | |||||||
10 | 5 | 15.942908 | 62.723815 | 1788.667917 | 6.297566 | |||||||
10 | 6 | 15.861777 | 63.044637 | 1799.606562 | 5.995713 | |||||||
10 | 7 | 15.835060 | 63.151009 | 1788.318634 | 6.021909 | |||||||
10 | 8 | 15.901913 | 62.885515 | 1781.450510 | 6.085332 | |||||||
10 | 9 | 15.919637 | 62.815502 | 1806.703806 | 6.254602 | |||||||
tensorrt | 1 | 2 | True | 600 | 1024 | 10 | 0 | 12.214332 | 81.871033 | 21520.837307 | 9.573817 | |
10 | 1 | 12.332597 | 81.085920 | 21626.183748 | 9.447336 | |||||||
10 | 2 | 12.442351 | 80.370665 | 21467.853069 | 9.792447 | |||||||
10 | 3 | 12.087889 | 82.727432 | 21474.493980 | 9.541512 | |||||||
10 | 4 | 12.321185 | 81.161022 | 21446.175575 | 9.764910 | |||||||
10 | 5 | 12.515192 | 79.902887 | 21555.088282 | 9.565473 | |||||||
10 | 6 | 12.355776 | 80.933809 | 21599.481106 | 9.463191 | |||||||
10 | 7 | 12.368492 | 80.850601 | 21490.350962 | 9.759068 | |||||||
10 | 8 | 12.350864 | 80.965996 | 21481.666803 | 9.582162 | |||||||
10 | 9 | 12.578623 | 79.499960 | 21465.908527 | 9.615660 | |||||||
2 | 2 | True | 600 | 1024 | 10 | 0 | 13.813024 | 72.395444 | 22227.952480 | 7.780313 | ||
10 | 1 | 13.716603 | 72.904348 | 22319.144011 | 7.857382 | |||||||
10 | 2 | 13.694680 | 73.021054 | 22134.814024 | 7.850707 | |||||||
10 | 3 | 13.688133 | 73.055983 | 22103.310585 | 7.707417 | |||||||
10 | 4 | 13.961142 | 71.627378 | 22314.942598 | 7.925808 | |||||||
10 | 5 | 13.772498 | 72.608471 | 21941.455126 | 7.641792 | |||||||
10 | 6 | 13.697386 | 73.006630 | 22218.677521 | 7.755816 | |||||||
10 | 7 | 13.799504 | 72.466373 | 22129.404545 | 7.634580 | |||||||
10 | 8 | 13.901105 | 71.936727 | 22288.933516 | 7.660806 | |||||||
10 | 9 | 13.729849 | 72.834015 | 22086.379051 | 7.763565 | |||||||
4 | 2 | True | 600 | 1024 | 10 | 0 | 14.887289 | 67.171395 | 17102.623701 | 7.688612 | ||
10 | 1 | 14.901266 | 67.108393 | 17197.448254 | 7.571965 | |||||||
10 | 2 | 14.920641 | 67.021251 | 17331.134081 | 7.504016 | |||||||
10 | 3 | 15.179828 | 65.876901 | 17033.634424 | 7.494926 | |||||||
10 | 4 | 14.912948 | 67.055821 | 16926.265717 | 7.471025 | |||||||
10 | 5 | 15.140375 | 66.048563 | 16950.997591 | 7.679582 | |||||||
10 | 6 | 14.804567 | 67.546725 | 17085.191727 | 7.456332 | |||||||
10 | 7 | 14.981155 | 66.750526 | 17058.808327 | 7.495344 | |||||||
10 | 8 | 15.026346 | 66.549778 | 17133.375883 | 7.729977 | |||||||
10 | 9 | 15.227070 | 65.672517 | 17176.436424 | 7.496089 | |||||||
8 | 2 | True | 600 | 1024 | 10 | 0 | 15.221861 | 65.694988 | 17159.111500 | 6.547987 | ||
10 | 1 | 15.405163 | 64.913303 | 16983.058214 | 6.352276 | |||||||
10 | 2 | 15.410370 | 64.891368 | 17195.908546 | 6.562412 | |||||||
10 | 3 | 15.475930 | 64.616472 | 17181.518078 | 6.568372 | |||||||
10 | 4 | 15.287969 | 65.410912 | 17114.690065 | 6.539419 | |||||||
10 | 5 | 15.276213 | 65.461248 | 17141.021967 | 6.698266 | |||||||
10 | 6 | 15.247918 | 65.582722 | 17249.283552 | 6.569609 | |||||||
10 | 7 | 15.357240 | 65.115869 | 17039.963484 | 6.565511 | |||||||
10 | 8 | 15.370338 | 65.060377 | 17096.708536 | 6.546274 | |||||||
10 | 9 | 15.376417 | 65.034658 | 17224.649191 | 6.451920 | |||||||
16 | 2 | True | 600 | 1024 | 10 | 0 | 15.976646 | 62.591359 | 16602.551460 | 6.260730 | ||
10 | 1 | 15.857681 | 63.060924 | 16584.681034 | 6.315164 | |||||||
10 | 2 | 15.944358 | 62.718108 | 16473.892927 | 6.287269 | |||||||
10 | 3 | 15.798477 | 63.297242 | 16396.528482 | 6.403334 | |||||||
10 | 4 | 15.984916 | 62.558979 | 16479.218006 | 6.443962 | |||||||
10 | 5 | 15.886793 | 62.945366 | 16550.421476 | 6.713882 | |||||||
10 | 6 | 15.834240 | 63.154280 | 16433.331013 | 6.300107 | |||||||
10 | 7 | 15.821920 | 63.203454 | 16525.912762 | 6.309062 | |||||||
10 | 8 | 15.796469 | 63.305289 | 16298.932791 | 6.288730 | |||||||
10 | 9 | 15.686025 | 63.751012 | 16429.342270 | 6.249793 | |||||||
32 | 2 | True | 600 | 1024 | 10 | 0 | 15.851167 | 63.086838 | 17299.829245 | 6.002590 | ||
10 | 1 | 15.771455 | 63.405693 | 17187.531471 | 6.064180 | |||||||
10 | 2 | 15.847697 | 63.100651 | 16918.631315 | 6.084248 | |||||||
10 | 3 | 15.869457 | 63.014127 | 16942.778826 | 6.116644 | |||||||
10 | 4 | 15.902235 | 62.884241 | 17201.121569 | 6.206512 | |||||||
10 | 5 | 15.848666 | 63.096792 | 17203.660488 | 6.110922 | |||||||
10 | 6 | 15.744702 | 63.513428 | 16960.286617 | 6.126728 | |||||||
10 | 7 | 15.995883 | 62.516086 | 16781.747580 | 6.115861 | |||||||
10 | 8 | 16.003934 | 62.484637 | 17277.103662 | 6.359812 | |||||||
10 | 9 | 15.886509 | 62.946491 | 17069.191456 | 6.053250 | |||||||
tensorrt-dynamic | 1 | 2 | True | 600 | 1024 | 10 | 0 | 16.734109 | 59.758186 | 12546.623468 | 9.447694 | |
10 | 1 | 15.540503 | 64.347982 | 12751.722574 | 9.544373 | |||||||
10 | 2 | 17.016744 | 58.765650 | 12663.028955 | 9.646416 | |||||||
10 | 3 | 15.905952 | 62.869549 | 12665.186644 | 9.731531 | |||||||
10 | 4 | 16.617291 | 60.178280 | 12725.333691 | 9.541631 | |||||||
10 | 5 | 15.995180 | 62.518835 | 12693.892956 | 9.388208 | |||||||
10 | 6 | 16.785542 | 59.575081 | 12597.485781 | 9.372473 | |||||||
10 | 7 | 16.232141 | 61.606169 | 12776.030064 | 9.385705 | |||||||
10 | 8 | 16.406110 | 60.952902 | 12575.339556 | 9.355068 | |||||||
10 | 9 | 16.690824 | 59.913158 | 12786.731243 | 9.495974 | |||||||
2 | 2 | True | 600 | 1024 | 10 | 0 | 18.098985 | 55.251718 | 12683.964491 | 7.887363 | ||
10 | 1 | 17.265093 | 57.920337 | 12633.701324 | 7.705867 | |||||||
10 | 2 | 18.116848 | 55.197239 | 12655.244827 | 7.636547 | |||||||
10 | 3 | 17.753818 | 56.325912 | 12547.592402 | 7.811964 | |||||||
10 | 4 | 17.941206 | 55.737615 | 12566.540241 | 7.757425 | |||||||
10 | 5 | 18.475157 | 54.126740 | 12551.458359 | 7.632315 | |||||||
10 | 6 | 18.155195 | 55.080652 | 12679.618835 | 7.662952 | |||||||
10 | 7 | 17.944161 | 55.728436 | 12613.080740 | 7.677913 | |||||||
10 | 8 | 17.781290 | 56.238890 | 12662.493467 | 7.966459 | |||||||
10 | 9 | 17.730702 | 56.399345 | 12775.243044 | 7.885098 | |||||||
4 | 2 | True | 600 | 1024 | 10 | 0 | 18.789180 | 53.222120 | 12475.938320 | 7.554084 | ||
10 | 1 | 19.372804 | 51.618755 | 12353.553295 | 7.454753 | |||||||
10 | 2 | 18.962770 | 52.734911 | 12520.078421 | 7.705092 | |||||||
10 | 3 | 19.544867 | 51.164329 | 12576.491117 | 7.529080 | |||||||
10 | 4 | 19.132111 | 52.268147 | 12633.758307 | 7.454246 | |||||||
10 | 5 | 19.420457 | 51.492095 | 12593.590736 | 7.604241 | |||||||
10 | 6 | 19.240831 | 51.972806 | 12665.605545 | 7.520586 | |||||||
10 | 7 | 19.024893 | 52.562714 | 12597.863674 | 7.429093 | |||||||
10 | 8 | 19.546916 | 51.158965 | 12497.672319 | 7.483214 | |||||||
10 | 9 | 19.574055 | 51.088035 | 12649.907827 | 7.510900 | |||||||
8 | 2 | True | 600 | 1024 | 10 | 0 | 19.121426 | 52.297354 | 12547.012329 | 6.488472 | ||
10 | 1 | 19.530715 | 51.201403 | 12815.947533 | 6.437615 | |||||||
10 | 2 | 19.642082 | 50.911099 | 12591.820240 | 6.410971 | |||||||
10 | 3 | 19.629661 | 50.943315 | 12722.246408 | 6.491035 | |||||||
10 | 4 | 19.466289 | 51.370859 | 12605.246305 | 6.557107 | |||||||
10 | 5 | 19.570128 | 51.098287 | 12560.843945 | 6.665528 | |||||||
10 | 6 | 19.819616 | 50.455064 | 12569.098711 | 6.636485 | |||||||
10 | 7 | 19.353596 | 51.669985 | 12711.484432 | 6.569028 | |||||||
10 | 8 | 19.770418 | 50.580621 | 12687.051296 | 6.467119 | |||||||
10 | 9 | 19.236000 | 51.985860 | 12635.541916 | 6.484702 | |||||||
16 | 2 | True | 600 | 1024 | 10 | 0 | 19.764188 | 50.596565 | 12726.392508 | 6.491296 | ||
10 | 1 | 19.618740 | 50.971672 | 12463.183403 | 6.296717 | |||||||
10 | 2 | 19.746944 | 50.640747 | 12824.097633 | 6.244048 | |||||||
10 | 3 | 19.659316 | 50.866470 | 12399.031162 | 6.438285 | |||||||
10 | 4 | 19.586755 | 51.054910 | 12678.436041 | 6.400786 | |||||||
10 | 5 | 19.455510 | 51.399320 | 12383.874655 | 6.279379 | |||||||
10 | 6 | 19.421693 | 51.488817 | 12594.056368 | 6.321602 | |||||||
10 | 7 | 19.557552 | 51.131144 | 12426.792145 | 6.236024 | |||||||
10 | 8 | 19.560932 | 51.122308 | 12633.033276 | 6.164126 | |||||||
10 | 9 | 19.611006 | 50.991774 | 12655.103922 | 6.318189 | |||||||
rcnn-resnet50-lowproposals | cpu | 1 | 2 | True | 600 | 1024 | 10 | 0 | 3.776142 | 264.820576 | 1686.880589 | 9.643912 |
10 | 1 | 3.688364 | 271.122932 | 1704.359293 | 9.935141 | |||||||
10 | 2 | 3.657459 | 273.413897 | 1718.741655 | 9.537816 | |||||||
10 | 3 | 3.681368 | 271.638155 | 1619.982958 | 9.682417 | |||||||
10 | 4 | 3.737363 | 267.568350 | 1606.738567 | 9.875298 | |||||||
10 | 5 | 3.723914 | 268.534660 | 1680.978775 | 9.723186 | |||||||
10 | 6 | 3.679088 | 271.806479 | 1595.991850 | 10.011077 | |||||||
10 | 7 | 3.744985 | 267.023802 | 1645.612001 | 9.914756 | |||||||
10 | 8 | 3.670180 | 272.466183 | 1597.892761 | 9.897351 | |||||||
10 | 9 | 3.638788 | 274.816751 | 1685.933113 | 9.681463 | |||||||
2 | 2 | True | 600 | 1024 | 10 | 0 | 3.829103 | 261.157751 | 1675.863743 | 8.010089 | ||
10 | 1 | 3.719642 | 268.843055 | 1708.093643 | 8.337080 | |||||||
10 | 2 | 3.827712 | 261.252642 | 1583.373070 | 8.207142 | |||||||
10 | 3 | 3.872635 | 258.222103 | 1676.360369 | 8.103073 | |||||||
10 | 4 | 3.844418 | 260.117412 | 1701.800108 | 8.178890 | |||||||
10 | 5 | 3.838114 | 260.544658 | 1634.593487 | 7.981360 | |||||||
10 | 6 | 3.844719 | 260.097027 | 1629.212379 | 7.709503 | |||||||
10 | 7 | 3.889469 | 257.104516 | 1712.654352 | 8.213580 | |||||||
10 | 8 | 3.845763 | 260.026455 | 1666.113377 | 8.351564 | |||||||
10 | 9 | 3.876064 | 257.993698 | 1699.373484 | 7.974684 | |||||||
4 | 2 | True | 600 | 1024 | 10 | 0 | 3.947951 | 253.295958 | 1684.618473 | 7.599264 | ||
10 | 1 | 3.891619 | 256.962478 | 1657.998562 | 7.850498 | |||||||
10 | 2 | 3.894700 | 256.759167 | 1633.961201 | 7.827699 | |||||||
10 | 3 | 3.903964 | 256.149888 | 1669.556618 | 7.757664 | |||||||
10 | 4 | 3.934027 | 254.192472 | 1699.060202 | 7.414043 | |||||||
10 | 5 | 3.935468 | 254.099369 | 1680.139542 | 7.916749 | |||||||
10 | 6 | 3.906316 | 255.995691 | 1682.508945 | 7.896006 | |||||||
10 | 7 | 3.908063 | 255.881250 | 1696.475744 | 7.962078 | |||||||
10 | 8 | 3.870694 | 258.351624 | 1627.237558 | 7.742405 | |||||||
10 | 9 | 3.939330 | 253.850281 | 1670.836210 | 7.573932 | |||||||
8 | 2 | True | 600 | 1024 | 10 | 0 | 3.859469 | 259.102970 | 1613.138199 | 6.570980 | ||
10 | 1 | 3.840609 | 260.375351 | 1678.300142 | 6.501794 | |||||||
10 | 2 | 3.866028 | 258.663416 | 1619.373083 | 6.715238 | |||||||
10 | 3 | 3.824838 | 261.448950 | 1683.642387 | 6.480053 | |||||||
10 | 4 | 3.865737 | 258.682907 | 1648.265123 | 6.416053 | |||||||
10 | 5 | 3.853725 | 259.489179 | 1659.857988 | 6.652877 | |||||||
10 | 6 | 3.878279 | 257.846326 | 1640.050888 | 6.461129 | |||||||
10 | 7 | 3.836441 | 260.658264 | 1623.372793 | 6.792918 | |||||||
10 | 8 | 3.868346 | 258.508444 | 1711.113930 | 6.581336 | |||||||
10 | 9 | 3.881968 | 257.601291 | 1625.286818 | 6.494537 | |||||||
16 | 2 | True | 600 | 1024 | 10 | 0 | 3.866765 | 258.614108 | 1654.815435 | 6.322645 | ||
10 | 1 | 3.869823 | 258.409739 | 1629.233122 | 6.453760 | |||||||
10 | 2 | 3.884349 | 257.443383 | 1612.328529 | 6.364495 | |||||||
10 | 3 | 3.876037 | 257.995442 | 1632.277966 | 6.321780 | |||||||
10 | 4 | 3.850778 | 259.687766 | 1690.767527 | 6.561197 | |||||||
10 | 5 | 3.880620 | 257.690772 | 1673.472166 | 6.332882 | |||||||
10 | 6 | 3.877476 | 257.899716 | 1623.745441 | 6.240845 | |||||||
10 | 7 | 3.866697 | 258.618683 | 1625.013351 | 6.257720 | |||||||
10 | 8 | 3.868957 | 258.467570 | 1662.688732 | 6.280772 | |||||||
10 | 9 | 3.876812 | 257.943884 | 1590.418100 | 6.240308 | |||||||
32 | 2 | True | 600 | 1024 | 10 | 0 | 3.892849 | 256.881282 | 1600.942612 | 6.155942 | ||
10 | 1 | 3.903304 | 256.193206 | 1638.194084 | 6.021615 | |||||||
10 | 2 | 3.878720 | 257.816985 | 1664.097309 | 6.247904 | |||||||
10 | 3 | 3.887547 | 257.231601 | 1596.452713 | 6.269380 | |||||||
10 | 4 | 3.901603 | 256.304920 | 1619.798660 | 5.978562 | |||||||
10 | 5 | 3.885975 | 257.335678 | 1698.755503 | 6.111003 | |||||||
10 | 6 | 3.880982 | 257.666714 | 1659.761429 | 6.098967 | |||||||
10 | 7 | 3.888605 | 257.161640 | 1715.822935 | 6.176483 | |||||||
10 | 8 | 3.894709 | 256.758608 | 1653.138161 | 6.132122 | |||||||
10 | 9 | 3.861509 | 258.966148 | 1622.913361 | 5.929604 | |||||||
cpu-prebuilt | 1 | 2 | True | 600 | 1024 | 10 | 0 | 3.571742 | 279.975414 | 2762.686491 | 17.721534 | |
10 | 1 | 3.650224 | 273.955822 | 1638.625622 | 9.535074 | |||||||
10 | 2 | 3.613571 | 276.734591 | 1577.911139 | 9.868741 | |||||||
10 | 3 | 3.677456 | 271.927118 | 1553.699970 | 9.736419 | |||||||
10 | 4 | 3.490724 | 286.473513 | 1564.384937 | 9.866118 | |||||||
10 | 5 | 3.660782 | 273.165703 | 1538.223743 | 9.918094 | |||||||
10 | 6 | 3.549237 | 281.750679 | 1550.678253 | 9.536862 | |||||||
10 | 7 | 3.651088 | 273.890972 | 1556.126833 | 9.942293 | |||||||
10 | 8 | 3.597361 | 277.981520 | 1622.909307 | 9.845018 | |||||||
10 | 9 | 3.706443 | 269.800425 | 1549.013138 | 9.619832 | |||||||
2 | 2 | True | 600 | 1024 | 10 | 0 | 3.783168 | 264.328718 | 1579.739332 | 8.128703 | ||
10 | 1 | 3.735273 | 267.718077 | 1639.370680 | 8.020580 | |||||||
10 | 2 | 3.812983 | 262.261868 | 1627.659321 | 8.489132 | |||||||
10 | 3 | 3.779005 | 264.619946 | 1547.396183 | 7.694066 | |||||||
10 | 4 | 3.778412 | 264.661431 | 1540.544748 | 8.074224 | |||||||
10 | 5 | 3.742069 | 267.231822 | 1542.426109 | 7.966459 | |||||||
10 | 6 | 3.686432 | 271.265030 | 1562.769413 | 8.267522 | |||||||
10 | 7 | 3.810065 | 262.462735 | 1558.845758 | 7.917762 | |||||||
10 | 8 | 3.810388 | 262.440443 | 1551.403522 | 8.073688 | |||||||
10 | 9 | 3.842094 | 260.274768 | 1539.196014 | 7.852554 | |||||||
4 | 2 | True | 600 | 1024 | 10 | 0 | 3.818147 | 261.907160 | 1545.026302 | 7.532388 | ||
10 | 1 | 3.838781 | 260.499358 | 1588.864565 | 7.528603 | |||||||
10 | 2 | 3.873019 | 258.196533 | 1605.333567 | 7.553667 | |||||||
10 | 3 | 3.875109 | 258.057237 | 1602.406979 | 7.640928 | |||||||
10 | 4 | 3.880915 | 257.671177 | 1651.915789 | 8.132309 | |||||||
10 | 5 | 3.847162 | 259.931862 | 1609.186649 | 7.605106 | |||||||
10 | 6 | 3.842808 | 260.226369 | 1652.390003 | 7.553011 | |||||||
10 | 7 | 3.842139 | 260.271668 | 1558.289051 | 7.787108 | |||||||
10 | 8 | 3.834420 | 260.795653 | 1633.130312 | 7.855207 | |||||||
10 | 9 | 3.835751 | 260.705113 | 1630.680799 | 7.746011 | |||||||
8 | 2 | True | 600 | 1024 | 10 | 0 | 3.845960 | 260.013074 | 1665.308952 | 6.696820 | ||
10 | 1 | 3.823265 | 261.556566 | 1555.235147 | 6.600454 | |||||||
10 | 2 | 3.834839 | 260.767132 | 1551.889658 | 6.581768 | |||||||
10 | 3 | 3.820514 | 261.744857 | 1559.449196 | 6.481290 | |||||||
10 | 4 | 3.827530 | 261.265099 | 1616.168261 | 6.699994 | |||||||
10 | 5 | 3.720410 | 268.787593 | 1541.977167 | 6.636932 | |||||||
10 | 6 | 3.846771 | 259.958267 | 1547.911406 | 6.595314 | |||||||
10 | 7 | 3.814516 | 262.156427 | 1532.830238 | 6.751522 | |||||||
10 | 8 | 3.834496 | 260.790437 | 1566.138983 | 6.781057 | |||||||
10 | 9 | 3.811435 | 262.368351 | 1609.718800 | 6.552622 | |||||||
16 | 2 | True | 600 | 1024 | 10 | 0 | 3.854812 | 259.416029 | 1636.818171 | 6.427616 | ||
10 | 1 | 3.837959 | 260.555148 | 1606.189728 | 6.298289 | |||||||
10 | 2 | 3.841213 | 260.334447 | 1573.059797 | 6.187394 | |||||||
10 | 3 | 3.826297 | 261.349320 | 1541.368961 | 6.510794 | |||||||
10 | 4 | 3.810786 | 262.413070 | 1613.836050 | 6.600820 | |||||||
10 | 5 | 3.844609 | 260.104463 | 1562.781334 | 6.305188 | |||||||
10 | 6 | 3.832436 | 260.930672 | 1536.884785 | 6.461143 | |||||||
10 | 7 | 3.813556 | 262.222484 | 1559.064865 | 6.540872 | |||||||
10 | 8 | 3.830241 | 261.080176 | 1580.272436 | 6.225564 | |||||||
10 | 9 | 3.813589 | 262.220159 | 1595.091581 | 6.294802 | |||||||
32 | 2 | True | 600 | 1024 | 10 | 0 | 3.864463 | 258.768164 | 1577.320099 | 6.226402 | ||
10 | 1 | 3.848046 | 259.872176 | 1571.588993 | 6.021578 | |||||||
10 | 2 | 3.843316 | 260.191955 | 1545.690060 | 6.018501 | |||||||
10 | 3 | 3.847767 | 259.890988 | 1636.627197 | 6.211761 | |||||||
10 | 4 | 3.839370 | 260.459386 | 1544.546366 | 6.139554 | |||||||
10 | 5 | 3.838207 | 260.538295 | 1589.231253 | 6.220452 | |||||||
10 | 6 | 3.844068 | 260.141060 | 1549.546003 | 6.105881 | |||||||
10 | 7 | 3.852871 | 259.546742 | 1572.925806 | 6.310277 | |||||||
10 | 8 | 3.843005 | 260.213032 | 1527.139902 | 6.078742 | |||||||
10 | 9 | 3.830920 | 261.033930 | 1548.498392 | 6.016731 | |||||||
cuda | 1 | 2 | True | 600 | 1024 | 10 | 0 | 16.084366 | 62.172174 | 1567.276478 | 9.552002 | |
10 | 1 | 15.767586 | 63.421249 | 1556.388855 | 9.823442 | |||||||
10 | 2 | 16.132559 | 61.986446 | 1579.791784 | 9.697795 | |||||||
10 | 3 | 15.805613 | 63.268661 | 1537.657022 | 9.535074 | |||||||
10 | 4 | 16.114708 | 62.055111 | 1572.025537 | 9.755731 | |||||||
10 | 5 | 16.276486 | 61.438322 | 1556.050539 | 9.635806 | |||||||
10 | 6 | 15.995302 | 62.518358 | 1579.099894 | 9.872913 | |||||||
10 | 7 | 15.939197 | 62.738419 | 1558.127880 | 9.831071 | |||||||
10 | 8 | 16.222410 | 61.643124 | 1542.162418 | 9.619713 | |||||||
10 | 9 | 16.040508 | 62.342167 | 1581.772089 | 9.413123 | |||||||
2 | 2 | True | 600 | 1024 | 10 | 0 | 18.869419 | 52.995801 | 1550.209761 | 7.856190 | ||
10 | 1 | 18.601131 | 53.760171 | 1540.921688 | 8.131802 | |||||||
10 | 2 | 18.757439 | 53.312182 | 1539.927483 | 8.144259 | |||||||
10 | 3 | 19.118986 | 52.304029 | 1575.437307 | 8.070350 | |||||||
10 | 4 | 18.425405 | 54.272890 | 1562.089443 | 7.939517 | |||||||
10 | 5 | 18.737412 | 53.369164 | 1564.453125 | 8.044004 | |||||||
10 | 6 | 19.089531 | 52.384734 | 1557.888746 | 8.139849 | |||||||
10 | 7 | 18.854364 | 53.038120 | 1559.280396 | 8.034647 | |||||||
10 | 8 | 19.140580 | 52.245021 | 1544.927359 | 7.880390 | |||||||
10 | 9 | 18.818411 | 53.139448 | 1578.546524 | 8.000910 | |||||||
4 | 2 | True | 600 | 1024 | 10 | 0 | 20.235260 | 49.418688 | 1598.390818 | 7.522523 | ||
10 | 1 | 20.737907 | 48.220873 | 1590.816736 | 7.533103 | |||||||
10 | 2 | 20.664268 | 48.392713 | 1582.442522 | 7.434607 | |||||||
10 | 3 | 20.443440 | 48.915446 | 1579.503536 | 7.438391 | |||||||
10 | 4 | 20.673919 | 48.370123 | 1575.470686 | 7.680893 | |||||||
10 | 5 | 20.722769 | 48.256099 | 1590.139151 | 7.592112 | |||||||
10 | 6 | 20.617720 | 48.501968 | 1567.997932 | 7.628381 | |||||||
10 | 7 | 20.751708 | 48.188806 | 1584.429502 | 7.561356 | |||||||
10 | 8 | 20.672900 | 48.372507 | 1578.259468 | 7.628292 | |||||||
10 | 9 | 20.251308 | 49.379528 | 1586.111307 | 7.510394 | |||||||
8 | 2 | True | 600 | 1024 | 10 | 0 | 21.168346 | 47.240347 | 1552.038193 | 6.471038 | ||
10 | 1 | 20.942423 | 47.749966 | 1568.918228 | 6.541625 | |||||||
10 | 2 | 20.961485 | 47.706544 | 1569.382429 | 6.726533 | |||||||
10 | 3 | 21.078944 | 47.440708 | 1556.970835 | 6.642163 | |||||||
10 | 4 | 21.030300 | 47.550440 | 1575.931072 | 6.492779 | |||||||
10 | 5 | 21.013560 | 47.588319 | 1558.716536 | 6.599799 | |||||||
10 | 6 | 20.729477 | 48.240483 | 1554.875374 | 6.788582 | |||||||
10 | 7 | 20.900406 | 47.845960 | 1577.084303 | 6.423414 | |||||||
10 | 8 | 21.157708 | 47.264099 | 1579.204321 | 6.443471 | |||||||
10 | 9 | 21.093294 | 47.408432 | 1558.570147 | 6.477118 | |||||||
16 | 2 | True | 600 | 1024 | 10 | 0 | 21.285771 | 46.979740 | 1574.208736 | 6.273493 | ||
10 | 1 | 21.814649 | 45.840755 | 1547.834158 | 6.276205 | |||||||
10 | 2 | 21.272560 | 47.008917 | 1569.916487 | 6.227680 | |||||||
10 | 3 | 21.355689 | 46.825930 | 1588.491201 | 6.268911 | |||||||
10 | 4 | 21.516113 | 46.476796 | 1551.367760 | 6.255686 | |||||||
10 | 5 | 21.321133 | 46.901822 | 1562.980175 | 6.638221 | |||||||
10 | 6 | 21.605507 | 46.284497 | 1574.791670 | 6.450735 | |||||||
10 | 7 | 21.552654 | 46.397999 | 1586.225033 | 6.326117 | |||||||
10 | 8 | 21.325659 | 46.891868 | 1552.012682 | 6.230108 | |||||||
10 | 9 | 21.816472 | 45.836926 | 1549.138546 | 6.490417 | |||||||
32 | 2 | True | 600 | 1024 | 10 | 0 | 21.648104 | 46.193421 | 2622.985125 | 5.982913 | ||
10 | 1 | 21.612583 | 46.269342 | 1578.860044 | 5.948056 | |||||||
10 | 2 | 21.579898 | 46.339422 | 1557.170868 | 5.979646 | |||||||
10 | 3 | 21.113880 | 47.362208 | 1564.578056 | 6.043833 | |||||||
10 | 4 | 21.264138 | 47.027536 | 1575.670719 | 5.968492 | |||||||
10 | 5 | 21.639975 | 46.210773 | 1553.828239 | 6.170273 | |||||||
10 | 6 | 21.754156 | 45.968227 | 1556.079626 | 6.273590 | |||||||
10 | 7 | 21.594380 | 46.308346 | 1561.932802 | 6.225429 | |||||||
10 | 8 | 21.437587 | 46.647042 | 1545.925856 | 5.935386 | |||||||
10 | 9 | 21.671702 | 46.143122 | 1582.964659 | 5.895533 | |||||||
tensorrt | 1 | 2 | True | 600 | 1024 | 10 | 0 | 15.691373 | 63.729286 | 19319.557190 | 9.539604 | |
10 | 1 | 16.066745 | 62.240362 | 19135.199308 | 9.448171 | |||||||
10 | 2 | 16.237734 | 61.584949 | 18963.383913 | 9.652853 | |||||||
10 | 3 | 15.890946 | 62.928915 | 19239.841938 | 9.773254 | |||||||
10 | 4 | 16.168193 | 61.849833 | 18947.120667 | 9.727597 | |||||||
10 | 5 | 16.050697 | 62.302589 | 19103.104830 | 9.832144 | |||||||
10 | 6 | 15.662310 | 63.847542 | 19037.372112 | 9.446740 | |||||||
10 | 7 | 15.738181 | 63.539743 | 19217.607260 | 9.669065 | |||||||
10 | 8 | 15.890404 | 62.931061 | 19089.416265 | 9.625077 | |||||||
10 | 9 | 16.007144 | 62.472105 | 19097.249746 | 9.390116 | |||||||
2 | 2 | True | 600 | 1024 | 10 | 0 | 18.722816 | 53.410769 | 19902.643919 | 7.814705 | ||
10 | 1 | 18.369201 | 54.438949 | 20071.136236 | 7.931173 | |||||||
10 | 2 | 18.643340 | 53.638458 | 19664.289951 | 7.718384 | |||||||
10 | 3 | 18.347425 | 54.503560 | 19818.207979 | 7.790208 | |||||||
10 | 4 | 18.914263 | 52.870154 | 19927.687168 | 7.919431 | |||||||
10 | 5 | 18.418932 | 54.291964 | 19979.107618 | 7.784545 | |||||||
10 | 6 | 18.046460 | 55.412531 | 19901.773214 | 7.896602 | |||||||
10 | 7 | 18.879697 | 52.966952 | 19892.263412 | 7.928789 | |||||||
10 | 8 | 19.006444 | 52.613735 | 19943.155289 | 7.798970 | |||||||
10 | 9 | 18.303110 | 54.635525 | 19775.532484 | 7.949591 | |||||||
4 | 2 | True | 600 | 1024 | 10 | 0 | 20.535098 | 48.697114 | 14887.097836 | 7.770628 | ||
10 | 1 | 20.871364 | 47.912538 | 14837.127686 | 7.451624 | |||||||
10 | 2 | 19.893728 | 50.267100 | 14736.799479 | 7.715344 | |||||||
10 | 3 | 20.228770 | 49.434543 | 14832.970142 | 7.595092 | |||||||
10 | 4 | 20.390196 | 49.043179 | 14797.318459 | 7.516712 | |||||||
10 | 5 | 19.897644 | 50.257206 | 14650.147915 | 7.577091 | |||||||
10 | 6 | 20.963004 | 47.703087 | 14841.446400 | 7.591426 | |||||||
10 | 7 | 20.416796 | 48.979282 | 14787.937403 | 7.556558 | |||||||
10 | 8 | 20.272229 | 49.328566 | 14814.521074 | 7.412940 | |||||||
10 | 9 | 20.624741 | 48.485458 | 14747.805834 | 7.531047 | |||||||
8 | 2 | True | 600 | 1024 | 10 | 0 | 20.523932 | 48.723608 | 14709.718943 | 6.500468 | ||
10 | 1 | 20.800436 | 48.075914 | 14736.230612 | 6.597221 | |||||||
10 | 2 | 20.801120 | 48.074335 | 14834.714651 | 6.659746 | |||||||
10 | 3 | 20.381575 | 49.063921 | 14885.342598 | 6.665811 | |||||||
10 | 4 | 20.680889 | 48.353821 | 14964.942932 | 6.466866 | |||||||
10 | 5 | 20.674594 | 48.368543 | 14761.517286 | 6.718606 | |||||||
10 | 6 | 20.751785 | 48.188627 | 14838.866711 | 6.756231 | |||||||
10 | 7 | 20.668252 | 48.383385 | 14749.555826 | 6.562561 | |||||||
10 | 8 | 20.842673 | 47.978491 | 14885.761738 | 6.570294 | |||||||
10 | 9 | 20.686052 | 48.341751 | 14799.415827 | 6.419659 | |||||||
16 | 2 | True | 600 | 1024 | 10 | 0 | 21.451991 | 46.615720 | 14167.942286 | 6.249599 | ||
10 | 1 | 21.320795 | 46.902567 | 14100.311995 | 6.188668 | |||||||
10 | 2 | 21.426163 | 46.671912 | 14353.028536 | 6.249785 | |||||||
10 | 3 | 21.325700 | 46.891779 | 14178.853989 | 6.322034 | |||||||
10 | 4 | 21.600778 | 46.294630 | 14232.103586 | 6.441049 | |||||||
10 | 5 | 21.403223 | 46.721935 | 14159.862041 | 6.345078 | |||||||
10 | 6 | 21.221657 | 47.121674 | 14205.360174 | 6.275162 | |||||||
10 | 7 | 21.808517 | 45.853645 | 14251.514673 | 6.265521 | |||||||
10 | 8 | 21.472631 | 46.570912 | 14136.046886 | 6.623082 | |||||||
10 | 9 | 21.514844 | 46.479538 | 14198.043108 | 6.200984 | |||||||
32 | 2 | True | 600 | 1024 | 10 | 0 | 21.399831 | 46.729341 | 14813.133955 | 5.983353 | ||
10 | 1 | 21.077047 | 47.444977 | 15146.105051 | 6.208703 | |||||||
10 | 2 | 21.434564 | 46.653621 | 14987.927675 | 6.029747 | |||||||
10 | 3 | 21.054068 | 47.496758 | 14913.025141 | 5.958252 | |||||||
10 | 4 | 21.407391 | 46.712838 | 14824.986458 | 6.372876 | |||||||
10 | 5 | 21.667721 | 46.151601 | 14543.232679 | 6.207205 | |||||||
10 | 6 | 21.553353 | 46.396494 | 15270.527840 | 6.166164 | |||||||
10 | 7 | 21.426570 | 46.671025 | 15092.374563 | 6.257627 | |||||||
10 | 8 | 21.373267 | 46.787418 | 15003.621578 | 6.111909 | |||||||
10 | 9 | 21.835027 | 45.797974 | 14296.097994 | 5.982772 | |||||||
tensorrt-dynamic | 1 | 2 | True | 600 | 1024 | 10 | 0 | 19.547941 | 51.156282 | 10180.581331 | 9.346962 | |
10 | 1 | 19.277509 | 51.873922 | 10163.849592 | 9.350657 | |||||||
10 | 2 | 19.510115 | 51.255465 | 10287.260056 | 9.528279 | |||||||
10 | 3 | 19.058867 | 52.469015 | 10135.560513 | 9.253860 | |||||||
10 | 4 | 19.540564 | 51.175594 | 10073.168755 | 9.530902 | |||||||
10 | 5 | 19.310525 | 51.785231 | 10132.394791 | 9.380341 | |||||||
10 | 6 | 19.149625 | 52.220345 | 10165.155172 | 9.348631 | |||||||
10 | 7 | 19.451754 | 51.409245 | 10150.344610 | 9.406328 | |||||||
10 | 8 | 20.320059 | 49.212456 | 10031.230688 | 9.447813 | |||||||
10 | 9 | 19.664979 | 50.851822 | 10164.824486 | 9.219527 | |||||||
2 | 2 | True | 600 | 1024 | 10 | 0 | 22.949729 | 43.573499 | 10234.578848 | 7.745802 | ||
10 | 1 | 23.307969 | 42.903781 | 10127.582073 | 7.786870 | |||||||
10 | 2 | 22.395421 | 44.651985 | 10190.723181 | 7.788539 | |||||||
10 | 3 | 22.153697 | 45.139194 | 10205.787420 | 7.702053 | |||||||
10 | 4 | 22.028213 | 45.396328 | 10160.840750 | 7.712722 | |||||||
10 | 5 | 22.668666 | 44.113755 | 10264.372826 | 7.872105 | |||||||
10 | 6 | 22.913997 | 43.641448 | 10351.198196 | 7.881701 | |||||||
10 | 7 | 23.252020 | 43.007016 | 10173.133373 | 7.907987 | |||||||
10 | 8 | 23.347671 | 42.830825 | 10346.702337 | 7.804811 | |||||||
10 | 9 | 22.761730 | 43.933392 | 10099.149704 | 7.834911 | |||||||
4 | 2 | True | 600 | 1024 | 10 | 0 | 24.980928 | 40.030539 | 10210.936308 | 7.672369 | ||
10 | 1 | 24.315863 | 41.125417 | 10129.615307 | 7.373780 | |||||||
10 | 2 | 24.481564 | 40.847063 | 10110.827208 | 7.653028 | |||||||
10 | 3 | 24.314594 | 41.127563 | 10235.378981 | 7.516921 | |||||||
10 | 4 | 24.006926 | 41.654646 | 10211.080074 | 7.368803 | |||||||
10 | 5 | 23.840958 | 41.944623 | 10235.380888 | 7.643521 | |||||||
10 | 6 | 24.729655 | 40.437281 | 10239.523649 | 7.675588 | |||||||
10 | 7 | 23.922443 | 41.801751 | 10143.581629 | 7.406592 | |||||||
10 | 8 | 25.000061 | 39.999902 | 10203.043222 | 7.486582 | |||||||
10 | 9 | 24.427135 | 40.938079 | 10122.092724 | 7.486641 | |||||||
8 | 2 | True | 600 | 1024 | 10 | 0 | 25.554476 | 39.132088 | 10071.565628 | 6.368309 | ||
10 | 1 | 25.588033 | 39.080769 | 10232.257605 | 6.553963 | |||||||
10 | 2 | 25.195574 | 39.689511 | 10183.977604 | 6.563455 | |||||||
10 | 3 | 25.130810 | 39.791793 | 10264.825344 | 6.493405 | |||||||
10 | 4 | 25.078032 | 39.875537 | 10099.519730 | 6.400272 | |||||||
10 | 5 | 25.040546 | 39.935231 | 10256.351471 | 6.537244 | |||||||
10 | 6 | 25.259359 | 39.589286 | 10054.270744 | 6.733045 | |||||||
10 | 7 | 24.842162 | 40.254146 | 10206.881762 | 6.629705 | |||||||
10 | 8 | 25.477580 | 39.250195 | 10128.998518 | 6.429940 | |||||||
10 | 9 | 25.006116 | 39.990216 | 10079.476833 | 6.499588 | |||||||
16 | 2 | True | 600 | 1024 | 10 | 0 | 25.089114 | 39.857924 | 10100.908995 | 6.341994 | ||
10 | 1 | 25.180514 | 39.713249 | 10158.185482 | 6.254509 | |||||||
10 | 2 | 25.322160 | 39.491102 | 10162.925482 | 6.388113 | |||||||
10 | 3 | 25.077367 | 39.876595 | 10212.424040 | 6.413274 | |||||||
10 | 4 | 25.038762 | 39.938077 | 10214.348316 | 6.333299 | |||||||
10 | 5 | 25.090333 | 39.855987 | 10069.103003 | 6.450847 | |||||||
10 | 6 | 25.516960 | 39.189622 | 10053.850174 | 6.228276 | |||||||
10 | 7 | 25.400204 | 39.369762 | 10129.296064 | 6.264724 | |||||||
10 | 8 | 25.372432 | 39.412856 | 10157.729149 | 6.278612 | |||||||
10 | 9 | 25.307674 | 39.513707 | 10180.256844 | 6.326571 | |||||||
ssd-inception-v2 | cpu | 1 | 2 | True | 300 | 300 | 10 | 0 | 26.572632 | 37.632704 | 1036.832571 | 9.979129 |
10 | 1 | 25.716150 | 38.886070 | 1052.604437 | 10.076046 | |||||||
10 | 2 | 26.590658 | 37.607193 | 1026.300430 | 9.832025 | |||||||
10 | 3 | 26.577347 | 37.626028 | 1056.766033 | 10.233045 | |||||||
10 | 4 | 23.907342 | 41.828156 | 1039.777040 | 9.956598 | |||||||
10 | 5 | 26.816429 | 37.290573 | 1021.740913 | 9.971499 | |||||||
10 | 6 | 26.684888 | 37.474394 | 1044.924021 | 10.188818 | |||||||
10 | 7 | 25.423568 | 39.333582 | 1032.768726 | 10.091543 | |||||||
10 | 8 | 25.973013 | 38.501501 | 1049.998283 | 9.798884 | |||||||
10 | 9 | 26.749388 | 37.384033 | 1030.857325 | 9.883761 | |||||||
2 | 2 | True | 300 | 300 | 10 | 0 | 32.043027 | 31.208038 | 1066.937923 | 8.204281 | ||
10 | 1 | 31.326843 | 31.921506 | 1013.860941 | 8.305132 | |||||||
10 | 2 | 32.727602 | 30.555248 | 1017.535210 | 8.301854 | |||||||
10 | 3 | 31.137768 | 32.115340 | 1122.016907 | 8.570492 | |||||||
10 | 4 | 31.417301 | 31.829596 | 1069.966793 | 8.527339 | |||||||
10 | 5 | 31.583139 | 31.662464 | 1033.203602 | 8.397460 | |||||||
10 | 6 | 32.600540 | 30.674338 | 1074.125528 | 8.381069 | |||||||
10 | 7 | 31.778762 | 31.467557 | 1052.721739 | 8.592367 | |||||||
10 | 8 | 32.721602 | 30.560851 | 1072.947264 | 8.622944 | |||||||
10 | 9 | 31.767570 | 31.478643 | 1021.064281 | 8.429468 | |||||||
4 | 2 | True | 300 | 300 | 10 | 0 | 34.712152 | 28.808355 | 1079.628944 | 8.134544 | ||
10 | 1 | 35.080577 | 28.505802 | 1052.744389 | 8.479595 | |||||||
10 | 2 | 36.187273 | 27.634025 | 1064.787149 | 8.079141 | |||||||
10 | 3 | 34.302220 | 29.152632 | 1054.917336 | 8.094251 | |||||||
10 | 4 | 34.690117 | 28.826654 | 1076.272964 | 8.246601 | |||||||
10 | 5 | 33.377930 | 29.959917 | 1068.475246 | 8.141667 | |||||||
10 | 6 | 34.564902 | 28.931081 | 1044.254780 | 8.358598 | |||||||
10 | 7 | 35.557907 | 28.123140 | 1029.908180 | 8.054137 | |||||||
10 | 8 | 35.066060 | 28.517604 | 1081.802130 | 8.091629 | |||||||
10 | 9 | 34.662022 | 28.850019 | 1085.449696 | 8.209705 | |||||||
8 | 2 | True | 300 | 300 | 10 | 0 | 37.562291 | 26.622444 | 1047.247410 | 7.124349 | ||
10 | 1 | 37.033181 | 27.002811 | 1053.466082 | 7.265568 | |||||||
10 | 2 | 37.049783 | 26.990712 | 1032.723665 | 6.791547 | |||||||
10 | 3 | 37.758629 | 26.484013 | 1050.156116 | 7.198974 | |||||||
10 | 4 | 37.212164 | 26.872933 | 1031.953812 | 6.740212 | |||||||
10 | 5 | 37.178190 | 26.897490 | 1072.241068 | 6.956279 | |||||||
10 | 6 | 37.115846 | 26.942670 | 1005.733490 | 6.915882 | |||||||
10 | 7 | 37.672318 | 26.544690 | 1009.104013 | 7.019505 | |||||||
10 | 8 | 37.186307 | 26.891619 | 1058.635473 | 6.974444 | |||||||
10 | 9 | 37.773038 | 26.473910 | 1056.904554 | 6.848559 | |||||||
16 | 2 | True | 300 | 300 | 10 | 0 | 38.760825 | 25.799245 | 1037.404537 | 6.621554 | ||
10 | 1 | 38.587141 | 25.915369 | 1084.344625 | 6.622039 | |||||||
10 | 2 | 37.776908 | 26.471198 | 1084.999084 | 6.839000 | |||||||
10 | 3 | 38.882073 | 25.718793 | 1034.811497 | 6.646998 | |||||||
10 | 4 | 38.437735 | 26.016101 | 1054.725647 | 6.825827 | |||||||
10 | 5 | 37.957524 | 26.345238 | 1047.569513 | 6.969713 | |||||||
10 | 6 | 38.986408 | 25.649965 | 1011.844397 | 6.576128 | |||||||
10 | 7 | 37.696145 | 26.527911 | 1029.245853 | 6.486863 | |||||||
10 | 8 | 37.715064 | 26.514605 | 1066.723347 | 6.803140 | |||||||
10 | 9 | 37.829549 | 26.434362 | 1069.365263 | 6.891549 | |||||||
32 | 2 | True | 300 | 300 | 10 | 0 | 41.369771 | 24.172239 | 1877.101421 | 6.227642 | ||
10 | 1 | 41.823907 | 23.909770 | 1041.133165 | 6.384440 | |||||||
10 | 2 | 41.438539 | 24.132125 | 1031.316280 | 6.295051 | |||||||
10 | 3 | 41.317048 | 24.203084 | 1022.511482 | 6.299019 | |||||||
10 | 4 | 41.612971 | 24.030969 | 1039.436340 | 6.318260 | |||||||
10 | 5 | 41.997414 | 23.810990 | 1026.664257 | 6.244041 | |||||||
10 | 6 | 41.327073 | 24.197213 | 1021.815777 | 6.243180 | |||||||
10 | 7 | 40.745813 | 24.542399 | 1082.146883 | 6.241050 | |||||||
10 | 8 | 41.205146 | 24.268813 | 1055.332422 | 6.234813 | |||||||
10 | 9 | 40.993315 | 24.394222 | 1066.293716 | 6.245423 | |||||||
cpu-prebuilt | 1 | 2 | True | 300 | 300 | 10 | 0 | 25.310193 | 39.509773 | 1867.937565 | 9.948254 | |
10 | 1 | 26.275655 | 38.058043 | 981.299639 | 9.884000 | |||||||
10 | 2 | 26.514176 | 37.715673 | 962.152719 | 10.094285 | |||||||
10 | 3 | 26.516020 | 37.713051 | 978.623629 | 9.932637 | |||||||
10 | 4 | 26.118577 | 38.286924 | 965.626478 | 9.927273 | |||||||
10 | 5 | 27.215064 | 36.744356 | 957.661629 | 10.138273 | |||||||
10 | 6 | 24.788738 | 40.340900 | 966.713190 | 10.067463 | |||||||
10 | 7 | 26.974057 | 37.072659 | 968.365669 | 9.965897 | |||||||
10 | 8 | 25.825564 | 38.721323 | 1029.874802 | 10.140657 | |||||||
10 | 9 | 27.613726 | 36.213875 | 979.713202 | 9.949684 | |||||||
2 | 2 | True | 300 | 300 | 10 | 0 | 32.721091 | 30.561328 | 963.088512 | 8.421898 | ||
10 | 1 | 31.530668 | 31.715155 | 959.016800 | 8.090496 | |||||||
10 | 2 | 32.665919 | 30.612946 | 967.540503 | 8.118570 | |||||||
10 | 3 | 31.888452 | 31.359315 | 1007.323503 | 8.356035 | |||||||
10 | 4 | 31.761195 | 31.484962 | 992.185116 | 8.307159 | |||||||
10 | 5 | 32.031525 | 31.219244 | 964.762449 | 8.395672 | |||||||
10 | 6 | 33.484917 | 29.864192 | 1035.646677 | 8.118153 | |||||||
10 | 7 | 31.882877 | 31.364799 | 949.239254 | 8.268595 | |||||||
10 | 8 | 32.539461 | 30.731916 | 972.521782 | 8.156657 | |||||||
10 | 9 | 32.463151 | 30.804157 | 958.978176 | 8.524895 | |||||||
4 | 2 | True | 300 | 300 | 10 | 0 | 36.524136 | 27.379155 | 1057.915449 | 7.965326 | ||
10 | 1 | 34.525851 | 28.963804 | 977.621317 | 8.055300 | |||||||
10 | 2 | 34.211428 | 29.229999 | 973.495722 | 8.031219 | |||||||
10 | 3 | 35.736275 | 27.982771 | 972.449064 | 8.033156 | |||||||
10 | 4 | 35.382728 | 28.262377 | 975.290775 | 7.904619 | |||||||
10 | 5 | 35.067306 | 28.516591 | 971.166134 | 8.013546 | |||||||
10 | 6 | 35.571552 | 28.112352 | 972.326040 | 8.023113 | |||||||
10 | 7 | 34.884363 | 28.666139 | 969.641447 | 8.077502 | |||||||
10 | 8 | 36.474825 | 27.416170 | 970.388651 | 7.910192 | |||||||
10 | 9 | 34.980591 | 28.587282 | 964.927912 | 8.209705 | |||||||
8 | 2 | True | 300 | 300 | 10 | 0 | 38.185275 | 26.188105 | 968.335152 | 6.790340 | ||
10 | 1 | 37.877078 | 26.401192 | 959.783554 | 6.948248 | |||||||
10 | 2 | 37.318362 | 26.796460 | 992.677689 | 7.083684 | |||||||
10 | 3 | 38.653840 | 25.870651 | 987.122536 | 6.998539 | |||||||
10 | 4 | 37.473358 | 26.685625 | 961.175203 | 6.757125 | |||||||
10 | 5 | 37.138070 | 26.926547 | 959.964514 | 6.811559 | |||||||
10 | 6 | 37.649619 | 26.560694 | 978.461504 | 6.938145 | |||||||
10 | 7 | 37.893846 | 26.389509 | 975.080729 | 6.824479 | |||||||
10 | 8 | 37.623319 | 26.579261 | 975.236893 | 6.731853 | |||||||
10 | 9 | 37.729631 | 26.504368 | 1045.089245 | 6.872997 | |||||||
16 | 2 | True | 300 | 300 | 10 | 0 | 38.612606 | 25.898278 | 978.707552 | 6.551683 | ||
10 | 1 | 38.210822 | 26.170596 | 1036.368132 | 6.597474 | |||||||
10 | 2 | 37.996466 | 26.318237 | 972.175360 | 6.533176 | |||||||
10 | 3 | 38.168986 | 26.199281 | 978.079319 | 6.587684 | |||||||
10 | 4 | 38.205188 | 26.174456 | 964.130640 | 6.586052 | |||||||
10 | 5 | 39.245455 | 25.480658 | 1013.383627 | 6.861612 | |||||||
10 | 6 | 38.218634 | 26.165247 | 960.180998 | 6.540664 | |||||||
10 | 7 | 37.764514 | 26.479885 | 967.053413 | 6.576061 | |||||||
10 | 8 | 38.970583 | 25.660381 | 968.597889 | 6.532528 | |||||||
10 | 9 | 37.874491 | 26.402995 | 983.211279 | 6.573610 | |||||||
32 | 2 | True | 300 | 300 | 10 | 0 | 41.838131 | 23.901641 | 975.125790 | 6.271232 | ||
10 | 1 | 41.999227 | 23.809962 | 982.212782 | 6.267916 | |||||||
10 | 2 | 41.301829 | 24.212003 | 1006.886482 | 6.328121 | |||||||
10 | 3 | 41.721473 | 23.968473 | 969.808578 | 6.299771 | |||||||
10 | 4 | 41.430263 | 24.136946 | 978.005648 | 6.249879 | |||||||
10 | 5 | 41.507189 | 24.092212 | 972.927809 | 6.207235 | |||||||
10 | 6 | 41.930330 | 23.849085 | 975.277662 | 6.333619 | |||||||
10 | 7 | 41.525321 | 24.081692 | 1004.874945 | 6.319590 | |||||||
10 | 8 | 41.925196 | 23.852006 | 970.216036 | 6.385561 | |||||||
10 | 9 | 41.331082 | 24.194866 | 982.164860 | 6.246779 | |||||||
cuda | 1 | 2 | True | 300 | 300 | 10 | 0 | 28.109696 | 35.574913 | 965.090752 | 10.004997 | |
10 | 1 | 29.774500 | 33.585787 | 976.880312 | 9.919405 | |||||||
10 | 2 | 27.870426 | 35.880327 | 962.543249 | 9.828210 | |||||||
10 | 3 | 27.885435 | 35.861015 | 951.909065 | 9.944797 | |||||||
10 | 4 | 27.480387 | 36.389589 | 978.668928 | 9.979367 | |||||||
10 | 5 | 27.832513 | 35.929203 | 980.034351 | 10.072112 | |||||||
10 | 6 | 27.539389 | 36.311626 | 986.590862 | 10.156035 | |||||||
10 | 7 | 28.420545 | 35.185814 | 962.435722 | 9.937167 | |||||||
10 | 8 | 27.704925 | 36.094666 | 979.434967 | 9.976506 | |||||||
10 | 9 | 28.175408 | 35.491943 | 972.663403 | 9.947777 | |||||||
2 | 2 | True | 300 | 300 | 10 | 0 | 38.258201 | 26.138186 | 972.539425 | 8.261263 | ||
10 | 1 | 38.212889 | 26.169181 | 978.279114 | 8.065999 | |||||||
10 | 2 | 35.699091 | 28.011918 | 973.811865 | 8.113444 | |||||||
10 | 3 | 36.653724 | 27.282357 | 994.790077 | 8.419037 | |||||||
10 | 4 | 37.787203 | 26.463985 | 978.210688 | 8.262396 | |||||||
10 | 5 | 37.740282 | 26.496887 | 973.612070 | 8.270741 | |||||||
10 | 6 | 37.583874 | 26.607156 | 989.429951 | 8.133411 | |||||||
10 | 7 | 37.682979 | 26.537180 | 969.769478 | 8.420289 | |||||||
10 | 8 | 37.053792 | 26.987791 | 960.559368 | 8.078039 | |||||||
10 | 9 | 36.546732 | 27.362227 | 962.187052 | 8.148491 | |||||||
4 | 2 | True | 300 | 300 | 10 | 0 | 45.336475 | 22.057295 | 994.799137 | 7.867455 | ||
10 | 1 | 44.779843 | 22.331476 | 976.380587 | 7.975012 | |||||||
10 | 2 | 45.576637 | 21.941066 | 965.592623 | 8.256733 | |||||||
10 | 3 | 44.983955 | 22.230148 | 973.847628 | 7.987708 | |||||||
10 | 4 | 43.230665 | 23.131728 | 975.527048 | 7.878542 | |||||||
10 | 5 | 42.922093 | 23.298025 | 987.102747 | 7.803261 | |||||||
10 | 6 | 46.138532 | 21.673858 | 965.362549 | 8.048773 | |||||||
10 | 7 | 44.891515 | 22.275925 | 976.725578 | 7.851899 | |||||||
10 | 8 | 46.558759 | 21.478236 | 963.508606 | 7.830173 | |||||||
10 | 9 | 43.252844 | 23.119867 | 970.390081 | 7.907033 | |||||||
8 | 2 | True | 300 | 300 | 10 | 0 | 48.758858 | 20.509094 | 974.528313 | 6.979302 | ||
10 | 1 | 47.543417 | 21.033406 | 972.609997 | 6.738648 | |||||||
10 | 2 | 48.377209 | 20.670891 | 977.948189 | 6.830394 | |||||||
10 | 3 | 46.740548 | 21.394700 | 966.236353 | 6.759718 | |||||||
10 | 4 | 48.735205 | 20.519048 | 974.811792 | 6.884545 | |||||||
10 | 5 | 48.517108 | 20.611286 | 986.879349 | 6.732196 | |||||||
10 | 6 | 47.390588 | 21.101236 | 967.341661 | 6.750762 | |||||||
10 | 7 | 49.090206 | 20.370662 | 952.601671 | 6.834149 | |||||||
10 | 8 | 48.310482 | 20.699441 | 970.391750 | 6.702393 | |||||||
10 | 9 | 47.784858 | 20.927131 | 965.574026 | 6.894395 | |||||||
16 | 2 | True | 300 | 300 | 10 | 0 | 49.848775 | 20.060673 | 979.045868 | 6.553441 | ||
10 | 1 | 48.719283 | 20.525753 | 983.616829 | 6.514989 | |||||||
10 | 2 | 50.066969 | 19.973248 | 971.480370 | 6.541945 | |||||||
10 | 3 | 48.540656 | 20.601287 | 975.140095 | 6.616287 | |||||||
10 | 4 | 51.361248 | 19.469932 | 988.603592 | 6.547920 | |||||||
10 | 5 | 49.087728 | 20.371690 | 977.543354 | 6.680205 | |||||||
10 | 6 | 50.312001 | 19.875973 | 977.187634 | 6.563298 | |||||||
10 | 7 | 48.251675 | 20.724669 | 963.807583 | 6.742224 | |||||||
10 | 8 | 48.084928 | 20.796537 | 976.600885 | 6.880574 | |||||||
10 | 9 | 51.159407 | 19.546747 | 965.466738 | 6.520070 | |||||||
32 | 2 | True | 300 | 300 | 10 | 0 | 49.659819 | 20.137005 | 976.863623 | 6.238621 | ||
10 | 1 | 53.331901 | 18.750504 | 999.082327 | 6.282549 | |||||||
10 | 2 | 53.744168 | 18.606670 | 986.496449 | 6.261077 | |||||||
10 | 3 | 50.400741 | 19.840978 | 969.493151 | 6.621391 | |||||||
10 | 4 | 52.747946 | 18.958084 | 964.337826 | 6.287921 | |||||||
10 | 5 | 51.363214 | 19.469187 | 975.760937 | 6.225426 | |||||||
10 | 6 | 53.496259 | 18.692896 | 978.708506 | 6.241269 | |||||||
10 | 7 | 52.518142 | 19.041039 | 988.959074 | 6.210350 | |||||||
10 | 8 | 51.895814 | 19.269377 | 983.508110 | 6.235622 | |||||||
10 | 9 | 53.257749 | 18.776610 | 966.600418 | 6.271277 | |||||||
tensorrt | 1 | 2 | True | 300 | 300 | 10 | 0 | 27.321608 | 36.601067 | 7839.582682 | 9.767532 | |
10 | 1 | 28.862141 | 34.647465 | 7773.597240 | 9.782195 | |||||||
10 | 2 | 28.424782 | 35.180569 | 7721.834660 | 9.779096 | |||||||
10 | 3 | 27.456282 | 36.421537 | 7757.497311 | 9.789348 | |||||||
10 | 4 | 27.313602 | 36.611795 | 7707.455635 | 9.891152 | |||||||
10 | 5 | 28.126850 | 35.553217 | 7734.989643 | 9.801149 | |||||||
10 | 6 | 27.824573 | 35.939455 | 7794.776917 | 9.782791 | |||||||
10 | 7 | 28.169921 | 35.498857 | 7746.086597 | 9.799957 | |||||||
10 | 8 | 26.829809 | 37.271976 | 7796.165466 | 9.813070 | |||||||
10 | 9 | 28.702160 | 34.840584 | 7715.471506 | 10.026932 | |||||||
2 | 2 | True | 300 | 300 | 10 | 0 | 36.985829 | 27.037382 | 7632.844210 | 8.126676 | ||
10 | 1 | 36.670869 | 27.269602 | 7687.655926 | 8.127272 | |||||||
10 | 2 | 38.436832 | 26.016712 | 7789.947987 | 8.062303 | |||||||
10 | 3 | 35.066060 | 28.517604 | 7786.698580 | 8.104444 | |||||||
10 | 4 | 37.074426 | 26.972771 | 7666.020632 | 8.024037 | |||||||
10 | 5 | 37.581685 | 26.608706 | 7781.909943 | 8.216202 | |||||||
10 | 6 | 37.255051 | 26.841998 | 7782.733679 | 8.075118 | |||||||
10 | 7 | 35.951383 | 27.815342 | 7691.067696 | 8.031487 | |||||||
10 | 8 | 37.446134 | 26.705027 | 7735.203028 | 8.328497 | |||||||
10 | 9 | 36.652603 | 27.283192 | 7770.588875 | 8.040667 | |||||||
4 | 2 | True | 300 | 300 | 10 | 0 | 44.146386 | 22.651911 | 7740.692139 | 7.919252 | ||
10 | 1 | 44.761683 | 22.340536 | 7769.182444 | 7.846475 | |||||||
10 | 2 | 43.392681 | 23.045361 | 7905.809402 | 7.800639 | |||||||
10 | 3 | 44.693715 | 22.374511 | 7671.643257 | 7.870644 | |||||||
10 | 4 | 42.553577 | 23.499787 | 7732.587576 | 7.852584 | |||||||
10 | 5 | 42.821742 | 23.352623 | 7811.178684 | 7.852226 | |||||||
10 | 6 | 46.288487 | 21.603644 | 7808.376551 | 7.758766 | |||||||
10 | 7 | 44.280263 | 22.583425 | 7781.347036 | 8.029252 | |||||||
10 | 8 | 44.176260 | 22.636592 | 7809.327841 | 7.926226 | |||||||
10 | 9 | 44.379356 | 22.533000 | 7739.988327 | 8.020282 | |||||||
8 | 2 | True | 300 | 300 | 10 | 0 | 48.026221 | 20.821959 | 7748.511791 | 6.949395 | ||
10 | 1 | 46.435372 | 21.535307 | 7780.887365 | 6.781697 | |||||||
10 | 2 | 48.929357 | 20.437628 | 7824.104071 | 6.719023 | |||||||
10 | 3 | 47.240668 | 21.168202 | 7722.230673 | 6.973475 | |||||||
10 | 4 | 48.485700 | 20.624638 | 7709.615469 | 6.775752 | |||||||
10 | 5 | 47.835064 | 20.905167 | 7706.537724 | 6.921723 | |||||||
10 | 6 | 48.050636 | 20.811379 | 7825.880289 | 6.969839 | |||||||
10 | 7 | 47.129924 | 21.217942 | 7810.398340 | 7.025376 | |||||||
10 | 8 | 47.452246 | 21.073818 | 7759.536266 | 6.922394 | |||||||
10 | 9 | 47.338171 | 21.124601 | 7723.293781 | 6.927058 | |||||||
16 | 2 | True | 300 | 300 | 10 | 0 | 49.736907 | 20.105794 | 7798.283100 | 6.811634 | ||
10 | 1 | 49.476083 | 20.211786 | 7794.642210 | 6.920174 | |||||||
10 | 2 | 50.439437 | 19.825757 | 7814.896822 | 6.792612 | |||||||
10 | 3 | 47.691438 | 20.968124 | 7675.437212 | 6.487630 | |||||||
10 | 4 | 49.773685 | 20.090938 | 7709.287167 | 6.701380 | |||||||
10 | 5 | 51.694456 | 19.344434 | 7704.929352 | 6.803341 | |||||||
10 | 6 | 48.661065 | 20.550311 | 7803.060770 | 6.765634 | |||||||
10 | 7 | 47.635446 | 20.992771 | 7775.330544 | 6.620087 | |||||||
10 | 8 | 50.336757 | 19.866198 | 7829.347372 | 6.883018 | |||||||
10 | 9 | 49.976701 | 20.009324 | 7808.050156 | 6.663896 | |||||||
32 | 2 | True | 300 | 300 | 10 | 0 | 51.145702 | 19.551985 | 7739.619017 | 6.216977 | ||
10 | 1 | 51.043740 | 19.591041 | 7721.035242 | 6.571375 | |||||||
10 | 2 | 51.182974 | 19.537747 | 7775.461912 | 6.222706 | |||||||
10 | 3 | 50.527391 | 19.791245 | 7787.240505 | 6.206919 | |||||||
10 | 4 | 51.528362 | 19.406788 | 7768.876076 | 6.189309 | |||||||
10 | 5 | 51.621468 | 19.371785 | 7786.898851 | 6.566465 | |||||||
10 | 6 | 52.143376 | 19.177891 | 7719.694853 | 6.319970 | |||||||
10 | 7 | 51.260305 | 19.508272 | 7847.770214 | 6.463062 | |||||||
10 | 8 | 53.134703 | 18.820092 | 7692.381144 | 6.631248 | |||||||
10 | 9 | 52.980898 | 18.874727 | 7763.093472 | 6.218217 | |||||||
tensorrt-dynamic | 1 | 2 | True | 300 | 300 | 10 | 0 | 31.003467 | 32.254457 | 6521.617889 | 9.732723 | |
10 | 1 | 31.812144 | 31.434536 | 6554.062366 | 9.750843 | |||||||
10 | 2 | 31.259486 | 31.990290 | 6575.267792 | 9.656787 | |||||||
10 | 3 | 32.676353 | 30.603170 | 6674.555779 | 9.833217 | |||||||
10 | 4 | 32.167128 | 31.087637 | 6644.479513 | 9.810805 | |||||||
10 | 5 | 32.307368 | 30.952692 | 6647.858381 | 9.827614 | |||||||
10 | 6 | 32.150361 | 31.103849 | 6569.484949 | 9.874940 | |||||||
10 | 7 | 31.519294 | 31.726599 | 6587.929964 | 9.768128 | |||||||
10 | 8 | 34.118895 | 29.309273 | 6669.947863 | 9.757519 | |||||||
10 | 9 | 33.977382 | 29.431343 | 6591.243029 | 9.645939 | |||||||
2 | 2 | True | 300 | 300 | 10 | 0 | 38.949390 | 25.674343 | 6567.115545 | 8.064389 | ||
10 | 1 | 39.330880 | 25.425315 | 6570.331097 | 8.101523 | |||||||
10 | 2 | 38.165079 | 26.201963 | 6622.971058 | 8.036017 | |||||||
10 | 3 | 37.756759 | 26.485324 | 6618.402481 | 8.016825 | |||||||
10 | 4 | 38.691949 | 25.845170 | 6611.620665 | 8.111596 | |||||||
10 | 5 | 37.549050 | 26.631832 | 6552.416801 | 7.992029 | |||||||
10 | 6 | 39.299740 | 25.445461 | 6609.288931 | 8.073509 | |||||||
10 | 7 | 38.597949 | 25.908113 | 6576.433897 | 8.067608 | |||||||
10 | 8 | 40.288589 | 24.820924 | 6521.219254 | 7.982850 | |||||||
10 | 9 | 37.713304 | 26.515841 | 6615.052223 | 8.041561 | |||||||
4 | 2 | True | 300 | 300 | 10 | 0 | 46.616974 | 21.451414 | 6590.298176 | 7.730275 | ||
10 | 1 | 45.601661 | 21.929026 | 6675.766706 | 7.896870 | |||||||
10 | 2 | 45.557207 | 21.950424 | 6571.399927 | 7.940561 | |||||||
10 | 3 | 44.636282 | 22.403300 | 6588.617086 | 8.052975 | |||||||
10 | 4 | 43.675881 | 22.895932 | 6583.994389 | 7.861435 | |||||||
10 | 5 | 45.446635 | 22.003829 | 6663.607359 | 7.858515 | |||||||
10 | 6 | 45.990554 | 21.743596 | 6600.759268 | 7.935882 | |||||||
10 | 7 | 46.355248 | 21.572530 | 6503.491163 | 7.827282 | |||||||
10 | 8 | 44.395327 | 22.524893 | 6576.805353 | 7.761031 | |||||||
10 | 9 | 45.889164 | 21.791637 | 6550.295115 | 8.018255 | |||||||
8 | 2 | True | 300 | 300 | 10 | 0 | 49.487904 | 20.206958 | 6548.888445 | 6.936729 | ||
10 | 1 | 48.825906 | 20.480931 | 6566.396713 | 6.986946 | |||||||
10 | 2 | 50.300009 | 19.880712 | 6565.106630 | 6.874979 | |||||||
10 | 3 | 50.178603 | 19.928813 | 6559.686184 | 6.937101 | |||||||
10 | 4 | 46.904872 | 21.319747 | 6659.745932 | 6.944045 | |||||||
10 | 5 | 49.049518 | 20.387560 | 6500.623941 | 6.987199 | |||||||
10 | 6 | 50.392320 | 19.844294 | 6513.159513 | 6.693140 | |||||||
10 | 7 | 47.459293 | 21.070689 | 6589.456081 | 6.958291 | |||||||
10 | 8 | 49.403747 | 20.241380 | 6576.894045 | 6.721020 | |||||||
10 | 9 | 47.675954 | 20.974934 | 6514.142036 | 6.808162 | |||||||
16 | 2 | True | 300 | 300 | 10 | 0 | 52.676255 | 18.983886 | 6599.140167 | 6.817013 | ||
10 | 1 | 52.344231 | 19.104302 | 6621.922255 | 6.884761 | |||||||
10 | 2 | 52.629326 | 19.000813 | 6682.018757 | 6.860964 | |||||||
10 | 3 | 52.352235 | 19.101381 | 6650.681973 | 6.515272 | |||||||
10 | 4 | 52.005322 | 19.228801 | 6671.128035 | 6.897494 | |||||||
10 | 5 | 50.304760 | 19.878834 | 6507.030725 | 6.698079 | |||||||
10 | 6 | 51.827640 | 19.294724 | 6568.404913 | 6.520748 | |||||||
10 | 7 | 49.720029 | 20.112619 | 6560.986042 | 6.504893 | |||||||
10 | 8 | 51.525256 | 19.407958 | 6544.950724 | 6.568745 | |||||||
10 | 9 | 51.635946 | 19.366354 | 6619.815350 | 6.623700 | |||||||
32 | 2 | True | 300 | 300 | 10 | 0 | 51.582584 | 19.386388 | 6629.342318 | 6.319094 | ||
10 | 1 | 52.750102 | 18.957309 | 6636.018515 | 6.235145 | |||||||
10 | 2 | 53.658631 | 18.636331 | 6637.416601 | 6.539639 | |||||||
10 | 3 | 52.206575 | 19.154675 | 6632.087469 | 6.554540 | |||||||
10 | 4 | 53.958676 | 18.532701 | 6691.053629 | 6.191995 | |||||||
10 | 5 | 52.312486 | 19.115895 | 6623.284817 | 6.639510 | |||||||
10 | 6 | 53.036880 | 18.854804 | 6683.665991 | 6.238684 | |||||||
10 | 7 | 52.403929 | 19.082539 | 6585.723400 | 6.232236 | |||||||
10 | 8 | 53.319994 | 18.754691 | 6604.930401 | 6.212588 | |||||||
10 | 9 | 50.975810 | 19.617148 | 6513.706923 | 6.610345 | |||||||
ssd-mobilenet-v1-fpn | cpu | 1 | 2 | True | 640 | 640 | 10 | 0 | 4.166774 | 239.993811 | 949.252129 | 9.547591 |
10 | 1 | 4.111962 | 243.192911 | 990.202427 | 9.488583 | |||||||
10 | 2 | 4.142085 | 241.424322 | 1005.813122 | 9.365082 | |||||||
10 | 3 | 4.182889 | 239.069223 | 1031.843662 | 9.510636 | |||||||
10 | 4 | 4.218243 | 237.065554 | 941.507101 | 9.429336 | |||||||
10 | 5 | 4.183807 | 239.016771 | 1013.438463 | 9.552360 | |||||||
10 | 6 | 4.162032 | 240.267277 | 1008.560419 | 9.738922 | |||||||
10 | 7 | 4.249527 | 235.320330 | 1016.711235 | 9.618044 | |||||||
10 | 8 | 4.177964 | 239.351034 | 951.983213 | 9.445429 | |||||||
10 | 9 | 4.193914 | 238.440752 | 976.160049 | 9.563684 | |||||||
2 | 2 | True | 640 | 640 | 10 | 0 | 4.154407 | 240.708232 | 1017.332315 | 8.106768 | ||
10 | 1 | 4.097705 | 244.039059 | 1011.907101 | 7.809579 | |||||||
10 | 2 | 4.065540 | 245.969772 | 1007.675886 | 8.003175 | |||||||
10 | 3 | 4.187782 | 238.789916 | 1001.776695 | 7.879436 | |||||||
10 | 4 | 4.133901 | 241.902232 | 968.447208 | 7.845998 | |||||||
10 | 5 | 4.162819 | 240.221858 | 1012.756824 | 8.244276 | |||||||
10 | 6 | 4.194730 | 238.394380 | 1018.407106 | 8.022308 | |||||||
10 | 7 | 4.155825 | 240.626097 | 1002.189875 | 8.193851 | |||||||
10 | 8 | 4.182516 | 239.090562 | 996.820211 | 7.999599 | |||||||
10 | 9 | 4.185278 | 238.932729 | 927.052975 | 7.790089 | |||||||
4 | 2 | True | 640 | 640 | 10 | 0 | 4.094902 | 244.206071 | 965.651274 | 7.668853 | ||
10 | 1 | 4.117809 | 242.847621 | 978.833675 | 7.734925 | |||||||
10 | 2 | 4.127013 | 242.305994 | 990.135908 | 7.600337 | |||||||
10 | 3 | 4.094468 | 244.231999 | 993.541956 | 7.612795 | |||||||
10 | 4 | 4.099731 | 243.918419 | 965.957642 | 7.927179 | |||||||
10 | 5 | 4.118635 | 242.798865 | 983.108044 | 7.523805 | |||||||
10 | 6 | 4.048905 | 246.980369 | 1011.893272 | 7.682055 | |||||||
10 | 7 | 4.189854 | 238.671780 | 1001.241684 | 7.517993 | |||||||
10 | 8 | 4.120459 | 242.691398 | 988.546610 | 7.618070 | |||||||
10 | 9 | 4.099926 | 243.906856 | 970.993280 | 7.643878 | |||||||
8 | 2 | True | 640 | 640 | 10 | 0 | 3.939119 | 253.863901 | 984.187841 | 6.399423 | ||
10 | 1 | 3.949129 | 253.220409 | 1007.894754 | 6.475702 | |||||||
10 | 2 | 3.952765 | 252.987474 | 980.275393 | 6.470412 | |||||||
10 | 3 | 3.982086 | 251.124680 | 967.080355 | 6.411701 | |||||||
10 | 4 | 3.979674 | 251.276881 | 991.317987 | 6.421462 | |||||||
10 | 5 | 3.939259 | 253.854841 | 985.423326 | 6.594971 | |||||||
10 | 6 | 3.953561 | 252.936542 | 1023.940563 | 6.901354 | |||||||
10 | 7 | 3.965071 | 252.202302 | 985.110283 | 6.592333 | |||||||
10 | 8 | 3.946019 | 253.419966 | 994.375944 | 6.497964 | |||||||
10 | 9 | 3.960012 | 252.524465 | 982.768536 | 6.395921 | |||||||
16 | 2 | True | 640 | 640 | 10 | 0 | 3.885555 | 257.363498 | 1022.043705 | 6.149754 | ||
10 | 1 | 3.900976 | 256.346077 | 1015.346289 | 6.295212 | |||||||
10 | 2 | 3.914565 | 255.456194 | 987.673759 | 6.167620 | |||||||
10 | 3 | 3.918962 | 255.169600 | 943.874836 | 6.149560 | |||||||
10 | 4 | 3.882112 | 257.591739 | 990.517616 | 6.132275 | |||||||
10 | 5 | 3.910913 | 255.694762 | 1012.816429 | 6.346256 | |||||||
10 | 6 | 3.920508 | 255.069003 | 974.900007 | 6.129012 | |||||||
10 | 7 | 3.923843 | 254.852176 | 995.025635 | 6.178208 | |||||||
10 | 8 | 3.905189 | 256.069526 | 963.919640 | 6.140187 | |||||||
10 | 9 | 3.905582 | 256.043792 | 981.600523 | 6.344199 | |||||||
32 | 2 | True | 640 | 640 | 10 | 0 | 3.897739 | 256.559022 | 1403.848410 | 5.851276 | ||
10 | 1 | 3.890113 | 257.061958 | 974.174738 | 6.015714 | |||||||
10 | 2 | 3.886433 | 257.305361 | 985.171795 | 5.890772 | |||||||
10 | 3 | 3.887184 | 257.255651 | 982.946157 | 5.989950 | |||||||
10 | 4 | 3.891006 | 257.002912 | 1027.502298 | 6.099410 | |||||||
10 | 5 | 3.889437 | 257.106610 | 1023.852587 | 6.042928 | |||||||
10 | 6 | 3.881790 | 257.613115 | 982.138157 | 5.939063 | |||||||
10 | 7 | 3.886426 | 257.305816 | 984.569788 | 5.910162 | |||||||
10 | 8 | 3.886651 | 257.290915 | 985.730886 | 5.911052 | |||||||
10 | 9 | 3.895844 | 256.683797 | 1014.714718 | 5.932350 | |||||||
cpu-prebuilt | 1 | 2 | True | 640 | 640 | 10 | 0 | 4.172486 | 239.665270 | 1395.193100 | 9.908676 | |
10 | 1 | 4.087677 | 244.637728 | 909.227133 | 9.484172 | |||||||
10 | 2 | 4.130065 | 242.126942 | 932.307005 | 9.700894 | |||||||
10 | 3 | 4.108261 | 243.412018 | 904.148817 | 9.459496 | |||||||
10 | 4 | 4.124635 | 242.445707 | 911.671877 | 9.546399 | |||||||
10 | 5 | 4.091377 | 244.416475 | 906.635523 | 9.561539 | |||||||
10 | 6 | 4.072824 | 245.529890 | 909.437656 | 9.397030 | |||||||
10 | 7 | 4.075099 | 245.392799 | 901.979446 | 9.731174 | |||||||
10 | 8 | 4.056446 | 246.521235 | 901.348352 | 9.513497 | |||||||
10 | 9 | 4.157077 | 240.553617 | 922.986269 | 9.658337 | |||||||
2 | 2 | True | 640 | 640 | 10 | 0 | 4.089441 | 244.532228 | 907.879114 | 7.840633 | ||
10 | 1 | 4.068966 | 245.762706 | 967.983723 | 8.200467 | |||||||
10 | 2 | 4.014391 | 249.103785 | 923.645258 | 7.966101 | |||||||
10 | 3 | 4.159423 | 240.417957 | 915.006638 | 8.030295 | |||||||
10 | 4 | 4.048118 | 247.028351 | 917.805433 | 7.984757 | |||||||
10 | 5 | 4.084958 | 244.800568 | 942.643404 | 8.256495 | |||||||
10 | 6 | 4.095344 | 244.179726 | 897.751331 | 7.796288 | |||||||
10 | 7 | 4.120690 | 242.677808 | 893.104553 | 8.310497 | |||||||
10 | 8 | 4.147510 | 241.108537 | 908.740520 | 7.971227 | |||||||
10 | 9 | 4.118610 | 242.800355 | 906.265259 | 7.853031 | |||||||
4 | 2 | True | 640 | 640 | 10 | 0 | 4.101861 | 243.791759 | 916.483641 | 7.702053 | ||
10 | 1 | 4.047837 | 247.045517 | 927.080154 | 7.462740 | |||||||
10 | 2 | 4.013608 | 249.152362 | 910.526037 | 7.573068 | |||||||
10 | 3 | 4.050227 | 246.899724 | 905.446291 | 7.483482 | |||||||
10 | 4 | 4.122979 | 242.543101 | 920.054197 | 7.383615 | |||||||
10 | 5 | 4.090524 | 244.467437 | 927.403688 | 7.703304 | |||||||
10 | 6 | 4.065780 | 245.955288 | 907.986641 | 7.302433 | |||||||
10 | 7 | 4.017075 | 248.937368 | 897.381544 | 7.494330 | |||||||
10 | 8 | 4.034593 | 247.856498 | 915.532827 | 7.501543 | |||||||
10 | 9 | 4.059147 | 246.357203 | 917.310238 | 7.793844 | |||||||
8 | 2 | True | 640 | 640 | 10 | 0 | 3.922392 | 254.946470 | 923.279047 | 6.436124 | ||
10 | 1 | 3.914174 | 255.481750 | 906.167507 | 6.409690 | |||||||
10 | 2 | 3.930945 | 254.391760 | 951.775789 | 6.742597 | |||||||
10 | 3 | 3.898218 | 256.527483 | 985.730171 | 6.353289 | |||||||
10 | 4 | 3.938811 | 253.883749 | 967.151880 | 6.462514 | |||||||
10 | 5 | 3.928303 | 254.562825 | 902.591705 | 6.386936 | |||||||
10 | 6 | 3.951163 | 253.090024 | 907.949686 | 6.553531 | |||||||
10 | 7 | 3.932486 | 254.292041 | 918.996096 | 6.339043 | |||||||
10 | 8 | 3.892489 | 256.905049 | 916.304827 | 6.409019 | |||||||
10 | 9 | 3.867488 | 258.565754 | 907.797575 | 6.496862 | |||||||
16 | 2 | True | 640 | 640 | 10 | 0 | 3.854445 | 259.440720 | 921.696901 | 6.182805 | ||
10 | 1 | 3.855517 | 259.368613 | 908.030510 | 6.175518 | |||||||
10 | 2 | 3.869401 | 258.437961 | 929.420471 | 6.223805 | |||||||
10 | 3 | 3.873543 | 258.161590 | 901.366949 | 6.210037 | |||||||
10 | 4 | 3.879507 | 257.764712 | 906.081915 | 6.112203 | |||||||
10 | 5 | 3.869912 | 258.403823 | 907.177687 | 6.196164 | |||||||
10 | 6 | 3.873590 | 258.158445 | 909.431458 | 6.212786 | |||||||
10 | 7 | 3.872074 | 258.259520 | 913.040638 | 6.348215 | |||||||
10 | 8 | 3.856121 | 259.327963 | 935.850382 | 6.444044 | |||||||
10 | 9 | 3.878208 | 257.851034 | 918.668747 | 6.283529 | |||||||
32 | 2 | True | 640 | 640 | 10 | 0 | 3.864554 | 258.762047 | 922.457933 | 6.037913 | ||
10 | 1 | 3.855414 | 259.375550 | 920.516729 | 5.923584 | |||||||
10 | 2 | 3.850972 | 259.674720 | 915.154219 | 6.017704 | |||||||
10 | 3 | 3.867050 | 258.595072 | 1005.593061 | 6.051864 | |||||||
10 | 4 | 3.855459 | 259.372473 | 920.384884 | 5.902320 | |||||||
10 | 5 | 3.839192 | 260.471471 | 953.571320 | 6.019197 | |||||||
10 | 6 | 3.864190 | 258.786455 | 967.902422 | 6.094638 | |||||||
10 | 7 | 3.854052 | 259.467207 | 906.492949 | 5.923774 | |||||||
10 | 8 | 3.845433 | 260.048725 | 901.516914 | 6.269075 | |||||||
10 | 9 | 3.859637 | 259.091735 | 904.022455 | 6.338898 | |||||||
cuda | 1 | 2 | True | 640 | 640 | 10 | 0 | 19.573027 | 51.090717 | 908.805370 | 9.612441 | |
10 | 1 | 19.350080 | 51.679373 | 902.155399 | 9.599686 | |||||||
10 | 2 | 19.189576 | 52.111626 | 919.715643 | 9.597778 | |||||||
10 | 3 | 19.237015 | 51.983118 | 907.780409 | 9.479403 | |||||||
10 | 4 | 19.720825 | 50.707817 | 900.603056 | 9.435534 | |||||||
10 | 5 | 18.962877 | 52.734613 | 913.372993 | 9.566069 | |||||||
10 | 6 | 18.795895 | 53.203106 | 927.624464 | 9.580970 | |||||||
10 | 7 | 19.962610 | 50.093651 | 904.953718 | 9.366274 | |||||||
10 | 8 | 18.800192 | 53.190947 | 904.262066 | 9.561539 | |||||||
10 | 9 | 19.563624 | 51.115274 | 909.379244 | 9.578466 | |||||||
2 | 2 | True | 640 | 640 | 10 | 0 | 21.948273 | 45.561671 | 925.212383 | 7.884979 | ||
10 | 1 | 22.139722 | 45.167685 | 904.875040 | 7.715762 | |||||||
10 | 2 | 22.356327 | 44.730067 | 940.769911 | 7.929206 | |||||||
10 | 3 | 22.583168 | 44.280767 | 930.185318 | 7.603943 | |||||||
10 | 4 | 22.491797 | 44.460654 | 929.051876 | 7.873476 | |||||||
10 | 5 | 22.584931 | 44.277310 | 921.633244 | 7.705450 | |||||||
10 | 6 | 22.455852 | 44.531822 | 924.786568 | 7.706344 | |||||||
10 | 7 | 21.845675 | 45.775652 | 936.403036 | 7.775545 | |||||||
10 | 8 | 22.369383 | 44.703960 | 920.533895 | 7.923305 | |||||||
10 | 9 | 22.693871 | 44.064760 | 945.333481 | 7.853866 | |||||||
4 | 2 | True | 640 | 640 | 10 | 0 | 24.841187 | 40.255725 | 909.008265 | 7.411778 | ||
10 | 1 | 24.960672 | 40.063024 | 920.446873 | 7.487774 | |||||||
10 | 2 | 24.869909 | 40.209234 | 909.488440 | 7.314205 | |||||||
10 | 3 | 24.831076 | 40.272117 | 921.611786 | 7.309943 | |||||||
10 | 4 | 25.481373 | 39.244354 | 910.260439 | 7.448256 | |||||||
10 | 5 | 24.773730 | 40.365338 | 923.399687 | 7.429630 | |||||||
10 | 6 | 24.993618 | 40.010214 | 906.753302 | 7.403255 | |||||||
10 | 7 | 25.702873 | 38.906157 | 928.272963 | 7.490605 | |||||||
10 | 8 | 25.486986 | 39.235711 | 920.787573 | 7.463127 | |||||||
10 | 9 | 24.908494 | 40.146947 | 914.773226 | 7.400990 | |||||||
8 | 2 | True | 640 | 640 | 10 | 0 | 25.328554 | 39.481133 | 927.286863 | 6.389275 | ||
10 | 1 | 24.961025 | 40.062457 | 915.333271 | 6.609529 | |||||||
10 | 2 | 25.891824 | 38.622230 | 904.504776 | 6.402537 | |||||||
10 | 3 | 24.953284 | 40.074885 | 920.495033 | 6.543800 | |||||||
10 | 4 | 26.049211 | 38.388878 | 914.555073 | 6.447956 | |||||||
10 | 5 | 25.514098 | 39.194018 | 915.846586 | 6.402671 | |||||||
10 | 6 | 25.208824 | 39.668649 | 923.800230 | 6.348789 | |||||||
10 | 7 | 25.849120 | 38.686037 | 913.218498 | 6.303921 | |||||||
10 | 8 | 25.196898 | 39.687425 | 910.559893 | 6.518662 | |||||||
10 | 9 | 25.084481 | 39.865285 | 912.072182 | 6.638706 | |||||||
16 | 2 | True | 640 | 640 | 10 | 0 | 26.573337 | 37.631705 | 907.567739 | 6.137401 | ||
10 | 1 | 26.623159 | 37.561283 | 924.509764 | 6.364942 | |||||||
10 | 2 | 27.052281 | 36.965460 | 919.187307 | 6.238095 | |||||||
10 | 3 | 27.121224 | 36.871493 | 923.502922 | 6.373614 | |||||||
10 | 4 | 26.488891 | 37.751675 | 913.130999 | 6.189905 | |||||||
10 | 5 | 26.545493 | 37.671179 | 917.901754 | 6.296627 | |||||||
10 | 6 | 26.711612 | 37.436903 | 928.848267 | 6.250955 | |||||||
10 | 7 | 26.795325 | 37.319943 | 956.294537 | 6.157666 | |||||||
10 | 8 | 26.468143 | 37.781268 | 915.115356 | 6.229423 | |||||||
10 | 9 | 26.731327 | 37.409291 | 904.491425 | 6.205052 | |||||||
32 | 2 | True | 640 | 640 | 10 | 0 | 26.939688 | 37.119955 | 918.742418 | 6.182730 | ||
10 | 1 | 27.054648 | 36.962226 | 914.777994 | 5.869318 | |||||||
10 | 2 | 27.190304 | 36.777817 | 933.827639 | 5.975340 | |||||||
10 | 3 | 27.137109 | 36.849909 | 926.579714 | 6.142229 | |||||||
10 | 4 | 26.749159 | 37.384354 | 918.555498 | 5.963236 | |||||||
10 | 5 | 26.429376 | 37.836686 | 930.832863 | 5.858600 | |||||||
10 | 6 | 26.825701 | 37.277684 | 923.490524 | 5.952094 | |||||||
10 | 7 | 26.777069 | 37.345387 | 920.230150 | 5.977575 | |||||||
10 | 8 | 26.844947 | 37.250958 | 925.060749 | 5.984571 | |||||||
10 | 9 | 26.654104 | 37.517674 | 928.603172 | 5.865470 | |||||||
tensorrt | 1 | 2 | True | 640 | 640 | 10 | 0 | 19.431928 | 51.461697 | 19697.484970 | 9.247065 | |
10 | 1 | 20.250110 | 49.382448 | 19534.241676 | 9.296894 | |||||||
10 | 2 | 19.502223 | 51.276207 | 19808.818340 | 9.350300 | |||||||
10 | 3 | 20.191522 | 49.525738 | 19857.414722 | 9.371519 | |||||||
10 | 4 | 19.747938 | 50.638199 | 19568.608046 | 9.309173 | |||||||
10 | 5 | 20.043123 | 49.892426 | 19725.984812 | 9.344578 | |||||||
10 | 6 | 19.708779 | 50.738811 | 19778.983593 | 9.471059 | |||||||
10 | 7 | 19.915217 | 50.212860 | 19713.012457 | 9.250283 | |||||||
10 | 8 | 19.488449 | 51.312447 | 19635.494947 | 9.330153 | |||||||
10 | 9 | 19.188347 | 52.114964 | 19832.072496 | 9.377003 | |||||||
2 | 2 | True | 640 | 640 | 10 | 0 | 22.928527 | 43.613791 | 21607.429504 | 7.562697 | ||
10 | 1 | 22.794449 | 43.870330 | 21589.494705 | 7.522821 | |||||||
10 | 2 | 22.722702 | 44.008851 | 21722.892046 | 7.638097 | |||||||
10 | 3 | 23.202242 | 43.099284 | 21588.389874 | 7.699311 | |||||||
10 | 4 | 22.835838 | 43.790817 | 21966.397762 | 7.536530 | |||||||
10 | 5 | 22.663828 | 44.123173 | 21663.414240 | 7.575333 | |||||||
10 | 6 | 22.792096 | 43.874860 | 21542.892933 | 7.686675 | |||||||
10 | 7 | 22.051724 | 45.347929 | 21649.904966 | 7.707298 | |||||||
10 | 8 | 22.281979 | 44.879317 | 21570.734739 | 7.615447 | |||||||
10 | 9 | 22.871202 | 43.723106 | 21798.259735 | 7.703841 | |||||||
4 | 2 | True | 640 | 640 | 10 | 0 | 25.176272 | 39.719939 | 11973.683357 | 7.282495 | ||
10 | 1 | 24.944937 | 40.088296 | 11978.130341 | 7.464558 | |||||||
10 | 2 | 25.543018 | 39.149642 | 12047.371149 | 7.466644 | |||||||
10 | 3 | 25.446628 | 39.297938 | 12042.906523 | 7.524014 | |||||||
10 | 4 | 25.667953 | 38.959086 | 12023.584127 | 7.380068 | |||||||
10 | 5 | 25.583838 | 39.087176 | 12001.087666 | 7.340968 | |||||||
10 | 6 | 25.606877 | 39.052010 | 11880.704880 | 7.398009 | |||||||
10 | 7 | 25.328611 | 39.481044 | 12004.886150 | 7.490426 | |||||||
10 | 8 | 25.458714 | 39.279282 | 12014.826536 | 7.544011 | |||||||
10 | 9 | 25.397551 | 39.373875 | 12006.185532 | 7.362038 | |||||||
8 | 2 | True | 640 | 640 | 10 | 0 | 25.097521 | 39.844573 | 13302.614450 | 6.381348 | ||
10 | 1 | 25.150250 | 39.761037 | 13281.148195 | 6.316394 | |||||||
10 | 2 | 25.261242 | 39.586335 | 13336.726189 | 6.398126 | |||||||
10 | 3 | 25.413016 | 39.349914 | 13257.743835 | 6.481037 | |||||||
10 | 4 | 25.249704 | 39.604425 | 13518.876791 | 6.493971 | |||||||
10 | 5 | 25.795009 | 38.767189 | 13310.051680 | 6.457239 | |||||||
10 | 6 | 25.376385 | 39.406717 | 13284.626007 | 6.421357 | |||||||
10 | 7 | 25.492059 | 39.227903 | 13395.771027 | 6.501481 | |||||||
10 | 8 | 25.256127 | 39.594352 | 13550.631762 | 6.353378 | |||||||
10 | 9 | 25.049351 | 39.921194 | 13315.902948 | 6.421164 | |||||||
16 | 2 | True | 640 | 640 | 10 | 0 | 25.640180 | 39.001286 | 16542.674780 | 6.298348 | ||
10 | 1 | 25.066698 | 39.893568 | 16451.378345 | 6.477304 | |||||||
10 | 2 | 25.613591 | 39.041772 | 16377.570391 | 6.301396 | |||||||
10 | 3 | 25.727941 | 38.868248 | 16550.896883 | 6.395690 | |||||||
10 | 4 | 25.279684 | 39.557457 | 16486.351967 | 6.212004 | |||||||
10 | 5 | 26.107898 | 38.302585 | 16543.775082 | 6.223150 | |||||||
10 | 6 | 25.412680 | 39.350435 | 16419.026852 | 6.312534 | |||||||
10 | 7 | 25.515922 | 39.191216 | 16384.063244 | 6.471224 | |||||||
10 | 8 | 25.295892 | 39.532110 | 16443.823814 | 6.333791 | |||||||
10 | 9 | 25.614960 | 39.039686 | 16459.635496 | 6.241322 | |||||||
32 | 2 | True | 640 | 640 | 10 | 0 | 25.498979 | 39.217256 | 22580.085278 | 5.934775 | ||
10 | 1 | 25.200389 | 39.681926 | 22651.859522 | 5.900986 | |||||||
10 | 2 | 25.942776 | 38.546376 | 22777.650595 | 5.904812 | |||||||
10 | 3 | 25.432211 | 39.320216 | 22732.622623 | 5.968172 | |||||||
10 | 4 | 25.543134 | 39.149463 | 22682.816267 | 6.100923 | |||||||
10 | 5 | 25.276280 | 39.562784 | 22743.459463 | 6.045006 | |||||||
10 | 6 | 25.224363 | 39.644212 | 22797.020435 | 5.873557 | |||||||
10 | 7 | 25.824476 | 38.722955 | 22711.929560 | 6.002318 | |||||||
10 | 8 | 25.430418 | 39.322987 | 22762.054443 | 6.018624 | |||||||
10 | 9 | 25.681106 | 38.939133 | 22828.942776 | 5.862597 | |||||||
tensorrt-dynamic | 1 | 2 | True | 640 | 640 | 10 | 0 | 23.651334 | 42.280912 | 6379.939556 | 9.138942 | |
10 | 1 | 22.586938 | 44.273376 | 6337.580919 | 9.437680 | |||||||
10 | 2 | 22.947532 | 43.577671 | 6281.933784 | 9.322882 | |||||||
10 | 3 | 22.223597 | 44.997215 | 6375.229359 | 9.170175 | |||||||
10 | 4 | 23.297677 | 42.922735 | 6335.123301 | 9.294748 | |||||||
10 | 5 | 23.255179 | 43.001175 | 6332.339287 | 9.318829 | |||||||
10 | 6 | 23.215533 | 43.074608 | 6294.281244 | 9.399056 | |||||||
10 | 7 | 23.157341 | 43.182850 | 6345.356703 | 9.421587 | |||||||
10 | 8 | 23.110259 | 43.270826 | 6355.256796 | 9.445548 | |||||||
10 | 9 | 22.905425 | 43.657780 | 6455.956936 | 9.447217 | |||||||
2 | 2 | True | 640 | 640 | 10 | 0 | 25.801892 | 38.756847 | 6311.048508 | 7.634759 | ||
10 | 1 | 26.239656 | 38.110256 | 6313.688993 | 7.738590 | |||||||
10 | 2 | 25.808005 | 38.747668 | 6355.959177 | 7.593751 | |||||||
10 | 3 | 26.471672 | 37.776232 | 6325.766563 | 7.632911 | |||||||
10 | 4 | 26.796898 | 37.317753 | 6292.751551 | 7.551193 | |||||||
10 | 5 | 26.432468 | 37.832260 | 6369.322538 | 7.606745 | |||||||
10 | 6 | 26.197535 | 38.171530 | 6398.904562 | 8.122444 | |||||||
10 | 7 | 26.126794 | 38.274884 | 6403.906345 | 7.721722 | |||||||
10 | 8 | 26.200808 | 38.166761 | 6384.660721 | 7.561564 | |||||||
10 | 9 | 27.021237 | 37.007928 | 6344.237089 | 7.621288 | |||||||
4 | 2 | True | 640 | 640 | 10 | 0 | 29.037478 | 34.438252 | 6343.791246 | 7.474542 | ||
10 | 1 | 28.185254 | 35.479546 | 6421.319008 | 7.432252 | |||||||
10 | 2 | 29.108413 | 34.354329 | 6373.960495 | 7.496566 | |||||||
10 | 3 | 28.662588 | 34.888685 | 6463.953733 | 7.437229 | |||||||
10 | 4 | 28.786274 | 34.738779 | 6337.746382 | 7.398278 | |||||||
10 | 5 | 28.889127 | 34.615099 | 6300.127268 | 7.326245 | |||||||
10 | 6 | 27.752679 | 36.032557 | 6315.848827 | 7.420301 | |||||||
10 | 7 | 28.809556 | 34.710705 | 6358.988285 | 7.201135 | |||||||
10 | 8 | 28.539864 | 35.038710 | 6364.130735 | 7.515818 | |||||||
10 | 9 | 29.355791 | 34.064829 | 6352.153301 | 7.515222 | |||||||
8 | 2 | True | 640 | 640 | 10 | 0 | 29.055934 | 34.416378 | 6499.320030 | 6.336465 | ||
10 | 1 | 28.686921 | 34.859091 | 6326.475620 | 6.397486 | |||||||
10 | 2 | 29.407272 | 34.005195 | 6237.746716 | 6.408036 | |||||||
10 | 3 | 28.364759 | 35.255015 | 6369.799614 | 6.522298 | |||||||
10 | 4 | 28.367253 | 35.251915 | 6358.793736 | 6.287098 | |||||||
10 | 5 | 28.584551 | 34.983933 | 6367.268085 | 6.484717 | |||||||
10 | 6 | 28.227340 | 35.426646 | 6397.254944 | 6.266743 | |||||||
10 | 7 | 28.760909 | 34.769416 | 6262.703419 | 6.326750 | |||||||
10 | 8 | 28.986106 | 34.499288 | 6388.038158 | 6.303608 | |||||||
10 | 9 | 28.658377 | 34.893811 | 6389.622927 | 6.511480 | |||||||
16 | 2 | True | 640 | 640 | 10 | 0 | 29.197202 | 34.249857 | 6348.584414 | 6.167918 | ||
10 | 1 | 28.978346 | 34.508526 | 6252.276421 | 6.100789 | |||||||
10 | 2 | 29.110219 | 34.352198 | 6358.824015 | 6.137222 | |||||||
10 | 3 | 28.091987 | 35.597339 | 6363.001823 | 6.313227 | |||||||
10 | 4 | 28.525913 | 35.055846 | 6329.951763 | 6.257400 | |||||||
10 | 5 | 28.889649 | 34.614474 | 6311.621428 | 6.251894 | |||||||
10 | 6 | 28.824578 | 34.692615 | 6385.085344 | 6.299280 | |||||||
10 | 7 | 28.331457 | 35.296455 | 6438.660860 | 6.476067 | |||||||
10 | 8 | 28.771859 | 34.756184 | 6343.760490 | 6.229334 | |||||||
10 | 9 | 28.315033 | 35.316929 | 6278.670788 | 6.128475 | |||||||
32 | 2 | True | 640 | 640 | 10 | 0 | 28.655912 | 34.896813 | 6336.538076 | 5.954769 | ||
10 | 1 | 28.375175 | 35.242073 | 6304.973125 | 5.921368 | |||||||
10 | 2 | 28.241969 | 35.408296 | 6316.627264 | 5.957868 | |||||||
10 | 3 | 28.419750 | 35.186797 | 6391.951561 | 5.892187 | |||||||
10 | 4 | 28.534015 | 35.045892 | 6357.141733 | 5.938355 | |||||||
10 | 5 | 28.553780 | 35.021633 | 6352.425098 | 5.932610 | |||||||
10 | 6 | 28.431785 | 35.171904 | 6358.306885 | 6.077591 | |||||||
10 | 7 | 28.640527 | 34.915559 | 6339.262486 | 5.921669 | |||||||
10 | 8 | 28.113447 | 35.570167 | 6322.747946 | 5.909916 | |||||||
10 | 9 | 28.453580 | 35.144962 | 6266.034603 | 5.850889 | |||||||
ssd-mobilenet-v1-non-quantized-mlperf | cpu | 1 | 2 | True | 300 | 300 | 10 | 0 | 44.508983 | 22.467375 | 855.396509 | 10.349393 |
10 | 1 | 45.153936 | 22.146463 | 860.897064 | 10.306597 | |||||||
10 | 2 | 44.406255 | 22.519350 | 849.796295 | 10.158300 | |||||||
10 | 3 | 42.634573 | 23.455143 | 790.455103 | 10.026693 | |||||||
10 | 4 | 45.146160 | 22.150278 | 862.575769 | 10.165095 | |||||||
10 | 5 | 44.147315 | 22.651434 | 855.742931 | 10.263205 | |||||||
10 | 6 | 42.617678 | 23.464441 | 794.686079 | 9.904742 | |||||||
10 | 7 | 42.135600 | 23.732901 | 842.722654 | 9.894967 | |||||||
10 | 8 | 44.101361 | 22.675037 | 891.747236 | 11.799097 | |||||||
10 | 9 | 43.114903 | 23.193836 | 847.278595 | 10.382295 | |||||||
2 | 2 | True | 300 | 300 | 10 | 0 | 54.922271 | 18.207550 | 844.219685 | 8.467555 | ||
10 | 1 | 53.679877 | 18.628955 | 861.808300 | 8.341193 | |||||||
10 | 2 | 54.998971 | 18.182158 | 838.324308 | 8.305073 | |||||||
10 | 3 | 58.247346 | 17.168164 | 824.517250 | 8.350492 | |||||||
10 | 4 | 57.007965 | 17.541409 | 823.447227 | 8.308351 | |||||||
10 | 5 | 56.391729 | 17.733097 | 875.511646 | 8.492947 | |||||||
10 | 6 | 56.694724 | 17.638326 | 816.074848 | 8.246958 | |||||||
10 | 7 | 56.834928 | 17.594814 | 866.644382 | 8.589089 | |||||||
10 | 8 | 55.320324 | 18.076539 | 815.828323 | 8.362293 | |||||||
10 | 9 | 53.852872 | 18.569112 | 844.886780 | 8.561969 | |||||||
4 | 2 | True | 300 | 300 | 10 | 0 | 63.342040 | 15.787303 | 855.436325 | 7.863492 | ||
10 | 1 | 62.332221 | 16.043067 | 844.418526 | 8.021593 | |||||||
10 | 2 | 63.359024 | 15.783072 | 848.405600 | 7.992387 | |||||||
10 | 3 | 65.518852 | 15.262783 | 854.447126 | 7.989645 | |||||||
10 | 4 | 62.017936 | 16.124368 | 849.282026 | 8.039773 | |||||||
10 | 5 | 62.335232 | 16.042292 | 843.133688 | 7.888258 | |||||||
10 | 6 | 67.212371 | 14.878213 | 864.814758 | 8.324951 | |||||||
10 | 7 | 63.548616 | 15.735984 | 859.345913 | 8.412153 | |||||||
10 | 8 | 65.048391 | 15.373170 | 838.207245 | 8.437037 | |||||||
10 | 9 | 61.140344 | 16.355813 | 828.130722 | 8.056521 | |||||||
8 | 2 | True | 300 | 300 | 10 | 0 | 70.252965 | 14.234275 | 811.311960 | 6.807566 | ||
10 | 1 | 69.835522 | 14.319360 | 837.511301 | 6.794080 | |||||||
10 | 2 | 70.439083 | 14.196664 | 808.301926 | 6.772205 | |||||||
10 | 3 | 66.213525 | 15.102655 | 833.750248 | 6.830335 | |||||||
10 | 4 | 71.619763 | 13.962626 | 853.405714 | 6.823197 | |||||||
10 | 5 | 68.943308 | 14.504671 | 809.007645 | 7.050350 | |||||||
10 | 6 | 70.880411 | 14.108270 | 868.093491 | 7.027805 | |||||||
10 | 7 | 70.659058 | 14.152467 | 850.801706 | 6.897926 | |||||||
10 | 8 | 68.717542 | 14.552325 | 820.596933 | 6.741554 | |||||||
10 | 9 | 70.115999 | 14.262080 | 829.351425 | 6.841555 | |||||||
16 | 2 | True | 300 | 300 | 10 | 0 | 68.719301 | 14.551952 | 781.180143 | 6.951325 | ||
10 | 1 | 69.414681 | 14.406174 | 863.272190 | 6.765753 | |||||||
10 | 2 | 67.408630 | 14.834896 | 849.275351 | 6.513953 | |||||||
10 | 3 | 66.561198 | 15.023768 | 852.967024 | 6.759889 | |||||||
10 | 4 | 68.436393 | 14.612108 | 866.723061 | 6.660096 | |||||||
10 | 5 | 68.497095 | 14.599159 | 839.836121 | 6.589592 | |||||||
10 | 6 | 70.165043 | 14.252111 | 851.131439 | 6.539963 | |||||||
10 | 7 | 68.609000 | 14.575347 | 826.849222 | 7.227622 | |||||||
10 | 8 | 66.593960 | 15.016377 | 862.487555 | 6.580189 | |||||||
10 | 9 | 69.750526 | 14.336810 | 842.926502 | 7.111885 | |||||||
32 | 2 | True | 300 | 300 | 10 | 0 | 66.393080 | 15.061811 | 1078.144073 | 6.210353 | ||
10 | 1 | 66.788014 | 14.972746 | 863.686085 | 6.306849 | |||||||
10 | 2 | 66.606914 | 15.013456 | 870.333433 | 6.739758 | |||||||
10 | 3 | 64.867184 | 15.416116 | 871.635437 | 6.371699 | |||||||
10 | 4 | 66.392686 | 15.061900 | 851.468325 | 6.762244 | |||||||
10 | 5 | 66.775919 | 14.975458 | 860.826015 | 6.418712 | |||||||
10 | 6 | 67.615711 | 14.789462 | 853.632450 | 6.495692 | |||||||
10 | 7 | 66.320938 | 15.078194 | 867.979050 | 6.417651 | |||||||
10 | 8 | 66.948122 | 14.936939 | 868.599415 | 6.417613 | |||||||
10 | 9 | 66.927491 | 14.941543 | 862.969875 | 6.263901 | |||||||
cpu-prebuilt | 1 | 2 | True | 300 | 300 | 10 | 0 | 40.713888 | 24.561644 | 1037.388802 | 9.943485 | |
10 | 1 | 42.277029 | 23.653507 | 771.442175 | 10.058641 | |||||||
10 | 2 | 42.541600 | 23.506403 | 780.729771 | 10.006428 | |||||||
10 | 3 | 44.113884 | 22.668600 | 790.134907 | 10.029793 | |||||||
10 | 4 | 43.597568 | 22.937059 | 765.999556 | 9.960651 | |||||||
10 | 5 | 42.141950 | 23.729324 | 774.374962 | 10.036230 | |||||||
10 | 6 | 42.938351 | 23.289204 | 772.964001 | 10.028243 | |||||||
10 | 7 | 44.268462 | 22.589445 | 785.434484 | 9.983778 | |||||||
10 | 8 | 44.407195 | 22.518873 | 779.783487 | 9.913445 | |||||||
10 | 9 | 43.708879 | 22.878647 | 792.213917 | 9.917259 | |||||||
2 | 2 | True | 300 | 300 | 10 | 0 | 55.870046 | 17.898679 | 777.980089 | 8.077025 | ||
10 | 1 | 56.983181 | 17.549038 | 773.367167 | 8.310854 | |||||||
10 | 2 | 55.902438 | 17.888308 | 772.530079 | 8.320510 | |||||||
10 | 3 | 53.071630 | 18.842459 | 771.639109 | 8.308947 | |||||||
10 | 4 | 55.269296 | 18.093228 | 764.454842 | 8.248508 | |||||||
10 | 5 | 53.726978 | 18.612623 | 780.973673 | 7.923067 | |||||||
10 | 6 | 57.128707 | 17.504334 | 774.303675 | 8.177876 | |||||||
10 | 7 | 55.807601 | 17.918706 | 771.489859 | 8.307040 | |||||||
10 | 8 | 50.296541 | 19.882083 | 766.900301 | 8.293748 | |||||||
10 | 9 | 55.417903 | 18.044710 | 764.200687 | 8.201241 | |||||||
4 | 2 | True | 300 | 300 | 10 | 0 | 62.462410 | 16.009629 | 774.709702 | 8.008301 | ||
10 | 1 | 63.380805 | 15.777647 | 774.232388 | 8.020818 | |||||||
10 | 2 | 65.092304 | 15.362799 | 768.320560 | 7.854253 | |||||||
10 | 3 | 61.739730 | 16.197026 | 795.464516 | 8.208185 | |||||||
10 | 4 | 61.302533 | 16.312540 | 909.101248 | 8.582771 | |||||||
10 | 5 | 63.020355 | 15.867889 | 763.962030 | 7.897943 | |||||||
10 | 6 | 63.541877 | 15.737653 | 767.083645 | 7.900655 | |||||||
10 | 7 | 63.157479 | 15.833437 | 760.612011 | 7.863700 | |||||||
10 | 8 | 63.071292 | 15.855074 | 794.938564 | 7.943928 | |||||||
10 | 9 | 62.629362 | 15.966952 | 766.959667 | 8.274227 | |||||||
8 | 2 | True | 300 | 300 | 10 | 0 | 68.078713 | 14.688879 | 777.205944 | 6.846160 | ||
10 | 1 | 67.215602 | 14.877498 | 785.662174 | 6.964460 | |||||||
10 | 2 | 69.126814 | 14.466166 | 762.176514 | 6.857082 | |||||||
10 | 3 | 70.328355 | 14.219016 | 797.222376 | 7.128149 | |||||||
10 | 4 | 67.411000 | 14.834374 | 767.273903 | 6.741390 | |||||||
10 | 5 | 67.367691 | 14.843911 | 763.527870 | 6.913438 | |||||||
10 | 6 | 68.967114 | 14.499664 | 763.197184 | 6.917983 | |||||||
10 | 7 | 66.953933 | 14.935642 | 763.759375 | 6.836981 | |||||||
10 | 8 | 68.047235 | 14.695674 | 804.507256 | 6.786123 | |||||||
10 | 9 | 62.645965 | 15.962720 | 763.679981 | 6.918207 | |||||||
16 | 2 | True | 300 | 300 | 10 | 0 | 66.415092 | 15.056819 | 788.475513 | 6.619506 | ||
10 | 1 | 67.211429 | 14.878422 | 829.724312 | 6.628186 | |||||||
10 | 2 | 65.238921 | 15.328273 | 779.192448 | 6.518036 | |||||||
10 | 3 | 65.852529 | 15.185446 | 767.430544 | 6.868519 | |||||||
10 | 4 | 66.074143 | 15.134513 | 788.130522 | 6.531455 | |||||||
10 | 5 | 67.154865 | 14.890954 | 771.184921 | 6.687127 | |||||||
10 | 6 | 67.007950 | 14.923602 | 773.524284 | 6.542481 | |||||||
10 | 7 | 67.325045 | 14.853314 | 769.742727 | 7.126704 | |||||||
10 | 8 | 64.996478 | 15.385449 | 767.860651 | 6.565034 | |||||||
10 | 9 | 66.780704 | 14.974385 | 764.333487 | 6.552696 | |||||||
32 | 2 | True | 300 | 300 | 10 | 0 | 65.663865 | 15.229076 | 788.587332 | 6.262325 | ||
10 | 1 | 64.805796 | 15.430719 | 771.837950 | 6.273981 | |||||||
10 | 2 | 66.753900 | 14.980398 | 787.343979 | 6.266356 | |||||||
10 | 3 | 65.936383 | 15.166134 | 763.461351 | 6.200690 | |||||||
10 | 4 | 64.695433 | 15.457042 | 775.409937 | 6.465737 | |||||||
10 | 5 | 66.763397 | 14.978267 | 781.033039 | 6.326370 | |||||||
10 | 6 | 64.756425 | 15.442483 | 768.030882 | 6.328046 | |||||||
10 | 7 | 64.535759 | 15.495285 | 779.752254 | 6.213501 | |||||||
10 | 8 | 65.751136 | 15.208863 | 764.954567 | 6.244205 | |||||||
10 | 9 | 65.092904 | 15.362658 | 775.216103 | 6.226167 | |||||||
cuda | 1 | 2 | True | 300 | 300 | 10 | 0 | 34.838148 | 28.704166 | 781.345367 | 10.071874 | |
10 | 1 | 35.993341 | 27.782917 | 783.009768 | 9.917855 | |||||||
10 | 2 | 35.707752 | 28.005123 | 779.697180 | 9.979963 | |||||||
10 | 3 | 34.500292 | 28.985262 | 784.879208 | 10.042787 | |||||||
10 | 4 | 35.513950 | 28.157949 | 774.436474 | 9.806156 | |||||||
10 | 5 | 33.792875 | 29.592037 | 778.587103 | 9.847999 | |||||||
10 | 6 | 35.608320 | 28.083324 | 777.881622 | 9.941220 | |||||||
10 | 7 | 32.425756 | 30.839682 | 786.830187 | 10.071516 | |||||||
10 | 8 | 33.300020 | 30.030012 | 774.903297 | 9.952307 | |||||||
10 | 9 | 35.324322 | 28.309107 | 770.522356 | 9.963036 | |||||||
2 | 2 | True | 300 | 300 | 10 | 0 | 44.507330 | 22.468209 | 778.796196 | 8.328557 | ||
10 | 1 | 43.788049 | 22.837281 | 774.612427 | 8.106649 | |||||||
10 | 2 | 44.823391 | 22.309780 | 772.593975 | 8.289516 | |||||||
10 | 3 | 44.332097 | 22.557020 | 776.311636 | 8.288622 | |||||||
10 | 4 | 45.798845 | 21.834612 | 771.892548 | 8.101702 | |||||||
10 | 5 | 42.399256 | 23.585320 | 779.415607 | 8.286357 | |||||||
10 | 6 | 45.019444 | 22.212625 | 780.917883 | 8.302510 | |||||||
10 | 7 | 43.681111 | 22.893190 | 786.888838 | 8.253455 | |||||||
10 | 8 | 45.360991 | 22.045374 | 776.494265 | 8.383989 | |||||||
10 | 9 | 41.860157 | 23.889065 | 766.506195 | 8.248746 | |||||||
4 | 2 | True | 300 | 300 | 10 | 0 | 48.156008 | 20.765841 | 777.790785 | 8.004785 | ||
10 | 1 | 45.749264 | 21.858275 | 765.287399 | 7.831812 | |||||||
10 | 2 | 51.807275 | 19.302309 | 790.815353 | 7.882565 | |||||||
10 | 3 | 49.348527 | 20.264030 | 774.976254 | 8.005470 | |||||||
10 | 4 | 48.305475 | 20.701587 | 773.345232 | 7.986993 | |||||||
10 | 5 | 46.588107 | 21.464705 | 773.250103 | 7.926434 | |||||||
10 | 6 | 48.916446 | 20.443022 | 775.005817 | 7.983893 | |||||||
10 | 7 | 47.273613 | 21.153450 | 782.892227 | 8.123457 | |||||||
10 | 8 | 47.400630 | 21.096766 | 774.888039 | 8.026481 | |||||||
10 | 9 | 47.832268 | 20.906389 | 785.664797 | 7.982075 | |||||||
8 | 2 | True | 300 | 300 | 10 | 0 | 51.164556 | 19.544780 | 776.380301 | 6.983578 | ||
10 | 1 | 51.929225 | 19.256979 | 781.573534 | 6.825358 | |||||||
10 | 2 | 53.323468 | 18.753469 | 766.869307 | 6.804869 | |||||||
10 | 3 | 50.549466 | 19.782603 | 774.079561 | 6.917417 | |||||||
10 | 4 | 50.507084 | 19.799203 | 778.929710 | 6.971538 | |||||||
10 | 5 | 51.109379 | 19.565880 | 777.666569 | 6.716475 | |||||||
10 | 6 | 51.273465 | 19.503266 | 781.795979 | 6.735116 | |||||||
10 | 7 | 53.648636 | 18.639803 | 786.628246 | 6.750897 | |||||||
10 | 8 | 52.151825 | 19.174784 | 781.433582 | 7.006764 | |||||||
10 | 9 | 51.116153 | 19.563287 | 769.179583 | 6.954193 | |||||||
16 | 2 | True | 300 | 300 | 10 | 0 | 50.197783 | 19.921198 | 792.678595 | 6.564252 | ||
10 | 1 | 55.402394 | 18.049762 | 781.792879 | 6.630279 | |||||||
10 | 2 | 54.092962 | 18.486694 | 793.374062 | 6.697290 | |||||||
10 | 3 | 52.851113 | 18.921077 | 785.227776 | 6.510057 | |||||||
10 | 4 | 52.790747 | 18.942714 | 785.464764 | 6.560571 | |||||||
10 | 5 | 50.150667 | 19.939914 | 790.877581 | 6.897539 | |||||||
10 | 6 | 52.605480 | 19.009426 | 783.695459 | 6.516472 | |||||||
10 | 7 | 52.157418 | 19.172728 | 778.192520 | 6.834872 | |||||||
10 | 8 | 51.597119 | 19.380927 | 774.550915 | 6.571859 | |||||||
10 | 9 | 53.542313 | 18.676817 | 777.358055 | 6.890178 | |||||||
32 | 2 | True | 300 | 300 | 10 | 0 | 53.818149 | 18.581092 | 779.099703 | 6.274331 | ||
10 | 1 | 54.704909 | 18.279895 | 789.219856 | 6.233845 | |||||||
10 | 2 | 52.738370 | 18.961526 | 783.346176 | 6.209411 | |||||||
10 | 3 | 53.099324 | 18.832631 | 777.828693 | 6.456271 | |||||||
10 | 4 | 54.019571 | 18.511809 | 770.405769 | 6.422836 | |||||||
10 | 5 | 53.729559 | 18.611729 | 801.283598 | 6.235909 | |||||||
10 | 6 | 52.587157 | 19.016050 | 772.557497 | 6.303951 | |||||||
10 | 7 | 54.049134 | 18.501684 | 784.798145 | 6.272491 | |||||||
10 | 8 | 55.155167 | 18.130668 | 781.807423 | 6.262083 | |||||||
10 | 9 | 52.850239 | 18.921390 | 781.973362 | 6.223582 | |||||||
tensorrt | 1 | 2 | True | 300 | 300 | 10 | 0 | 34.491213 | 28.992891 | 5693.123102 | 9.831667 | |
10 | 1 | 34.909769 | 28.645277 | 5614.737511 | 9.802699 | |||||||
10 | 2 | 34.405768 | 29.064894 | 5548.023462 | 9.771824 | |||||||
10 | 3 | 33.113885 | 30.198812 | 5601.720810 | 9.880662 | |||||||
10 | 4 | 33.933400 | 29.469490 | 5567.697525 | 9.871960 | |||||||
10 | 5 | 36.429127 | 27.450562 | 5629.716873 | 9.792566 | |||||||
10 | 6 | 35.355885 | 28.283834 | 5636.938572 | 9.807348 | |||||||
10 | 7 | 34.066797 | 29.354095 | 5734.992504 | 10.001659 | |||||||
10 | 8 | 35.254547 | 28.365135 | 5749.200821 | 9.958982 | |||||||
10 | 9 | 32.603454 | 30.671597 | 5569.962025 | 9.765744 | |||||||
2 | 2 | True | 300 | 300 | 10 | 0 | 41.345392 | 24.186492 | 5669.808388 | 8.022785 | ||
10 | 1 | 42.247433 | 23.670077 | 5584.904432 | 7.995546 | |||||||
10 | 2 | 43.110915 | 23.195982 | 5624.918938 | 8.073151 | |||||||
10 | 3 | 43.516149 | 22.979975 | 5633.650541 | 8.129537 | |||||||
10 | 4 | 44.190573 | 22.629261 | 5563.676834 | 8.092761 | |||||||
10 | 5 | 42.802514 | 23.363113 | 5689.352512 | 8.023202 | |||||||
10 | 6 | 40.245099 | 24.847746 | 5572.940826 | 8.210301 | |||||||
10 | 7 | 41.530641 | 24.078608 | 5571.259499 | 8.071780 | |||||||
10 | 8 | 41.993012 | 23.813486 | 5589.100838 | 8.057117 | |||||||
10 | 9 | 43.195271 | 23.150682 | 5695.473194 | 8.090854 | |||||||
4 | 2 | True | 300 | 300 | 10 | 0 | 48.249906 | 20.725429 | 5556.540966 | 7.749975 | ||
10 | 1 | 51.402517 | 19.454300 | 5524.202108 | 7.788837 | |||||||
10 | 2 | 50.275139 | 19.890547 | 5638.597012 | 7.917553 | |||||||
10 | 3 | 48.851497 | 20.470202 | 5544.986963 | 7.811934 | |||||||
10 | 4 | 48.008012 | 20.829856 | 5682.790756 | 7.802725 | |||||||
10 | 5 | 47.691675 | 20.968020 | 5664.843082 | 8.069426 | |||||||
10 | 6 | 47.879909 | 20.885587 | 5650.647640 | 7.854670 | |||||||
10 | 7 | 47.997299 | 20.834506 | 5630.479336 | 7.815361 | |||||||
10 | 8 | 47.534796 | 21.037221 | 5514.477968 | 7.812589 | |||||||
10 | 9 | 47.777782 | 20.930231 | 5590.559244 | 7.780701 | |||||||
8 | 2 | True | 300 | 300 | 10 | 0 | 50.022484 | 19.991010 | 5636.264801 | 6.643206 | ||
10 | 1 | 52.279151 | 19.128084 | 5630.309820 | 6.805852 | |||||||
10 | 2 | 49.403165 | 20.241618 | 5643.610477 | 6.730497 | |||||||
10 | 3 | 51.554468 | 19.396961 | 5637.037992 | 6.989181 | |||||||
10 | 4 | 49.197883 | 20.326078 | 5590.353727 | 6.730586 | |||||||
10 | 5 | 52.063461 | 19.207329 | 5637.848139 | 6.794155 | |||||||
10 | 6 | 50.623136 | 19.753814 | 5649.809122 | 6.753027 | |||||||
10 | 7 | 51.294236 | 19.495368 | 5627.628326 | 6.769717 | |||||||
10 | 8 | 51.352248 | 19.473344 | 5567.685366 | 6.736740 | |||||||
10 | 9 | 51.455487 | 19.434273 | 5618.886232 | 6.746203 | |||||||
16 | 2 | True | 300 | 300 | 10 | 0 | 52.854860 | 18.919736 | 5635.564804 | 6.518625 | ||
10 | 1 | 50.472707 | 19.812688 | 5616.070032 | 6.881125 | |||||||
10 | 2 | 51.503744 | 19.416064 | 5620.897532 | 6.502539 | |||||||
10 | 3 | 52.060472 | 19.208431 | 5690.553904 | 6.879076 | |||||||
10 | 4 | 52.010119 | 19.227028 | 5623.275042 | 6.887466 | |||||||
10 | 5 | 51.807155 | 19.302353 | 5606.832981 | 6.520502 | |||||||
10 | 6 | 55.841826 | 17.907724 | 5690.791845 | 6.719068 | |||||||
10 | 7 | 50.728944 | 19.712612 | 5658.821583 | 6.842412 | |||||||
10 | 8 | 53.442538 | 18.711686 | 5633.854151 | 6.828517 | |||||||
10 | 9 | 53.552225 | 18.673360 | 5628.093243 | 6.515622 | |||||||
32 | 2 | True | 300 | 300 | 10 | 0 | 53.113382 | 18.827647 | 5677.363634 | 6.352689 | ||
10 | 1 | 53.698669 | 18.622436 | 5608.144283 | 6.485902 | |||||||
10 | 2 | 54.095621 | 18.485785 | 5602.419615 | 6.409224 | |||||||
10 | 3 | 55.063932 | 18.160708 | 5697.304487 | 6.222568 | |||||||
10 | 4 | 51.639145 | 19.365154 | 5669.396877 | 6.242018 | |||||||
10 | 5 | 53.686082 | 18.626802 | 5628.892422 | 6.337665 | |||||||
10 | 6 | 56.188279 | 17.797306 | 5633.605242 | 6.216008 | |||||||
10 | 7 | 52.798887 | 18.939793 | 5645.969152 | 6.189067 | |||||||
10 | 8 | 52.907468 | 18.900923 | 5606.514692 | 6.473586 | |||||||
10 | 9 | 54.338853 | 18.403038 | 5652.473211 | 6.511830 | |||||||
tensorrt-dynamic | 1 | 2 | True | 300 | 300 | 10 | 0 | 33.075499 | 30.233860 | 4428.390741 | 9.896278 | |
10 | 1 | 35.898765 | 27.856112 | 4479.261875 | 9.874344 | |||||||
10 | 2 | 35.232633 | 28.382778 | 4560.572863 | 9.808779 | |||||||
10 | 3 | 35.927978 | 27.833462 | 4453.529119 | 9.793162 | |||||||
10 | 4 | 34.725084 | 28.797626 | 4468.748808 | 9.745121 | |||||||
10 | 5 | 33.368370 | 29.968500 | 4467.795610 | 9.806395 | |||||||
10 | 6 | 34.366865 | 29.097795 | 4409.515142 | 9.976268 | |||||||
10 | 7 | 35.376760 | 28.267145 | 4497.458935 | 9.778738 | |||||||
10 | 8 | 32.995618 | 30.307055 | 4504.912615 | 9.788394 | |||||||
10 | 9 | 32.630341 | 30.646324 | 4538.682461 | 9.847879 | |||||||
2 | 2 | True | 300 | 300 | 10 | 0 | 44.159865 | 22.644997 | 4527.956724 | 8.072674 | ||
10 | 1 | 43.264556 | 23.113608 | 4500.693560 | 8.028150 | |||||||
10 | 2 | 41.775520 | 23.937464 | 4431.074381 | 8.014083 | |||||||
10 | 3 | 41.853265 | 23.892999 | 4470.486164 | 8.065104 | |||||||
10 | 4 | 42.518528 | 23.519158 | 4494.201183 | 8.137047 | |||||||
10 | 5 | 43.462714 | 23.008227 | 4473.366261 | 8.062184 | |||||||
10 | 6 | 45.637386 | 21.911860 | 4491.267443 | 8.057714 | |||||||
10 | 7 | 42.913969 | 23.302436 | 4471.668482 | 8.096933 | |||||||
10 | 8 | 41.951220 | 23.837209 | 4529.442310 | 8.108199 | |||||||
10 | 9 | 42.023094 | 23.796439 | 4510.761976 | 8.094668 | |||||||
4 | 2 | True | 300 | 300 | 10 | 0 | 49.638937 | 20.145476 | 4398.817539 | 8.087516 | ||
10 | 1 | 48.622142 | 20.566761 | 4474.259615 | 7.867664 | |||||||
10 | 2 | 48.535916 | 20.603299 | 4536.252737 | 8.033156 | |||||||
10 | 3 | 49.745497 | 20.102322 | 4426.193714 | 8.049458 | |||||||
10 | 4 | 48.561344 | 20.592511 | 4510.492563 | 7.939309 | |||||||
10 | 5 | 48.524265 | 20.608246 | 4523.043633 | 7.985383 | |||||||
10 | 6 | 48.355597 | 20.680130 | 4416.669130 | 7.866770 | |||||||
10 | 7 | 47.774381 | 20.931721 | 4529.404402 | 7.852346 | |||||||
10 | 8 | 48.585533 | 20.582259 | 4480.943680 | 8.084804 | |||||||
10 | 9 | 47.964230 | 20.848870 | 4440.499544 | 7.843494 | |||||||
8 | 2 | True | 300 | 300 | 10 | 0 | 49.644224 | 20.143330 | 4441.440582 | 6.721780 | ||
10 | 1 | 50.144783 | 19.942254 | 4443.773985 | 6.800517 | |||||||
10 | 2 | 51.281614 | 19.500166 | 4456.780910 | 6.947145 | |||||||
10 | 3 | 51.593945 | 19.382119 | 4501.610041 | 6.735057 | |||||||
10 | 4 | 50.013910 | 19.994438 | 4496.972561 | 6.897643 | |||||||
10 | 5 | 52.018020 | 19.224107 | 4485.256433 | 6.950125 | |||||||
10 | 6 | 52.346926 | 19.103318 | 4493.339300 | 6.978855 | |||||||
10 | 7 | 51.063412 | 19.583493 | 4480.364561 | 6.962791 | |||||||
10 | 8 | 50.863554 | 19.660443 | 4510.897398 | 6.955460 | |||||||
10 | 9 | 51.222275 | 19.522756 | 4498.049259 | 6.953925 | |||||||
16 | 2 | True | 300 | 300 | 10 | 0 | 55.135931 | 18.136993 | 4443.065166 | 6.560914 | ||
10 | 1 | 53.695210 | 18.623635 | 4502.415180 | 6.883219 | |||||||
10 | 2 | 52.671252 | 18.985689 | 4430.941820 | 6.867565 | |||||||
10 | 3 | 53.916820 | 18.547088 | 4419.278145 | 6.855160 | |||||||
10 | 4 | 52.181184 | 19.163996 | 4415.038824 | 6.553091 | |||||||
10 | 5 | 51.752221 | 19.322842 | 4370.236158 | 6.860144 | |||||||
10 | 6 | 51.836888 | 19.291282 | 4543.978930 | 6.480657 | |||||||
10 | 7 | 53.332155 | 18.750414 | 4506.866932 | 6.521039 | |||||||
10 | 8 | 53.612891 | 18.652231 | 4417.213440 | 6.573483 | |||||||
10 | 9 | 52.644684 | 18.995270 | 4505.507708 | 6.823301 | |||||||
32 | 2 | True | 300 | 300 | 10 | 0 | 53.851619 | 18.569544 | 4444.882870 | 6.220557 | ||
10 | 1 | 55.655008 | 17.967835 | 4402.207851 | 6.254584 | |||||||
10 | 2 | 56.931938 | 17.564833 | 4446.827650 | 6.302960 | |||||||
10 | 3 | 57.242784 | 17.469451 | 4511.808872 | 6.349295 | |||||||
10 | 4 | 54.578289 | 18.322304 | 4474.316120 | 6.366946 | |||||||
10 | 5 | 54.404888 | 18.380702 | 4485.224247 | 6.514076 | |||||||
10 | 6 | 53.523417 | 18.683411 | 4479.867935 | 6.208107 | |||||||
10 | 7 | 53.068734 | 18.843487 | 4491.706133 | 6.267328 | |||||||
10 | 8 | 55.089674 | 18.152222 | 4475.549459 | 6.558314 | |||||||
10 | 9 | 54.115993 | 18.478826 | 4445.625305 | 6.254699 | |||||||
ssd-mobilenet-v1-quantized-mlperf | cpu | 1 | 2 | True | 300 | 300 | 10 | 0 | 41.348449 | 24.184704 | 1141.518593 | 9.508848 |
10 | 1 | 40.496114 | 24.693727 | 1171.593904 | 10.394216 | |||||||
10 | 2 | 41.953528 | 23.835897 | 1141.031742 | 10.167122 | |||||||
10 | 3 | 41.385168 | 24.163246 | 1137.880325 | 9.997845 | |||||||
10 | 4 | 39.455007 | 25.345325 | 1147.413731 | 9.865284 | |||||||
10 | 5 | 43.608900 | 22.931099 | 1123.368263 | 10.007501 | |||||||
10 | 6 | 36.653564 | 27.282476 | 1281.663418 | 10.389447 | |||||||
10 | 7 | 39.008073 | 25.635719 | 1127.808571 | 10.025382 | |||||||
10 | 8 | 42.125443 | 23.738623 | 1143.161297 | 10.257363 | |||||||
10 | 9 | 40.091226 | 24.943113 | 1132.368088 | 10.350823 | |||||||
2 | 2 | True | 300 | 300 | 10 | 0 | 54.527070 | 18.339515 | 1154.313564 | 8.379519 | ||
10 | 1 | 52.303272 | 19.119263 | 1100.859404 | 8.277714 | |||||||
10 | 2 | 48.142051 | 20.771861 | 1136.225939 | 8.205116 | |||||||
10 | 3 | 50.676042 | 19.733191 | 1108.897209 | 8.291483 | |||||||
10 | 4 | 46.849337 | 21.345019 | 1142.849684 | 8.236468 | |||||||
10 | 5 | 51.675628 | 19.351482 | 1120.688438 | 8.327782 | |||||||
10 | 6 | 52.557237 | 19.026875 | 1108.834267 | 8.068800 | |||||||
10 | 7 | 50.874273 | 19.656301 | 1104.010820 | 8.074701 | |||||||
10 | 8 | 52.412421 | 19.079447 | 1131.302118 | 8.441091 | |||||||
10 | 9 | 51.449018 | 19.436717 | 1149.085522 | 8.410871 | |||||||
4 | 2 | True | 300 | 300 | 10 | 0 | 55.355917 | 18.064916 | 1158.612013 | 8.156538 | ||
10 | 1 | 55.221452 | 18.108904 | 1160.176277 | 8.203596 | |||||||
10 | 2 | 55.130903 | 18.138647 | 1082.293510 | 8.134514 | |||||||
10 | 3 | 59.414665 | 16.830862 | 1095.991850 | 8.108407 | |||||||
10 | 4 | 54.393422 | 18.384576 | 1091.183186 | 8.103549 | |||||||
10 | 5 | 53.077003 | 18.840551 | 1098.875284 | 7.998437 | |||||||
10 | 6 | 54.653363 | 18.297136 | 1150.421858 | 8.282721 | |||||||
10 | 7 | 53.999337 | 18.518746 | 1106.023312 | 7.997632 | |||||||
10 | 8 | 55.504991 | 18.016398 | 1161.789656 | 8.129805 | |||||||
10 | 9 | 54.145552 | 18.468738 | 1119.019747 | 8.028477 | |||||||
8 | 2 | True | 300 | 300 | 10 | 0 | 63.781389 | 15.678555 | 1130.697250 | 6.893709 | ||
10 | 1 | 63.636597 | 15.714228 | 1124.075413 | 6.753534 | |||||||
10 | 2 | 61.982765 | 16.133517 | 1108.465195 | 6.904945 | |||||||
10 | 3 | 62.164084 | 16.086459 | 1108.081102 | 6.685421 | |||||||
10 | 4 | 63.903466 | 15.648603 | 1153.816938 | 6.953776 | |||||||
10 | 5 | 63.158787 | 15.833110 | 1165.574312 | 6.874070 | |||||||
10 | 6 | 65.668748 | 15.227944 | 1097.320318 | 6.773993 | |||||||
10 | 7 | 65.437460 | 15.281767 | 1131.476164 | 6.856203 | |||||||
10 | 8 | 64.929819 | 15.401244 | 1157.756805 | 6.803423 | |||||||
10 | 9 | 64.890266 | 15.410632 | 1127.169847 | 6.915033 | |||||||
16 | 2 | True | 300 | 300 | 10 | 0 | 61.278967 | 16.318813 | 1116.379499 | 6.518774 | ||
10 | 1 | 60.619049 | 16.496465 | 1111.896038 | 6.598473 | |||||||
10 | 2 | 60.792907 | 16.449288 | 1105.592966 | 6.524555 | |||||||
10 | 3 | 61.690240 | 16.210020 | 1125.183582 | 6.771743 | |||||||
10 | 4 | 58.035130 | 17.230943 | 1161.416769 | 6.706670 | |||||||
10 | 5 | 61.566240 | 16.242668 | 1137.651682 | 6.813996 | |||||||
10 | 6 | 61.949522 | 16.142175 | 1147.143364 | 6.436564 | |||||||
10 | 7 | 59.478540 | 16.812786 | 1132.051229 | 6.585948 | |||||||
10 | 8 | 61.019874 | 16.388103 | 1106.467009 | 6.517507 | |||||||
10 | 9 | 60.501496 | 16.528517 | 1114.739418 | 6.584004 | |||||||
32 | 2 | True | 300 | 300 | 10 | 0 | 60.571968 | 16.509287 | 1335.273027 | 6.240573 | ||
10 | 1 | 58.888475 | 16.981252 | 1139.098406 | 6.271660 | |||||||
10 | 2 | 59.194109 | 16.893573 | 1164.017200 | 6.336439 | |||||||
10 | 3 | 60.497487 | 16.529612 | 1140.981436 | 6.424516 | |||||||
10 | 4 | 57.294612 | 17.453648 | 1146.106958 | 6.223690 | |||||||
10 | 5 | 57.372592 | 17.429926 | 1160.487175 | 6.275326 | |||||||
10 | 6 | 57.879513 | 17.277271 | 1129.624128 | 6.222263 | |||||||
10 | 7 | 57.862246 | 17.282426 | 1111.538410 | 6.232411 | |||||||
10 | 8 | 60.131693 | 16.630165 | 1117.774963 | 6.223902 | |||||||
10 | 9 | 57.830558 | 17.291896 | 1154.215574 | 6.232198 | |||||||
cpu-prebuilt | 1 | 2 | True | 300 | 300 | 10 | 0 | 40.441059 | 24.727345 | 1309.064388 | 9.849906 | |
10 | 1 | 37.045610 | 26.993752 | 1047.098160 | 9.984732 | |||||||
10 | 2 | 43.521567 | 22.977114 | 1052.574873 | 9.961367 | |||||||
10 | 3 | 37.864298 | 26.410103 | 1045.958281 | 9.989738 | |||||||
10 | 4 | 37.574952 | 26.613474 | 1031.730890 | 10.116339 | |||||||
10 | 5 | 39.878149 | 25.076389 | 1095.279455 | 9.931684 | |||||||
10 | 6 | 40.063654 | 24.960279 | 1048.730612 | 10.042787 | |||||||
10 | 7 | 36.900576 | 27.099848 | 1040.490389 | 10.020614 | |||||||
10 | 8 | 40.199969 | 24.875641 | 1122.545481 | 10.402083 | |||||||
10 | 9 | 39.426450 | 25.363684 | 1047.638655 | 10.037899 | |||||||
2 | 2 | True | 300 | 300 | 10 | 0 | 50.685534 | 19.729495 | 1040.905714 | 8.306503 | ||
10 | 1 | 48.573857 | 20.587206 | 1037.618876 | 8.160651 | |||||||
10 | 2 | 51.053234 | 19.587398 | 1043.580294 | 8.207619 | |||||||
10 | 3 | 46.482008 | 21.513700 | 1048.915386 | 8.179367 | |||||||
10 | 4 | 48.895490 | 20.451784 | 1034.586668 | 8.265018 | |||||||
10 | 5 | 48.553896 | 20.595670 | 1055.195570 | 8.268952 | |||||||
10 | 6 | 49.706146 | 20.118237 | 1033.941031 | 8.346558 | |||||||
10 | 7 | 52.070490 | 19.204736 | 1167.417288 | 8.097112 | |||||||
10 | 8 | 49.188219 | 20.330071 | 1048.541069 | 8.374274 | |||||||
10 | 9 | 52.884933 | 18.908978 | 1043.299913 | 8.308649 | |||||||
4 | 2 | True | 300 | 300 | 10 | 0 | 55.742704 | 17.939568 | 1098.007917 | 8.038461 | ||
10 | 1 | 64.986156 | 15.387893 | 1042.261124 | 7.875025 | |||||||
10 | 2 | 57.551021 | 17.375886 | 1044.894695 | 8.018285 | |||||||
10 | 3 | 64.205000 | 15.575111 | 1042.172432 | 7.973731 | |||||||
10 | 4 | 58.329767 | 17.143905 | 1032.604456 | 7.848501 | |||||||
10 | 5 | 57.594683 | 17.362714 | 1057.824612 | 7.987052 | |||||||
10 | 6 | 60.255630 | 16.595960 | 1063.431978 | 7.877618 | |||||||
10 | 7 | 54.803683 | 18.246949 | 1043.725729 | 8.001059 | |||||||
10 | 8 | 55.601933 | 17.984986 | 1052.542448 | 8.195430 | |||||||
10 | 9 | 57.626731 | 17.353058 | 1188.806295 | 7.968754 | |||||||
8 | 2 | True | 300 | 300 | 10 | 0 | 61.420131 | 16.281307 | 1038.946867 | 6.855279 | ||
10 | 1 | 59.209176 | 16.889274 | 1118.232012 | 6.844476 | |||||||
10 | 2 | 60.896120 | 16.421407 | 1035.385132 | 6.851062 | |||||||
10 | 3 | 61.316760 | 16.308755 | 1037.714481 | 6.793469 | |||||||
10 | 4 | 63.736926 | 15.689492 | 1068.039417 | 6.991088 | |||||||
10 | 5 | 63.553912 | 15.734673 | 1049.790144 | 6.952107 | |||||||
10 | 6 | 61.231386 | 16.331494 | 1031.262636 | 6.818563 | |||||||
10 | 7 | 62.301089 | 16.051084 | 1056.199789 | 6.892756 | |||||||
10 | 8 | 62.549739 | 15.987277 | 1022.531748 | 6.714419 | |||||||
10 | 9 | 67.521012 | 14.810205 | 1041.496992 | 6.728142 | |||||||
16 | 2 | True | 300 | 300 | 10 | 0 | 60.322466 | 16.577572 | 1165.717125 | 6.635241 | ||
10 | 1 | 61.596246 | 16.234756 | 1067.545891 | 6.781265 | |||||||
10 | 2 | 58.108648 | 17.209142 | 1034.183741 | 6.792784 | |||||||
10 | 3 | 60.298455 | 16.584173 | 1027.941942 | 6.518237 | |||||||
10 | 4 | 59.369461 | 16.843677 | 1031.779289 | 6.543800 | |||||||
10 | 5 | 59.765905 | 16.731948 | 1041.755676 | 6.752186 | |||||||
10 | 6 | 59.762233 | 16.732976 | 1048.759222 | 6.551087 | |||||||
10 | 7 | 60.554341 | 16.514093 | 1062.961578 | 6.571285 | |||||||
10 | 8 | 59.123575 | 16.913727 | 1081.460476 | 6.551549 | |||||||
10 | 9 | 55.715399 | 17.948359 | 1028.668642 | 6.500758 | |||||||
32 | 2 | True | 300 | 300 | 10 | 0 | 58.722987 | 17.029107 | 1089.289427 | 6.313432 | ||
10 | 1 | 56.852863 | 17.589264 | 1098.215103 | 6.244589 | |||||||
10 | 2 | 56.595440 | 17.669268 | 1055.323839 | 6.296054 | |||||||
10 | 3 | 59.791731 | 16.724721 | 1037.086487 | 6.419033 | |||||||
10 | 4 | 56.710342 | 17.633468 | 1034.259796 | 6.256852 | |||||||
10 | 5 | 57.984183 | 17.246082 | 1064.899206 | 6.237723 | |||||||
10 | 6 | 58.078550 | 17.218061 | 1122.566223 | 6.265502 | |||||||
10 | 7 | 58.812017 | 17.003328 | 1052.809000 | 6.317627 | |||||||
10 | 8 | 57.999869 | 17.241418 | 1058.693171 | 6.457172 | |||||||
10 | 9 | 57.860250 | 17.283022 | 1046.101570 | 6.279267 | |||||||
cuda | 1 | 2 | True | 300 | 300 | 10 | 0 | 47.736863 | 20.948172 | 1072.395086 | 9.973407 | |
10 | 1 | 44.426951 | 22.508860 | 1061.632156 | 9.851217 | |||||||
10 | 2 | 45.339906 | 22.055626 | 1052.780151 | 9.912848 | |||||||
10 | 3 | 45.633911 | 21.913528 | 1051.055908 | 9.842157 | |||||||
10 | 4 | 45.379149 | 22.036552 | 1045.479774 | 10.001063 | |||||||
10 | 5 | 47.179492 | 21.195650 | 1213.608742 | 9.879351 | |||||||
10 | 6 | 46.484584 | 21.512508 | 1034.584761 | 9.995222 | |||||||
10 | 7 | 46.701451 | 21.412611 | 1059.213400 | 10.006666 | |||||||
10 | 8 | 45.686600 | 21.888256 | 1056.025982 | 10.016084 | |||||||
10 | 9 | 46.721740 | 21.403313 | 1036.118746 | 10.092020 | |||||||
2 | 2 | True | 300 | 300 | 10 | 0 | 58.822431 | 17.000318 | 1072.357416 | 8.326054 | ||
10 | 1 | 57.381152 | 17.427325 | 1038.028002 | 8.314252 | |||||||
10 | 2 | 57.955590 | 17.254591 | 1023.281574 | 8.316636 | |||||||
10 | 3 | 59.619255 | 16.773105 | 1030.957222 | 8.168757 | |||||||
10 | 4 | 56.107337 | 17.822981 | 1056.241989 | 8.212805 | |||||||
10 | 5 | 57.715941 | 17.326236 | 1067.446709 | 8.144021 | |||||||
10 | 6 | 57.721898 | 17.324448 | 1051.792383 | 8.059025 | |||||||
10 | 7 | 54.800282 | 18.248081 | 1052.458763 | 8.316636 | |||||||
10 | 8 | 57.631878 | 17.351508 | 1046.841145 | 8.296788 | |||||||
10 | 9 | 56.964994 | 17.554641 | 1033.020496 | 8.300185 | |||||||
4 | 2 | True | 300 | 300 | 10 | 0 | 65.204375 | 15.336394 | 1040.844440 | 8.035362 | ||
10 | 1 | 65.846973 | 15.186727 | 1054.573298 | 7.947505 | |||||||
10 | 2 | 69.567952 | 14.374435 | 1053.631783 | 7.832497 | |||||||
10 | 3 | 64.892650 | 15.410066 | 1065.173388 | 7.954657 | |||||||
10 | 4 | 65.823980 | 15.192032 | 1044.612885 | 7.860094 | |||||||
10 | 5 | 63.247240 | 15.810966 | 1047.475338 | 7.912278 | |||||||
10 | 6 | 65.543681 | 15.257001 | 1056.888580 | 7.834315 | |||||||
10 | 7 | 65.533952 | 15.259266 | 1036.722898 | 7.966399 | |||||||
10 | 8 | 67.347273 | 14.848411 | 1054.852724 | 7.903993 | |||||||
10 | 9 | 64.580909 | 15.484452 | 1056.848288 | 7.932007 | |||||||
8 | 2 | True | 300 | 300 | 10 | 0 | 74.732140 | 13.381124 | 1029.964924 | 6.796435 | ||
10 | 1 | 74.683903 | 13.389766 | 1054.652691 | 6.828427 | |||||||
10 | 2 | 72.663400 | 13.762087 | 1051.391840 | 6.789342 | |||||||
10 | 3 | 73.634178 | 13.580650 | 1047.311306 | 6.884679 | |||||||
10 | 4 | 72.830264 | 13.730556 | 1052.465200 | 6.779656 | |||||||
10 | 5 | 74.047729 | 13.504803 | 1062.226772 | 6.733328 | |||||||
10 | 6 | 72.906696 | 13.716161 | 1042.716980 | 6.745428 | |||||||
10 | 7 | 72.332110 | 13.825119 | 1049.687862 | 6.696597 | |||||||
10 | 8 | 72.947272 | 13.708532 | 1049.215794 | 6.844774 | |||||||
10 | 9 | 71.459915 | 13.993859 | 1044.232845 | 6.917447 | |||||||
16 | 2 | True | 300 | 300 | 10 | 0 | 76.220230 | 13.119876 | 1058.016539 | 6.763577 | ||
10 | 1 | 77.116415 | 12.967408 | 1043.073893 | 6.593823 | |||||||
10 | 2 | 76.519544 | 13.068557 | 1061.495543 | 6.925061 | |||||||
10 | 3 | 78.035741 | 12.814641 | 1043.457985 | 6.579340 | |||||||
10 | 4 | 77.564478 | 12.892500 | 1060.048103 | 6.749853 | |||||||
10 | 5 | 76.995467 | 12.987778 | 1046.889782 | 6.552026 | |||||||
10 | 6 | 77.696217 | 12.870640 | 1057.307720 | 6.630041 | |||||||
10 | 7 | 75.357326 | 13.270110 | 1063.073635 | 6.586321 | |||||||
10 | 8 | 77.163411 | 12.959510 | 1055.134773 | 6.653994 | |||||||
10 | 9 | 78.046994 | 12.812793 | 1045.463085 | 6.904095 | |||||||
32 | 2 | True | 300 | 300 | 10 | 0 | 78.084545 | 12.806632 | 1036.835432 | 6.313942 | ||
10 | 1 | 77.134630 | 12.964346 | 1049.352884 | 6.631158 | |||||||
10 | 2 | 77.850885 | 12.845069 | 1039.554834 | 6.222758 | |||||||
10 | 3 | 78.302340 | 12.771010 | 1035.851955 | 6.272547 | |||||||
10 | 4 | 77.800478 | 12.853391 | 1066.196203 | 6.254006 | |||||||
10 | 5 | 77.417553 | 12.916967 | 1058.874130 | 6.411519 | |||||||
10 | 6 | 77.410989 | 12.918063 | 1062.852144 | 6.332852 | |||||||
10 | 7 | 76.002140 | 13.157524 | 1041.868925 | 6.322779 | |||||||
10 | 8 | 77.588153 | 12.888566 | 1063.034534 | 6.214421 | |||||||
10 | 9 | 77.352635 | 12.927808 | 1079.278946 | 6.207768 | |||||||
tensorrt | 1 | 2 | True | 300 | 300 | 10 | 0 | 44.879506 | 22.281885 | 7123.430490 | 9.938359 | |
10 | 1 | 45.896571 | 21.788120 | 7108.290195 | 9.763122 | |||||||
10 | 2 | 45.750886 | 21.857500 | 7096.955061 | 9.778380 | |||||||
10 | 3 | 46.714454 | 21.406651 | 7063.511372 | 9.863853 | |||||||
10 | 4 | 44.961773 | 22.241116 | 7079.815626 | 9.698868 | |||||||
10 | 5 | 46.786364 | 21.373749 | 7096.222401 | 9.900928 | |||||||
10 | 6 | 45.375222 | 22.038460 | 7078.917027 | 9.767294 | |||||||
10 | 7 | 46.308035 | 21.594524 | 7104.745865 | 9.731770 | |||||||
10 | 8 | 45.647817 | 21.906853 | 7133.631945 | 9.848475 | |||||||
10 | 9 | 45.444050 | 22.005081 | 7150.356531 | 9.665608 | |||||||
2 | 2 | True | 300 | 300 | 10 | 0 | 58.572711 | 17.072797 | 7159.089088 | 8.055568 | ||
10 | 1 | 56.268416 | 17.771959 | 7057.126999 | 8.049965 | |||||||
10 | 2 | 56.662555 | 17.648339 | 7124.001980 | 8.127034 | |||||||
10 | 3 | 57.482204 | 17.396688 | 7202.754974 | 8.050621 | |||||||
10 | 4 | 57.387825 | 17.425299 | 7141.631842 | 8.012891 | |||||||
10 | 5 | 56.594128 | 17.669678 | 7013.514280 | 8.051515 | |||||||
10 | 6 | 59.028978 | 16.940832 | 7109.473228 | 8.028746 | |||||||
10 | 7 | 57.955590 | 17.254591 | 7135.635853 | 8.022904 | |||||||
10 | 8 | 57.148556 | 17.498255 | 7042.576551 | 8.270383 | |||||||
10 | 9 | 58.484913 | 17.098427 | 7034.452677 | 8.007348 | |||||||
4 | 2 | True | 300 | 300 | 10 | 0 | 64.725415 | 15.449882 | 7074.600697 | 8.012056 | ||
10 | 1 | 63.373144 | 15.779555 | 7085.893393 | 8.088231 | |||||||
10 | 2 | 66.429424 | 15.053570 | 7048.755884 | 8.031487 | |||||||
10 | 3 | 65.250275 | 15.325606 | 7034.267187 | 8.069247 | |||||||
10 | 4 | 65.214766 | 15.333951 | 7130.547285 | 7.950902 | |||||||
10 | 5 | 65.505550 | 15.265882 | 7089.531422 | 7.904530 | |||||||
10 | 6 | 64.029799 | 15.617728 | 7119.791985 | 7.780850 | |||||||
10 | 7 | 65.942214 | 15.164793 | 7195.689201 | 7.865220 | |||||||
10 | 8 | 65.534464 | 15.259147 | 7132.315159 | 7.791936 | |||||||
10 | 9 | 63.680558 | 15.703380 | 7093.014956 | 7.820636 | |||||||
8 | 2 | True | 300 | 300 | 10 | 0 | 71.298507 | 14.025539 | 7074.872017 | 6.767228 | ||
10 | 1 | 72.376888 | 13.816565 | 7089.612961 | 6.696120 | |||||||
10 | 2 | 73.121817 | 13.675809 | 7110.588074 | 6.759971 | |||||||
10 | 3 | 73.200939 | 13.661027 | 7105.098248 | 6.812528 | |||||||
10 | 4 | 72.154638 | 13.859123 | 7090.573788 | 6.809860 | |||||||
10 | 5 | 72.213958 | 13.847739 | 7094.809532 | 6.766707 | |||||||
10 | 6 | 74.139514 | 13.488084 | 7119.920015 | 6.968752 | |||||||
10 | 7 | 72.254699 | 13.839930 | 7242.331505 | 6.968305 | |||||||
10 | 8 | 74.052304 | 13.503969 | 7073.332071 | 6.843194 | |||||||
10 | 9 | 71.986527 | 13.891488 | 7078.927040 | 6.784365 | |||||||
16 | 2 | True | 300 | 300 | 10 | 0 | 76.237202 | 13.116956 | 7137.548923 | 6.830409 | ||
10 | 1 | 75.098016 | 13.315931 | 7022.910595 | 6.522901 | |||||||
10 | 2 | 75.640508 | 13.220429 | 7039.772511 | 6.748743 | |||||||
10 | 3 | 74.806781 | 13.367772 | 7034.528971 | 6.886221 | |||||||
10 | 4 | 74.952158 | 13.341844 | 7142.646551 | 6.512262 | |||||||
10 | 5 | 75.163708 | 13.304293 | 7138.361692 | 6.879665 | |||||||
10 | 6 | 76.975154 | 12.991205 | 7137.981892 | 6.521046 | |||||||
10 | 7 | 74.334390 | 13.452724 | 7127.883911 | 6.899901 | |||||||
10 | 8 | 76.398632 | 13.089240 | 7101.144314 | 6.532736 | |||||||
10 | 9 | 78.012699 | 12.818426 | 7104.007959 | 6.573454 | |||||||
32 | 2 | True | 300 | 300 | 10 | 0 | 75.877238 | 13.179183 | 7028.620958 | 6.213941 | ||
10 | 1 | 78.366163 | 12.760609 | 7215.569258 | 6.314900 | |||||||
10 | 2 | 77.502625 | 12.902789 | 7181.191206 | 6.204851 | |||||||
10 | 3 | 77.052797 | 12.978114 | 7204.288960 | 6.472256 | |||||||
10 | 4 | 74.507041 | 13.421550 | 7076.518536 | 6.345276 | |||||||
10 | 5 | 74.613696 | 13.402365 | 7155.494452 | 6.593291 | |||||||
10 | 6 | 77.437162 | 12.913696 | 7074.496746 | 6.642245 | |||||||
10 | 7 | 78.017823 | 12.817584 | 7032.968521 | 6.642971 | |||||||
10 | 8 | 75.998827 | 13.158098 | 7065.843344 | 6.629419 | |||||||
10 | 9 | 77.519635 | 12.899958 | 7109.196186 | 6.290577 | |||||||
tensorrt-dynamic | 1 | 2 | True | 300 | 300 | 10 | 0 | 45.938293 | 21.768332 | 5793.458462 | 9.775043 | |
10 | 1 | 45.675654 | 21.893501 | 5750.547647 | 9.920835 | |||||||
10 | 2 | 51.432930 | 19.442797 | 5830.008745 | 9.742856 | |||||||
10 | 3 | 49.596821 | 20.162582 | 5755.321026 | 9.704709 | |||||||
10 | 4 | 49.436064 | 20.228148 | 5926.057339 | 9.736776 | |||||||
10 | 5 | 45.546200 | 21.955729 | 5836.916924 | 9.829998 | |||||||
10 | 6 | 47.782545 | 20.928144 | 5818.340778 | 9.796858 | |||||||
10 | 7 | 49.294299 | 20.286322 | 5859.798670 | 9.711623 | |||||||
10 | 8 | 45.307092 | 22.071600 | 5864.037991 | 9.728909 | |||||||
10 | 9 | 45.384059 | 22.034168 | 5768.066883 | 9.842157 | |||||||
2 | 2 | True | 300 | 300 | 10 | 0 | 57.416500 | 17.416596 | 5758.180380 | 8.009374 | ||
10 | 1 | 54.676339 | 18.289447 | 5801.112652 | 8.045614 | |||||||
10 | 2 | 59.107588 | 16.918302 | 5800.835371 | 8.006454 | |||||||
10 | 3 | 59.636632 | 16.768217 | 5811.677456 | 8.012474 | |||||||
10 | 4 | 57.085943 | 17.517447 | 5873.568058 | 7.994771 | |||||||
10 | 5 | 58.615276 | 17.060399 | 5802.568436 | 8.155286 | |||||||
10 | 6 | 57.741367 | 17.318606 | 5855.651617 | 7.979155 | |||||||
10 | 7 | 60.370980 | 16.564250 | 5841.228485 | 7.967949 | |||||||
10 | 8 | 57.798656 | 17.301440 | 5840.348482 | 8.026183 | |||||||
10 | 9 | 54.218695 | 18.443823 | 5810.206175 | 7.998705 | |||||||
4 | 2 | True | 300 | 300 | 10 | 0 | 68.002691 | 14.705300 | 5865.043879 | 8.005500 | ||
10 | 1 | 69.428613 | 14.403284 | 5854.304552 | 7.781118 | |||||||
10 | 2 | 66.962350 | 14.933765 | 5865.014315 | 7.751703 | |||||||
10 | 3 | 69.325334 | 14.424741 | 5867.359638 | 8.062124 | |||||||
10 | 4 | 69.243788 | 14.441729 | 5873.419046 | 7.969081 | |||||||
10 | 5 | 69.559876 | 14.376104 | 5812.558889 | 8.033216 | |||||||
10 | 6 | 69.630895 | 14.361441 | 5865.339279 | 8.025318 | |||||||
10 | 7 | 67.982025 | 14.709771 | 5872.568369 | 7.962793 | |||||||
10 | 8 | 69.782656 | 14.330208 | 5845.269680 | 7.953584 | |||||||
10 | 9 | 67.747041 | 14.760792 | 5910.014391 | 8.042395 | |||||||
8 | 2 | True | 300 | 300 | 10 | 0 | 73.276231 | 13.646990 | 5830.368996 | 6.824210 | ||
10 | 1 | 71.899684 | 13.908267 | 5899.592161 | 6.959260 | |||||||
10 | 2 | 73.132814 | 13.673753 | 5873.061419 | 6.992325 | |||||||
10 | 3 | 73.893467 | 13.532996 | 5847.330570 | 6.635457 | |||||||
10 | 4 | 72.348174 | 13.822049 | 5839.567661 | 6.717265 | |||||||
10 | 5 | 73.382318 | 13.627261 | 5853.819370 | 6.948799 | |||||||
10 | 6 | 74.256497 | 13.466835 | 5942.756414 | 6.785452 | |||||||
10 | 7 | 74.786273 | 13.371438 | 5841.147900 | 6.892428 | |||||||
10 | 8 | 73.390504 | 13.625741 | 5794.231892 | 6.856382 | |||||||
10 | 9 | 76.317831 | 13.103098 | 5854.991436 | 6.855786 | |||||||
16 | 2 | True | 300 | 300 | 10 | 0 | 79.187677 | 12.628227 | 5828.539610 | 6.874055 | ||
10 | 1 | 76.099831 | 13.140634 | 5960.506916 | 6.546430 | |||||||
10 | 2 | 78.597822 | 12.722999 | 5811.300993 | 6.724693 | |||||||
10 | 3 | 77.659263 | 12.876764 | 5794.836998 | 6.541140 | |||||||
10 | 4 | 78.604635 | 12.721896 | 5913.775682 | 6.476842 | |||||||
10 | 5 | 76.692777 | 13.039038 | 5850.826740 | 6.695062 | |||||||
10 | 6 | 76.448153 | 13.080761 | 5859.509468 | 6.677456 | |||||||
10 | 7 | 76.065414 | 13.146579 | 5859.508038 | 6.517343 | |||||||
10 | 8 | 77.981605 | 12.823537 | 5865.531921 | 6.869994 | |||||||
10 | 9 | 76.892161 | 13.005227 | 5846.389294 | 6.884292 | |||||||
32 | 2 | True | 300 | 300 | 10 | 0 | 80.189638 | 12.470439 | 5762.305021 | 6.599370 | ||
10 | 1 | 78.977063 | 12.661904 | 5833.571672 | 6.236974 | |||||||
10 | 2 | 82.863083 | 12.068100 | 5827.735186 | 6.217435 | |||||||
10 | 3 | 80.388719 | 12.439556 | 5816.005707 | 6.597616 | |||||||
10 | 4 | 78.810997 | 12.688585 | 5843.477011 | 6.239973 | |||||||
10 | 5 | 79.709880 | 12.545496 | 5795.105457 | 6.575037 | |||||||
10 | 6 | 80.851082 | 12.368418 | 5842.574835 | 6.621655 | |||||||
10 | 7 | 81.112587 | 12.328543 | 5779.558420 | 6.600361 | |||||||
10 | 8 | 80.312524 | 12.451358 | 5818.472385 | 6.293070 | |||||||
10 | 9 | 79.353741 | 12.601800 | 5791.924715 | 6.193805 | |||||||
ssd-resnet50-fpn | cpu | 1 | 2 | True | 640 | 640 | 10 | 0 | 2.885392 | 346.573353 | 1215.217590 | 9.813547 |
10 | 1 | 2.902233 | 344.562292 | 1213.778973 | 9.861469 | |||||||
10 | 2 | 2.901994 | 344.590664 | 1163.634300 | 9.424686 | |||||||
10 | 3 | 2.908665 | 343.800306 | 1198.755503 | 9.889960 | |||||||
10 | 4 | 2.922375 | 342.187405 | 1183.545589 | 9.415150 | |||||||
10 | 5 | 2.865341 | 348.998547 | 1217.129230 | 9.387851 | |||||||
10 | 6 | 2.888207 | 346.235514 | 1232.977867 | 9.844065 | |||||||
10 | 7 | 2.838141 | 352.343321 | 1231.852293 | 9.802461 | |||||||
10 | 8 | 2.925300 | 341.845274 | 1222.834587 | 9.759426 | |||||||
10 | 9 | 2.910623 | 343.569040 | 1165.804625 | 9.410620 | |||||||
2 | 2 | True | 640 | 640 | 10 | 0 | 2.873998 | 347.947359 | 1159.969807 | 7.540405 | ||
10 | 1 | 2.908272 | 343.846798 | 1234.817982 | 7.984102 | |||||||
10 | 2 | 2.894643 | 345.465779 | 1150.921106 | 7.940948 | |||||||
10 | 3 | 2.877366 | 347.540021 | 1126.492739 | 7.705986 | |||||||
10 | 4 | 2.903768 | 344.380140 | 1224.944115 | 7.951438 | |||||||
10 | 5 | 2.895594 | 345.352292 | 1193.471193 | 7.978678 | |||||||
10 | 6 | 2.923425 | 342.064500 | 1203.737497 | 7.766485 | |||||||
10 | 7 | 2.900185 | 344.805598 | 1162.850142 | 7.783830 | |||||||
10 | 8 | 2.831976 | 353.110313 | 1156.932592 | 7.961750 | |||||||
10 | 9 | 2.923105 | 342.101932 | 1166.455507 | 7.627249 | |||||||
4 | 2 | True | 640 | 640 | 10 | 0 | 2.866955 | 348.802149 | 1184.247494 | 7.521212 | ||
10 | 1 | 2.856502 | 350.078583 | 1208.733320 | 7.707179 | |||||||
10 | 2 | 2.894666 | 345.463037 | 1201.236486 | 7.814735 | |||||||
10 | 3 | 2.854054 | 350.378752 | 1137.424946 | 7.486254 | |||||||
10 | 4 | 2.889178 | 346.119225 | 1205.458641 | 7.488489 | |||||||
10 | 5 | 2.849271 | 350.966930 | 1258.634806 | 7.556528 | |||||||
10 | 6 | 2.862804 | 349.307895 | 1127.643108 | 7.340252 | |||||||
10 | 7 | 2.872507 | 348.127961 | 1195.940971 | 7.396042 | |||||||
10 | 8 | 2.848825 | 351.021886 | 1144.015312 | 7.435232 | |||||||
10 | 9 | 2.856191 | 350.116611 | 1192.873001 | 7.433087 | |||||||
8 | 2 | True | 640 | 640 | 10 | 0 | 2.837015 | 352.483124 | 1195.983171 | 6.284982 | ||
10 | 1 | 2.832456 | 353.050530 | 1168.994665 | 6.403863 | |||||||
10 | 2 | 2.823737 | 354.140669 | 1218.814135 | 6.399363 | |||||||
10 | 3 | 2.810910 | 355.756640 | 1235.333920 | 6.492764 | |||||||
10 | 4 | 2.829624 | 353.403866 | 1225.069523 | 6.618798 | |||||||
10 | 5 | 2.794465 | 357.850224 | 1211.092949 | 6.317213 | |||||||
10 | 6 | 2.812321 | 355.578184 | 1205.430984 | 6.580472 | |||||||
10 | 7 | 2.820940 | 354.491740 | 1201.059580 | 6.551847 | |||||||
10 | 8 | 2.806979 | 356.254905 | 1186.581135 | 6.576344 | |||||||
10 | 9 | 2.821171 | 354.462683 | 1192.502022 | 6.348789 | |||||||
16 | 2 | True | 640 | 640 | 10 | 0 | 2.813172 | 355.470613 | 1164.383173 | 6.226808 | ||
10 | 1 | 2.818235 | 354.831964 | 1223.844290 | 6.216079 | |||||||
10 | 2 | 2.810229 | 355.842948 | 1199.043274 | 6.146997 | |||||||
10 | 3 | 2.802453 | 356.830269 | 1204.602718 | 6.347194 | |||||||
10 | 4 | 2.784725 | 359.101936 | 1191.951036 | 6.114006 | |||||||
10 | 5 | 2.806251 | 356.347278 | 1238.991499 | 6.278954 | |||||||
10 | 6 | 2.802616 | 356.809527 | 1217.591047 | 6.227031 | |||||||
10 | 7 | 2.801952 | 356.894091 | 1185.748577 | 6.277829 | |||||||
10 | 8 | 2.807754 | 356.156498 | 1172.047138 | 6.207116 | |||||||
10 | 9 | 2.806592 | 356.304035 | 1185.555696 | 6.203011 | |||||||
32 | 2 | True | 640 | 640 | 10 | 0 | 2.798054 | 357.391268 | 2438.719749 | 5.896248 | ||
10 | 1 | 2.807195 | 356.227458 | 1187.539339 | 5.959757 | |||||||
10 | 2 | 2.796749 | 357.558042 | 1222.377062 | 5.879760 | |||||||
10 | 3 | 2.799535 | 357.202135 | 1218.173742 | 5.875945 | |||||||
10 | 4 | 2.804346 | 356.589369 | 1235.699415 | 5.910259 | |||||||
10 | 5 | 2.789166 | 358.530104 | 1222.545624 | 5.984668 | |||||||
10 | 6 | 2.789829 | 358.444877 | 1208.798170 | 5.984273 | |||||||
10 | 7 | 2.796627 | 357.573621 | 1180.090189 | 5.946502 | |||||||
10 | 8 | 2.794275 | 357.874520 | 1225.750208 | 5.948119 | |||||||
10 | 9 | 2.797504 | 357.461505 | 1233.389139 | 6.108604 | |||||||
cpu-prebuilt | 1 | 2 | True | 640 | 640 | 10 | 0 | 2.855453 | 350.207090 | 2278.793573 | 9.891272 | |
10 | 1 | 2.954680 | 338.446140 | 1129.206181 | 9.652257 | |||||||
10 | 2 | 2.889051 | 346.134424 | 1142.500162 | 9.572744 | |||||||
10 | 3 | 2.922671 | 342.152834 | 1112.239361 | 9.393334 | |||||||
10 | 4 | 2.902564 | 344.522953 | 1125.231028 | 9.726524 | |||||||
10 | 5 | 2.850115 | 350.862980 | 1139.945984 | 9.559512 | |||||||
10 | 6 | 2.867265 | 348.764420 | 1113.990545 | 9.485006 | |||||||
10 | 7 | 2.847977 | 351.126432 | 1118.859053 | 9.380341 | |||||||
10 | 8 | 2.846104 | 351.357460 | 1108.821630 | 9.745359 | |||||||
10 | 9 | 2.880664 | 347.142220 | 1126.899481 | 9.636045 | |||||||
2 | 2 | True | 640 | 640 | 10 | 0 | 2.878353 | 347.420931 | 1111.602306 | 7.814884 | ||
10 | 1 | 2.882036 | 346.976876 | 1120.844841 | 7.746935 | |||||||
10 | 2 | 2.843334 | 351.699829 | 1121.196508 | 7.841945 | |||||||
10 | 3 | 2.875354 | 347.783208 | 1135.895967 | 8.069575 | |||||||
10 | 4 | 2.888179 | 346.238971 | 1108.161211 | 7.781208 | |||||||
10 | 5 | 2.850747 | 350.785255 | 1180.108547 | 7.913172 | |||||||
10 | 6 | 2.910487 | 343.585134 | 1111.355066 | 7.823527 | |||||||
10 | 7 | 2.870341 | 348.390698 | 1114.764690 | 7.639170 | |||||||
10 | 8 | 2.879936 | 347.229958 | 1117.313623 | 7.627785 | |||||||
10 | 9 | 2.857527 | 349.952936 | 1119.010687 | 7.763743 | |||||||
4 | 2 | True | 640 | 640 | 10 | 0 | 2.815198 | 355.214775 | 1127.735138 | 7.499129 | ||
10 | 1 | 2.859160 | 349.753082 | 1123.138428 | 7.436484 | |||||||
10 | 2 | 2.852198 | 350.606740 | 1103.125572 | 7.412642 | |||||||
10 | 3 | 2.856863 | 350.034297 | 1115.490675 | 7.509857 | |||||||
10 | 4 | 2.804357 | 356.588006 | 1113.413334 | 7.386327 | |||||||
10 | 5 | 2.821205 | 354.458451 | 1123.439074 | 7.423639 | |||||||
10 | 6 | 2.833225 | 352.954626 | 1111.227512 | 7.583082 | |||||||
10 | 7 | 2.857581 | 349.946320 | 1113.034725 | 7.508188 | |||||||
10 | 8 | 2.855387 | 350.215197 | 1134.685278 | 8.161485 | |||||||
10 | 9 | 2.814018 | 355.363786 | 1095.266342 | 7.439435 | |||||||
8 | 2 | True | 640 | 640 | 10 | 0 | 2.789838 | 358.443707 | 1118.631601 | 6.431282 | ||
10 | 1 | 2.820658 | 354.527265 | 1109.792948 | 6.465271 | |||||||
10 | 2 | 2.806657 | 356.295764 | 1105.580330 | 6.383821 | |||||||
10 | 3 | 2.811476 | 355.684996 | 1129.949808 | 6.376565 | |||||||
10 | 4 | 2.792511 | 358.100593 | 1101.967335 | 6.407395 | |||||||
10 | 5 | 2.801499 | 356.951714 | 1119.222879 | 6.572589 | |||||||
10 | 6 | 2.804273 | 356.598675 | 1107.131481 | 6.362662 | |||||||
10 | 7 | 2.794106 | 357.896268 | 1120.184898 | 6.467849 | |||||||
10 | 8 | 2.787627 | 358.728081 | 1100.586653 | 6.664187 | |||||||
10 | 9 | 2.806029 | 356.375545 | 1097.465277 | 6.390840 | |||||||
16 | 2 | True | 640 | 640 | 10 | 0 | 2.793312 | 357.997969 | 1117.201328 | 6.260753 | ||
10 | 1 | 2.787269 | 358.774066 | 1137.892246 | 6.353207 | |||||||
10 | 2 | 2.775893 | 360.244483 | 1107.661009 | 6.194562 | |||||||
10 | 3 | 2.795524 | 357.714742 | 1106.746435 | 6.221645 | |||||||
10 | 4 | 2.789867 | 358.440027 | 1113.170147 | 6.227575 | |||||||
10 | 5 | 2.785558 | 358.994484 | 1116.304398 | 6.189026 | |||||||
10 | 6 | 2.782097 | 359.441057 | 1177.857637 | 6.233983 | |||||||
10 | 7 | 2.777166 | 360.079348 | 1109.665394 | 6.439984 | |||||||
10 | 8 | 2.774922 | 360.370502 | 1112.155676 | 6.156623 | |||||||
10 | 9 | 2.779182 | 359.818116 | 1106.245518 | 6.240182 | |||||||
32 | 2 | True | 640 | 640 | 10 | 0 | 2.793304 | 357.999019 | 1118.134022 | 5.916126 | ||
10 | 1 | 2.784916 | 359.077275 | 1106.137037 | 5.865730 | |||||||
10 | 2 | 2.783606 | 359.246209 | 1111.650705 | 5.980566 | |||||||
10 | 3 | 2.787308 | 358.769089 | 1121.110439 | 5.964067 | |||||||
10 | 4 | 2.775340 | 360.316262 | 1107.404470 | 5.879041 | |||||||
10 | 5 | 2.783919 | 359.205842 | 1092.256308 | 5.947400 | |||||||
10 | 6 | 2.781490 | 359.519571 | 1114.127398 | 6.119121 | |||||||
10 | 7 | 2.769306 | 361.101329 | 1105.468512 | 5.958006 | |||||||
10 | 8 | 2.776802 | 360.126570 | 1110.611677 | 5.901009 | |||||||
10 | 9 | 2.777269 | 360.065982 | 1107.602119 | 5.951378 | |||||||
cuda | 1 | 2 | True | 640 | 640 | 10 | 0 | 15.044780 | 66.468239 | 1098.026752 | 9.421945 | |
10 | 1 | 15.477536 | 64.609766 | 1129.821777 | 9.449124 | |||||||
10 | 2 | 14.993473 | 66.695690 | 1105.736256 | 9.390235 | |||||||
10 | 3 | 14.742047 | 67.833185 | 1108.495235 | 9.438276 | |||||||
10 | 4 | 15.425056 | 64.829588 | 1129.258633 | 9.686470 | |||||||
10 | 5 | 15.192460 | 65.822124 | 1117.984056 | 9.646535 | |||||||
10 | 6 | 14.797803 | 67.577600 | 1102.870703 | 9.317398 | |||||||
10 | 7 | 15.038253 | 66.497087 | 1133.430004 | 9.444475 | |||||||
10 | 8 | 15.015265 | 66.598892 | 1104.692459 | 9.422898 | |||||||
10 | 9 | 15.172181 | 65.910101 | 1112.380028 | 9.325027 | |||||||
2 | 2 | True | 640 | 640 | 10 | 0 | 17.788794 | 56.215167 | 1117.373943 | 7.849932 | ||
10 | 1 | 17.869584 | 55.961013 | 1113.932133 | 7.669449 | |||||||
10 | 2 | 17.461570 | 57.268620 | 1129.554510 | 7.846773 | |||||||
10 | 3 | 17.505369 | 57.125330 | 1125.203371 | 7.897556 | |||||||
10 | 4 | 17.872325 | 55.952430 | 1120.651484 | 7.834733 | |||||||
10 | 5 | 17.840814 | 56.051254 | 1126.897812 | 7.941365 | |||||||
10 | 6 | 17.768145 | 56.280494 | 1131.600618 | 7.722080 | |||||||
10 | 7 | 17.404943 | 57.454944 | 1110.110521 | 7.553518 | |||||||
10 | 8 | 17.549720 | 56.980968 | 1103.447437 | 7.722795 | |||||||
10 | 9 | 17.620128 | 56.753278 | 1129.095316 | 7.849455 | |||||||
4 | 2 | True | 640 | 640 | 10 | 0 | 19.009631 | 52.604914 | 1105.010509 | 7.283628 | ||
10 | 1 | 19.646119 | 50.900638 | 1117.938995 | 7.447034 | |||||||
10 | 2 | 19.069981 | 52.438438 | 1107.816696 | 7.761061 | |||||||
10 | 3 | 19.608669 | 50.997853 | 1134.235382 | 7.297724 | |||||||
10 | 4 | 19.501497 | 51.278114 | 1118.249416 | 7.535100 | |||||||
10 | 5 | 19.580863 | 51.070273 | 1114.309549 | 7.481039 | |||||||
10 | 6 | 19.669613 | 50.839841 | 1120.993614 | 7.478744 | |||||||
10 | 7 | 19.541293 | 51.173687 | 1113.941669 | 7.593006 | |||||||
10 | 8 | 19.117287 | 52.308679 | 1117.832422 | 7.227778 | |||||||
10 | 9 | 19.412457 | 51.513314 | 1126.186371 | 7.310241 | |||||||
8 | 2 | True | 640 | 640 | 10 | 0 | 19.876099 | 50.311685 | 1117.755175 | 6.379679 | ||
10 | 1 | 19.936954 | 50.158113 | 1116.433382 | 6.557599 | |||||||
10 | 2 | 20.212125 | 49.475253 | 1117.033720 | 6.511047 | |||||||
10 | 3 | 20.008964 | 49.977601 | 1131.582737 | 6.359369 | |||||||
10 | 4 | 19.981511 | 50.046265 | 1133.501291 | 6.507501 | |||||||
10 | 5 | 19.702229 | 50.755680 | 1121.912003 | 6.450221 | |||||||
10 | 6 | 19.764490 | 50.595790 | 1111.566782 | 6.495044 | |||||||
10 | 7 | 19.619205 | 50.970465 | 1114.754200 | 6.510496 | |||||||
10 | 8 | 19.858724 | 50.355703 | 1116.500139 | 6.394997 | |||||||
10 | 9 | 19.596427 | 51.029712 | 1126.966000 | 6.479204 | |||||||
16 | 2 | True | 640 | 640 | 10 | 0 | 21.172854 | 47.230288 | 1117.800713 | 6.400287 | ||
10 | 1 | 21.047138 | 47.512397 | 1107.041359 | 6.163068 | |||||||
10 | 2 | 20.762853 | 48.162937 | 1124.565840 | 6.408639 | |||||||
10 | 3 | 20.749295 | 48.194408 | 1126.641273 | 6.126396 | |||||||
10 | 4 | 21.492133 | 46.528652 | 1130.404949 | 6.149955 | |||||||
10 | 5 | 21.321513 | 46.900988 | 1110.189438 | 6.229348 | |||||||
10 | 6 | 21.329177 | 46.884134 | 1120.916843 | 6.235205 | |||||||
10 | 7 | 21.451538 | 46.616703 | 1117.917299 | 6.182045 | |||||||
10 | 8 | 21.151159 | 47.278732 | 1129.104376 | 6.296031 | |||||||
10 | 9 | 20.991265 | 47.638863 | 1125.458479 | 6.268002 | |||||||
32 | 2 | True | 640 | 640 | 10 | 0 | 21.131578 | 47.322541 | 1135.979176 | 5.965155 | ||
10 | 1 | 21.439374 | 46.643153 | 1124.232292 | 6.127946 | |||||||
10 | 2 | 21.342394 | 46.855099 | 1130.904198 | 5.932517 | |||||||
10 | 3 | 21.092555 | 47.410093 | 1113.237143 | 5.863123 | |||||||
10 | 4 | 20.837156 | 47.991194 | 1138.520241 | 5.897202 | |||||||
10 | 5 | 21.044528 | 47.518291 | 1127.521992 | 5.988065 | |||||||
10 | 6 | 21.254780 | 47.048241 | 1127.163410 | 5.989894 | |||||||
10 | 7 | 21.061998 | 47.478877 | 1136.384249 | 5.897298 | |||||||
10 | 8 | 21.253932 | 47.050118 | 1131.122589 | 6.049484 | |||||||
10 | 9 | 21.122978 | 47.341809 | 1120.296955 | 5.881034 | |||||||
tensorrt | 1 | 2 | True | 640 | 640 | 10 | 0 | 15.570907 | 64.222336 | 21729.543209 | 9.394884 | |
10 | 1 | 16.074873 | 62.208891 | 21746.314526 | 9.488940 | |||||||
10 | 2 | 16.338304 | 61.205864 | 21647.392273 | 9.246588 | |||||||
10 | 3 | 16.071054 | 62.223673 | 21447.484493 | 9.172678 | |||||||
10 | 4 | 16.122947 | 62.023401 | 21772.876501 | 9.240508 | |||||||
10 | 5 | 16.205862 | 61.706066 | 21609.282255 | 9.258628 | |||||||
10 | 6 | 16.713970 | 59.830189 | 21890.000582 | 9.244323 | |||||||
10 | 7 | 15.914824 | 62.834501 | 21275.634527 | 9.418249 | |||||||
10 | 8 | 16.356207 | 61.138868 | 21520.533800 | 9.368420 | |||||||
10 | 9 | 16.302551 | 61.340094 | 21316.932917 | 9.224415 | |||||||
2 | 2 | True | 640 | 640 | 10 | 0 | 18.955122 | 52.756190 | 23919.415712 | 7.594585 | ||
10 | 1 | 18.540696 | 53.935409 | 23624.637127 | 7.618606 | |||||||
10 | 2 | 18.921430 | 52.850127 | 23499.101639 | 7.565439 | |||||||
10 | 3 | 18.671433 | 53.557754 | 23391.526222 | 7.526278 | |||||||
10 | 4 | 18.196231 | 54.956436 | 23598.426342 | 7.588744 | |||||||
10 | 5 | 18.777005 | 53.256631 | 23855.793238 | 7.571578 | |||||||
10 | 6 | 18.793537 | 53.209782 | 23437.061310 | 7.582605 | |||||||
10 | 7 | 18.557061 | 53.887844 | 23561.732769 | 7.421434 | |||||||
10 | 8 | 18.949341 | 52.772284 | 23810.215235 | 7.553399 | |||||||
10 | 9 | 18.621654 | 53.700924 | 23574.730396 | 7.589579 | |||||||
4 | 2 | True | 640 | 640 | 10 | 0 | 20.415578 | 48.982203 | 13964.055777 | 7.495016 | ||
10 | 1 | 20.558223 | 48.642337 | 13821.491480 | 7.330626 | |||||||
10 | 2 | 20.337696 | 49.169779 | 13901.971102 | 7.315248 | |||||||
10 | 3 | 20.208668 | 49.483716 | 13633.214474 | 7.559001 | |||||||
10 | 4 | 20.480075 | 48.827946 | 13880.959511 | 7.485181 | |||||||
10 | 5 | 20.495311 | 48.791647 | 13754.168272 | 7.535517 | |||||||
10 | 6 | 20.423531 | 48.963130 | 13678.659678 | 7.557243 | |||||||
10 | 7 | 20.295060 | 49.273074 | 13856.650591 | 7.384658 | |||||||
10 | 8 | 20.356598 | 49.124122 | 13791.505575 | 7.390469 | |||||||
10 | 9 | 20.404430 | 49.008965 | 13819.857597 | 7.358462 | |||||||
8 | 2 | True | 640 | 640 | 10 | 0 | 21.386117 | 46.759307 | 15457.005501 | 6.325573 | ||
10 | 1 | 20.925588 | 47.788382 | 15310.769081 | 6.405577 | |||||||
10 | 2 | 21.052784 | 47.499657 | 15355.959654 | 6.333739 | |||||||
10 | 3 | 20.773098 | 48.139185 | 15436.644316 | 6.615311 | |||||||
10 | 4 | 20.757895 | 48.174441 | 15398.816586 | 6.397918 | |||||||
10 | 5 | 20.607792 | 48.525333 | 15496.545076 | 6.420434 | |||||||
10 | 6 | 20.722935 | 48.255712 | 15283.169031 | 6.394431 | |||||||
10 | 7 | 20.734371 | 48.229098 | 15375.441313 | 6.582066 | |||||||
10 | 8 | 21.183180 | 47.207266 | 15395.080090 | 6.349027 | |||||||
10 | 9 | 21.018878 | 47.576278 | 15299.387217 | 6.549969 | |||||||
16 | 2 | True | 640 | 640 | 10 | 0 | 21.361222 | 46.813801 | 18176.128626 | 6.257810 | ||
10 | 1 | 21.380230 | 46.772182 | 18112.614870 | 6.449446 | |||||||
10 | 2 | 21.488789 | 46.535894 | 18246.995211 | 6.438613 | |||||||
10 | 3 | 21.359951 | 46.816587 | 18380.831480 | 6.129384 | |||||||
10 | 4 | 20.977000 | 47.671258 | 18351.099253 | 6.451964 | |||||||
10 | 5 | 21.244209 | 47.071651 | 18284.997940 | 6.177515 | |||||||
10 | 6 | 21.471016 | 46.574414 | 18289.912701 | 6.147586 | |||||||
10 | 7 | 21.308548 | 46.929523 | 18348.347902 | 6.401733 | |||||||
10 | 8 | 20.823155 | 48.023462 | 18243.337631 | 6.366849 | |||||||
10 | 9 | 21.180365 | 47.213539 | 18333.791256 | 6.314740 | |||||||
32 | 2 | True | 640 | 640 | 10 | 0 | 21.191782 | 47.188103 | 24676.125288 | 6.090987 | ||
10 | 1 | 21.083311 | 47.430880 | 24752.432585 | 5.904481 | |||||||
10 | 2 | 21.125678 | 47.335759 | 24673.513651 | 5.980283 | |||||||
10 | 3 | 21.127640 | 47.331363 | 24676.829815 | 5.923975 | |||||||
10 | 4 | 21.269877 | 47.014847 | 24702.081442 | 5.911347 | |||||||
10 | 5 | 21.000507 | 47.617897 | 24648.655176 | 5.978446 | |||||||
10 | 6 | 21.364272 | 46.807118 | 24671.283007 | 5.951062 | |||||||
10 | 7 | 21.282035 | 46.987988 | 24687.311172 | 5.950600 | |||||||
10 | 8 | 20.938467 | 47.758989 | 24765.106678 | 6.044965 | |||||||
10 | 9 | 21.084040 | 47.429241 | 24839.820147 | 5.940046 | |||||||
tensorrt-dynamic | 1 | 2 | True | 640 | 640 | 10 | 0 | 19.510659 | 51.254034 | 8519.782305 | 9.186983 | |
10 | 1 | 19.327788 | 51.738977 | 8500.771523 | 9.692311 | |||||||
10 | 2 | 19.465386 | 51.373243 | 8400.408030 | 9.241462 | |||||||
10 | 3 | 20.335329 | 49.175501 | 8444.699049 | 9.147525 | |||||||
10 | 4 | 19.936516 | 50.159216 | 8430.749416 | 9.275198 | |||||||
10 | 5 | 18.953537 | 52.760601 | 8339.345455 | 9.375453 | |||||||
10 | 6 | 19.509933 | 51.255941 | 8486.658812 | 9.344339 | |||||||
10 | 7 | 19.839855 | 50.403595 | 8455.882311 | 9.330869 | |||||||
10 | 8 | 19.872755 | 50.320148 | 8421.129942 | 9.277582 | |||||||
10 | 9 | 20.354079 | 49.130201 | 8518.504620 | 9.328961 | |||||||
2 | 2 | True | 640 | 640 | 10 | 0 | 22.375349 | 44.692039 | 8460.820913 | 7.580161 | ||
10 | 1 | 22.628919 | 44.191241 | 8456.921101 | 7.472217 | |||||||
10 | 2 | 21.955511 | 45.546651 | 8441.268921 | 7.547975 | |||||||
10 | 3 | 22.382514 | 44.677734 | 8476.423502 | 7.572532 | |||||||
10 | 4 | 22.365625 | 44.711471 | 8486.182928 | 7.580638 | |||||||
10 | 5 | 21.967873 | 45.521021 | 8448.971510 | 7.503867 | |||||||
10 | 6 | 22.394703 | 44.653416 | 8465.628386 | 7.618845 | |||||||
10 | 7 | 22.409241 | 44.624448 | 8421.254396 | 7.518291 | |||||||
10 | 8 | 21.862299 | 45.740843 | 8426.948309 | 7.569313 | |||||||
10 | 9 | 22.333352 | 44.776082 | 8466.913939 | 7.509351 | |||||||
4 | 2 | True | 640 | 640 | 10 | 0 | 23.920294 | 41.805506 | 8466.913700 | 7.536948 | ||
10 | 1 | 23.513210 | 42.529285 | 8473.692417 | 7.440627 | |||||||
10 | 2 | 23.655570 | 42.273343 | 8480.237722 | 7.608294 | |||||||
10 | 3 | 23.764469 | 42.079628 | 8435.468674 | 7.287860 | |||||||
10 | 4 | 23.972588 | 41.714311 | 8399.927855 | 7.281214 | |||||||
10 | 5 | 24.284995 | 41.177690 | 8280.506611 | 7.427931 | |||||||
10 | 6 | 23.890456 | 41.857719 | 8474.812031 | 7.368922 | |||||||
10 | 7 | 23.802365 | 42.012632 | 8443.987608 | 7.532328 | |||||||
10 | 8 | 23.798989 | 42.018592 | 8468.756676 | 7.303774 | |||||||
10 | 9 | 24.087061 | 41.516066 | 8756.255865 | 7.281870 | |||||||
8 | 2 | True | 640 | 640 | 10 | 0 | 24.149400 | 41.408896 | 8371.308565 | 6.414413 | ||
10 | 1 | 24.079766 | 41.528642 | 8380.914211 | 6.348655 | |||||||
10 | 2 | 23.011062 | 43.457359 | 8537.108660 | 6.313503 | |||||||
10 | 3 | 23.971218 | 41.716695 | 8319.250345 | 6.473899 | |||||||
10 | 4 | 23.989573 | 41.684777 | 8341.042280 | 6.289378 | |||||||
10 | 5 | 24.223966 | 41.281432 | 8475.624800 | 6.320685 | |||||||
10 | 6 | 24.313308 | 41.129738 | 8340.878010 | 6.365463 | |||||||
10 | 7 | 24.019264 | 41.633248 | 8514.063358 | 6.458774 | |||||||
10 | 8 | 24.014709 | 41.641146 | 8560.509443 | 6.431967 | |||||||
10 | 9 | 24.146463 | 41.413933 | 8319.505215 | 6.476253 | |||||||
16 | 2 | True | 640 | 640 | 10 | 0 | 24.324447 | 41.110903 | 8523.086071 | 6.373674 | ||
10 | 1 | 23.775641 | 42.059854 | 8404.950380 | 6.176323 | |||||||
10 | 2 | 24.280584 | 41.185170 | 8522.124052 | 6.459951 | |||||||
10 | 3 | 24.073271 | 41.539848 | 8431.672335 | 6.225787 | |||||||
10 | 4 | 24.300199 | 41.151926 | 8449.722290 | 6.536342 | |||||||
10 | 5 | 24.594776 | 40.659040 | 8488.881826 | 6.295867 | |||||||
10 | 6 | 24.248246 | 41.240096 | 8375.000477 | 6.217360 | |||||||
10 | 7 | 24.075231 | 41.536465 | 8429.190874 | 6.083399 | |||||||
10 | 8 | 23.958176 | 41.739404 | 8284.771442 | 6.156728 | |||||||
10 | 9 | 23.548903 | 42.464823 | 8354.423761 | 6.275095 | |||||||
32 | 2 | True | 640 | 640 | 10 | 0 | 24.111050 | 41.474760 | 8494.910240 | 5.925834 | ||
10 | 1 | 23.958574 | 41.738711 | 8489.223480 | 5.846027 | |||||||
10 | 2 | 23.979064 | 41.703045 | 8476.033926 | 6.055284 | |||||||
10 | 3 | 24.214622 | 41.297361 | 8539.590120 | 5.996846 | |||||||
10 | 4 | 23.922038 | 41.802458 | 8418.959856 | 6.071333 | |||||||
10 | 5 | 24.738744 | 40.422425 | 8410.470009 | 5.948696 | |||||||
10 | 6 | 23.969677 | 41.719377 | 8425.133944 | 6.118607 | |||||||
10 | 7 | 23.967135 | 41.723803 | 8452.291250 | 6.080065 | |||||||
10 | 8 | 24.044863 | 41.588925 | 8353.692293 | 5.913790 | |||||||
10 | 9 | 24.059470 | 41.563675 | 8362.168312 | 5.903147 | |||||||
ssdlite-mobilenet-v2 | cpu | 1 | 2 | True | 300 | 300 | 10 | 0 | 39.685341 | 25.198221 | 862.735510 | 10.295510 |
10 | 1 | 38.059108 | 26.274920 | 875.326633 | 10.284185 | |||||||
10 | 2 | 38.016678 | 26.304245 | 850.307703 | 9.809732 | |||||||
10 | 3 | 37.161473 | 26.909590 | 848.699808 | 9.995341 | |||||||
10 | 4 | 36.292639 | 27.553797 | 815.796137 | 9.835124 | |||||||
10 | 5 | 36.992680 | 27.032375 | 855.764389 | 10.437012 | |||||||
10 | 6 | 36.585465 | 27.333260 | 823.440313 | 9.884477 | |||||||
10 | 7 | 36.976048 | 27.044535 | 863.843441 | 10.589600 | |||||||
10 | 8 | 37.688058 | 26.533604 | 842.252016 | 10.356188 | |||||||
10 | 9 | 36.079414 | 27.716637 | 836.422205 | 10.013103 | |||||||
2 | 2 | True | 300 | 300 | 10 | 0 | 50.425035 | 19.831419 | 848.634005 | 8.233964 | ||
10 | 1 | 50.965145 | 19.621253 | 856.149912 | 8.628905 | |||||||
10 | 2 | 52.640348 | 18.996835 | 875.950813 | 8.672178 | |||||||
10 | 3 | 51.905527 | 19.265771 | 846.791983 | 8.576155 | |||||||
10 | 4 | 49.655538 | 20.138741 | 880.769253 | 8.548200 | |||||||
10 | 5 | 51.085569 | 19.575000 | 873.834133 | 8.720458 | |||||||
10 | 6 | 53.114307 | 18.827319 | 850.406885 | 8.596361 | |||||||
10 | 7 | 52.699544 | 18.975496 | 877.855301 | 8.659899 | |||||||
10 | 8 | 50.205031 | 19.918323 | 814.801931 | 8.282781 | |||||||
10 | 9 | 51.838489 | 19.290686 | 855.423450 | 8.524060 | |||||||
4 | 2 | True | 300 | 300 | 10 | 0 | 58.231374 | 17.172873 | 860.884905 | 8.060366 | ||
10 | 1 | 54.661197 | 18.294513 | 867.341518 | 8.239925 | |||||||
10 | 2 | 56.616855 | 17.662585 | 859.322309 | 8.227885 | |||||||
10 | 3 | 55.873581 | 17.897546 | 854.336262 | 8.497715 | |||||||
10 | 4 | 55.702728 | 17.952442 | 860.478878 | 8.361101 | |||||||
10 | 5 | 57.902385 | 17.270446 | 838.958502 | 8.259237 | |||||||
10 | 6 | 55.431452 | 18.040299 | 866.113901 | 8.402050 | |||||||
10 | 7 | 55.038484 | 18.169105 | 873.219967 | 8.160889 | |||||||
10 | 8 | 59.594901 | 16.779959 | 866.595745 | 8.166939 | |||||||
10 | 9 | 56.829537 | 17.596483 | 864.920139 | 8.304119 | |||||||
8 | 2 | True | 300 | 300 | 10 | 0 | 60.394994 | 16.557664 | 847.701073 | 6.887943 | ||
10 | 1 | 65.184488 | 15.341073 | 856.268167 | 7.110670 | |||||||
10 | 2 | 64.526389 | 15.497535 | 883.671045 | 6.978080 | |||||||
10 | 3 | 63.105098 | 15.846580 | 853.388071 | 7.361040 | |||||||
10 | 4 | 61.999715 | 16.129106 | 854.346037 | 6.790102 | |||||||
10 | 5 | 60.889048 | 16.423315 | 873.489618 | 6.929606 | |||||||
10 | 6 | 63.257614 | 15.808374 | 860.797882 | 6.799281 | |||||||
10 | 7 | 63.593540 | 15.724868 | 873.976231 | 6.884992 | |||||||
10 | 8 | 63.919900 | 15.644580 | 800.388098 | 6.886363 | |||||||
10 | 9 | 65.018141 | 15.380323 | 857.316971 | 6.874159 | |||||||
16 | 2 | True | 300 | 300 | 10 | 0 | 60.372718 | 16.563773 | 876.538992 | 6.611742 | ||
10 | 1 | 62.656143 | 15.960127 | 845.313787 | 7.245757 | |||||||
10 | 2 | 60.175827 | 16.617969 | 880.301714 | 6.795049 | |||||||
10 | 3 | 62.156023 | 16.088545 | 841.965914 | 6.593056 | |||||||
10 | 4 | 61.231944 | 16.331345 | 851.051569 | 6.575733 | |||||||
10 | 5 | 60.472601 | 16.536415 | 874.032497 | 6.778210 | |||||||
10 | 6 | 62.592794 | 15.976280 | 877.879620 | 6.638654 | |||||||
10 | 7 | 61.218594 | 16.334906 | 871.866226 | 6.617002 | |||||||
10 | 8 | 61.320850 | 16.307667 | 857.220888 | 6.511718 | |||||||
10 | 9 | 61.836840 | 16.171589 | 838.464499 | 6.742433 | |||||||
32 | 2 | True | 300 | 300 | 10 | 0 | 60.648523 | 16.488448 | 1003.379822 | 6.257281 | ||
10 | 1 | 62.038518 | 16.119018 | 858.625889 | 6.314501 | |||||||
10 | 2 | 61.297690 | 16.313829 | 870.803595 | 6.263062 | |||||||
10 | 3 | 61.261961 | 16.323343 | 878.454447 | 6.259497 | |||||||
10 | 4 | 58.678264 | 17.042086 | 857.612133 | 6.264176 | |||||||
10 | 5 | 60.631180 | 16.493164 | 824.439287 | 6.288312 | |||||||
10 | 6 | 60.984496 | 16.397610 | 827.073097 | 6.329279 | |||||||
10 | 7 | 60.128515 | 16.631044 | 834.861994 | 6.248549 | |||||||
10 | 8 | 59.084872 | 16.924806 | 796.676874 | 6.223783 | |||||||
10 | 9 | 60.305743 | 16.582169 | 817.299366 | 6.313596 | |||||||
cpu-prebuilt | 1 | 2 | True | 300 | 300 | 10 | 0 | 37.004102 | 27.024031 | 949.477911 | 9.892106 | |
10 | 1 | 37.368067 | 26.760817 | 782.538652 | 10.296226 | |||||||
10 | 2 | 37.597519 | 26.597500 | 761.238337 | 10.153770 | |||||||
10 | 3 | 37.601901 | 26.594400 | 777.010679 | 10.021806 | |||||||
10 | 4 | 38.062907 | 26.272297 | 765.479803 | 9.991169 | |||||||
10 | 5 | 38.547045 | 25.942326 | 772.315025 | 10.000944 | |||||||
10 | 6 | 36.258755 | 27.579546 | 783.654451 | 10.087013 | |||||||
10 | 7 | 37.603586 | 26.593208 | 770.739794 | 9.885430 | |||||||
10 | 8 | 38.028052 | 26.296377 | 782.424688 | 9.866834 | |||||||
10 | 9 | 36.295151 | 27.551889 | 792.186737 | 10.169029 | |||||||
2 | 2 | True | 300 | 300 | 10 | 0 | 48.991724 | 20.411611 | 785.945415 | 8.294463 | ||
10 | 1 | 49.559901 | 20.177603 | 859.849215 | 8.650362 | |||||||
10 | 2 | 48.770410 | 20.504236 | 766.938686 | 8.291662 | |||||||
10 | 3 | 49.186777 | 20.330667 | 786.423683 | 8.145630 | |||||||
10 | 4 | 48.470012 | 20.631313 | 862.405300 | 8.572221 | |||||||
10 | 5 | 49.019494 | 20.400047 | 780.265808 | 8.450449 | |||||||
10 | 6 | 50.361462 | 19.856453 | 768.947363 | 8.481145 | |||||||
10 | 7 | 49.089775 | 20.370841 | 774.491072 | 8.264840 | |||||||
10 | 8 | 47.876630 | 20.887017 | 786.745787 | 8.256376 | |||||||
10 | 9 | 50.821876 | 19.676566 | 801.594973 | 8.289516 | |||||||
4 | 2 | True | 300 | 300 | 10 | 0 | 55.883445 | 17.894387 | 794.907331 | 7.973313 | ||
10 | 1 | 52.787923 | 18.943727 | 785.968304 | 8.051932 | |||||||
10 | 2 | 57.212673 | 17.478645 | 784.177780 | 8.001566 | |||||||
10 | 3 | 53.389477 | 18.730283 | 799.047709 | 8.024305 | |||||||
10 | 4 | 55.693113 | 17.955542 | 782.022476 | 8.064538 | |||||||
10 | 5 | 53.976752 | 18.526495 | 795.651436 | 8.258611 | |||||||
10 | 6 | 57.645739 | 17.347336 | 777.827501 | 7.873803 | |||||||
10 | 7 | 52.706497 | 18.972993 | 782.297850 | 8.054614 | |||||||
10 | 8 | 53.816768 | 18.581569 | 781.893015 | 7.929951 | |||||||
10 | 9 | 53.702729 | 18.621027 | 791.301727 | 7.836729 | |||||||
8 | 2 | True | 300 | 300 | 10 | 0 | 58.745708 | 17.022520 | 770.885468 | 6.994680 | ||
10 | 1 | 58.582426 | 17.069966 | 782.234907 | 6.892636 | |||||||
10 | 2 | 60.420768 | 16.550601 | 804.603100 | 7.039666 | |||||||
10 | 3 | 63.338453 | 15.788198 | 776.143074 | 6.763458 | |||||||
10 | 4 | 61.200115 | 16.339839 | 773.752689 | 6.763175 | |||||||
10 | 5 | 60.864749 | 16.429871 | 779.057026 | 6.774992 | |||||||
10 | 6 | 62.106324 | 16.101420 | 789.723873 | 6.877095 | |||||||
10 | 7 | 61.079354 | 16.372144 | 768.090725 | 6.792203 | |||||||
10 | 8 | 63.146901 | 15.836090 | 771.646738 | 7.009849 | |||||||
10 | 9 | 61.256425 | 16.324818 | 787.130833 | 6.843984 | |||||||
16 | 2 | True | 300 | 300 | 10 | 0 | 58.729256 | 17.027289 | 786.702633 | 6.566666 | ||
10 | 1 | 58.600279 | 17.064765 | 775.289297 | 6.510623 | |||||||
10 | 2 | 57.869381 | 17.280295 | 801.863432 | 6.936930 | |||||||
10 | 3 | 58.835426 | 16.996562 | 784.094810 | 6.589137 | |||||||
10 | 4 | 57.795620 | 17.302349 | 775.352240 | 6.557748 | |||||||
10 | 5 | 57.727956 | 17.322630 | 767.080784 | 6.591357 | |||||||
10 | 6 | 59.615441 | 16.774178 | 829.609156 | 6.648198 | |||||||
10 | 7 | 57.891795 | 17.273605 | 776.070118 | 6.593898 | |||||||
10 | 8 | 59.204161 | 16.890705 | 766.680241 | 6.543301 | |||||||
10 | 9 | 57.923675 | 17.264098 | 837.984800 | 6.583177 | |||||||
32 | 2 | True | 300 | 300 | 10 | 0 | 57.782930 | 17.306149 | 784.720898 | 6.350499 | ||
10 | 1 | 57.193657 | 17.484456 | 784.260035 | 6.251678 | |||||||
10 | 2 | 58.120374 | 17.205670 | 778.075695 | 6.204356 | |||||||
10 | 3 | 57.936727 | 17.260209 | 780.213118 | 6.225489 | |||||||
10 | 4 | 57.048188 | 17.529041 | 794.155359 | 6.290961 | |||||||
10 | 5 | 58.113252 | 17.207779 | 773.253918 | 6.246470 | |||||||
10 | 6 | 58.781315 | 17.012209 | 774.410248 | 6.380927 | |||||||
10 | 7 | 58.123168 | 17.204843 | 770.066977 | 6.393492 | |||||||
10 | 8 | 57.623787 | 17.353944 | 794.302940 | 6.217804 | |||||||
10 | 9 | 58.012679 | 17.237611 | 833.894014 | 6.635834 | |||||||
cuda | 1 | 2 | True | 300 | 300 | 10 | 0 | 32.349978 | 30.911922 | 789.393902 | 10.004997 | |
10 | 1 | 32.277533 | 30.981302 | 777.021646 | 9.960294 | |||||||
10 | 2 | 33.160485 | 30.156374 | 778.235674 | 9.951949 | |||||||
10 | 3 | 32.484773 | 30.783653 | 773.295403 | 9.849787 | |||||||
10 | 4 | 32.289460 | 30.969858 | 782.374382 | 9.889722 | |||||||
10 | 5 | 33.100035 | 30.211449 | 780.789375 | 9.934664 | |||||||
10 | 6 | 33.402650 | 29.937744 | 792.579651 | 9.874344 | |||||||
10 | 7 | 33.941364 | 29.462576 | 780.071735 | 10.011554 | |||||||
10 | 8 | 33.921874 | 29.479504 | 784.799099 | 9.832978 | |||||||
10 | 9 | 32.897534 | 30.397415 | 792.848825 | 9.998083 | |||||||
2 | 2 | True | 300 | 300 | 10 | 0 | 44.786537 | 22.328138 | 788.602829 | 8.304298 | ||
10 | 1 | 40.870994 | 24.467230 | 782.656431 | 8.443475 | |||||||
10 | 2 | 41.782387 | 23.933530 | 781.589985 | 8.288801 | |||||||
10 | 3 | 43.433234 | 23.023844 | 793.455124 | 8.127034 | |||||||
10 | 4 | 44.176609 | 22.636414 | 791.908979 | 8.200824 | |||||||
10 | 5 | 42.058491 | 23.776412 | 789.214134 | 7.984221 | |||||||
10 | 6 | 43.240916 | 23.126245 | 797.036409 | 8.341908 | |||||||
10 | 7 | 42.246582 | 23.670554 | 784.744978 | 8.341849 | |||||||
10 | 8 | 44.305638 | 22.570491 | 792.612791 | 8.268595 | |||||||
10 | 9 | 43.159046 | 23.170114 | 790.400267 | 8.097827 | |||||||
4 | 2 | True | 300 | 300 | 10 | 0 | 50.584978 | 19.768715 | 797.727823 | 8.020848 | ||
10 | 1 | 48.003205 | 20.831943 | 775.827408 | 7.975131 | |||||||
10 | 2 | 46.668974 | 21.427512 | 791.930914 | 7.946432 | |||||||
10 | 3 | 48.008424 | 20.829678 | 791.920185 | 7.830560 | |||||||
10 | 4 | 47.840998 | 20.902574 | 776.671886 | 8.027762 | |||||||
10 | 5 | 47.704558 | 20.962358 | 784.771681 | 8.086592 | |||||||
10 | 6 | 48.114714 | 20.783663 | 792.357206 | 7.941931 | |||||||
10 | 7 | 47.777646 | 20.930290 | 785.501957 | 7.936209 | |||||||
10 | 8 | 47.000006 | 21.276593 | 773.928642 | 8.145422 | |||||||
10 | 9 | 47.861606 | 20.893574 | 789.598465 | 8.004040 | |||||||
8 | 2 | True | 300 | 300 | 10 | 0 | 49.444806 | 20.224571 | 791.300058 | 6.731212 | ||
10 | 1 | 49.426816 | 20.231932 | 788.105965 | 6.797835 | |||||||
10 | 2 | 51.412283 | 19.450605 | 798.650742 | 7.010430 | |||||||
10 | 3 | 49.625942 | 20.150751 | 798.736334 | 6.831899 | |||||||
10 | 4 | 49.323283 | 20.274401 | 786.125898 | 6.808758 | |||||||
10 | 5 | 51.141161 | 19.553721 | 793.793678 | 6.724164 | |||||||
10 | 6 | 50.413292 | 19.836038 | 795.562744 | 6.924197 | |||||||
10 | 7 | 50.309436 | 19.876987 | 791.213989 | 6.806701 | |||||||
10 | 8 | 51.698558 | 19.342899 | 789.509296 | 6.778181 | |||||||
10 | 9 | 52.680183 | 18.982470 | 798.557997 | 6.741926 | |||||||
16 | 2 | True | 300 | 300 | 10 | 0 | 50.071265 | 19.971535 | 775.088072 | 6.526105 | ||
10 | 1 | 51.439750 | 19.440219 | 788.074493 | 6.713055 | |||||||
10 | 2 | 50.958334 | 19.623876 | 798.418999 | 6.875217 | |||||||
10 | 3 | 50.748355 | 19.705072 | 796.075106 | 6.591968 | |||||||
10 | 4 | 51.126668 | 19.559264 | 794.337988 | 6.549180 | |||||||
10 | 5 | 53.981311 | 18.524930 | 781.834364 | 6.682500 | |||||||
10 | 6 | 51.376701 | 19.464076 | 796.562195 | 6.605364 | |||||||
10 | 7 | 52.089203 | 19.197837 | 796.659946 | 6.516390 | |||||||
10 | 8 | 51.525138 | 19.408002 | 801.054716 | 6.619275 | |||||||
10 | 9 | 50.990199 | 19.611612 | 793.004751 | 6.594062 | |||||||
32 | 2 | True | 300 | 300 | 10 | 0 | 52.525603 | 19.038334 | 794.289351 | 6.252967 | ||
10 | 1 | 53.810231 | 18.583827 | 794.852257 | 6.505683 | |||||||
10 | 2 | 53.541330 | 18.677160 | 785.206079 | 6.416973 | |||||||
10 | 3 | 52.971238 | 18.878169 | 779.656410 | 6.322965 | |||||||
10 | 4 | 53.455948 | 18.706992 | 792.399883 | 6.244738 | |||||||
10 | 5 | 51.737299 | 19.328415 | 787.132978 | 6.224751 | |||||||
10 | 6 | 53.231684 | 18.785805 | 793.002367 | 6.631620 | |||||||
10 | 7 | 51.691490 | 19.345544 | 779.975653 | 6.219286 | |||||||
10 | 8 | 52.593215 | 19.013859 | 780.918360 | 6.271467 | |||||||
10 | 9 | 53.496430 | 18.692836 | 782.269716 | 6.598189 | |||||||
tensorrt | 1 | 2 | True | 300 | 300 | 10 | 0 | 35.050382 | 28.530359 | 35672.811985 | 9.877920 | |
10 | 1 | 37.707710 | 26.519775 | 35734.363079 | 9.876132 | |||||||
10 | 2 | 35.758896 | 27.965069 | 35356.230259 | 9.820700 | |||||||
10 | 3 | 35.530797 | 28.144598 | 35558.438778 | 9.880185 | |||||||
10 | 4 | 36.383938 | 27.484655 | 35570.314646 | 9.799600 | |||||||
10 | 5 | 35.633429 | 28.063536 | 35888.130188 | 9.905934 | |||||||
10 | 6 | 35.771705 | 27.955055 | 35514.756680 | 9.971023 | |||||||
10 | 7 | 35.799795 | 27.933121 | 35461.050272 | 9.771466 | |||||||
10 | 8 | 37.590780 | 26.602268 | 35439.099073 | 9.826541 | |||||||
10 | 9 | 37.125620 | 26.935577 | 35536.747932 | 9.871244 | |||||||
2 | 2 | True | 300 | 300 | 10 | 0 | 44.218991 | 22.614717 | 36102.570772 | 8.064449 | ||
10 | 1 | 43.894594 | 22.781849 | 35689.090729 | 8.099318 | |||||||
10 | 2 | 46.790018 | 21.372080 | 35965.830326 | 8.110583 | |||||||
10 | 3 | 46.000011 | 21.739125 | 36059.750080 | 8.101583 | |||||||
10 | 4 | 45.685605 | 21.888733 | 35974.194527 | 8.059144 | |||||||
10 | 5 | 45.064670 | 22.190332 | 35960.492134 | 8.215189 | |||||||
10 | 6 | 46.366907 | 21.567106 | 36009.477854 | 8.117616 | |||||||
10 | 7 | 42.498711 | 23.530126 | 35665.980339 | 8.049250 | |||||||
10 | 8 | 45.227458 | 22.110462 | 36006.569862 | 8.111775 | |||||||
10 | 9 | 45.155152 | 22.145867 | 36033.411980 | 8.205235 | |||||||
4 | 2 | True | 300 | 300 | 10 | 0 | 51.897339 | 19.268811 | 20436.912537 | 7.952839 | ||
10 | 1 | 47.530217 | 21.039248 | 20523.124695 | 8.060575 | |||||||
10 | 2 | 50.317358 | 19.873857 | 20642.505884 | 7.989317 | |||||||
10 | 3 | 49.739303 | 20.104825 | 20552.595377 | 8.039922 | |||||||
10 | 4 | 47.691540 | 20.968080 | 20634.422541 | 7.922381 | |||||||
10 | 5 | 50.226524 | 19.909799 | 20610.222816 | 8.024842 | |||||||
10 | 6 | 49.207839 | 20.321965 | 20518.425941 | 8.024156 | |||||||
10 | 7 | 48.164994 | 20.761967 | 20581.721306 | 7.939219 | |||||||
10 | 8 | 50.559520 | 19.778669 | 20608.603477 | 7.805288 | |||||||
10 | 9 | 49.909909 | 20.036101 | 20471.409798 | 8.016050 | |||||||
8 | 2 | True | 300 | 300 | 10 | 0 | 51.884579 | 19.273549 | 21162.240028 | 6.769925 | ||
10 | 1 | 52.411521 | 19.079775 | 21199.075937 | 7.179871 | |||||||
10 | 2 | 51.620535 | 19.372135 | 21240.265608 | 6.921858 | |||||||
10 | 3 | 51.347533 | 19.475132 | 21119.003057 | 6.866679 | |||||||
10 | 4 | 50.172901 | 19.931078 | 21245.890617 | 7.002726 | |||||||
10 | 5 | 53.531379 | 18.680632 | 21303.807735 | 6.739497 | |||||||
10 | 6 | 52.406200 | 19.081712 | 21211.510420 | 6.978109 | |||||||
10 | 7 | 50.439589 | 19.825697 | 21201.290131 | 6.951377 | |||||||
10 | 8 | 51.978053 | 19.238889 | 21105.926037 | 6.746009 | |||||||
10 | 9 | 51.141551 | 19.553572 | 21163.401842 | 6.907374 | |||||||
16 | 2 | True | 300 | 300 | 10 | 0 | 54.150795 | 18.466949 | 22976.331234 | 6.852485 | ||
10 | 1 | 54.501297 | 18.348187 | 23107.044697 | 6.870307 | |||||||
10 | 2 | 52.729979 | 18.964544 | 23003.034115 | 6.869771 | |||||||
10 | 3 | 51.683627 | 19.348487 | 23097.741604 | 6.533362 | |||||||
10 | 4 | 52.691641 | 18.978342 | 23121.733904 | 6.860301 | |||||||
10 | 5 | 52.760739 | 18.953487 | 23012.316942 | 6.557144 | |||||||
10 | 6 | 53.070833 | 18.842742 | 23209.119081 | 6.877601 | |||||||
10 | 7 | 52.512492 | 19.043088 | 23119.111538 | 6.905422 | |||||||
10 | 8 | 52.026126 | 19.221112 | 22915.400028 | 6.558336 | |||||||
10 | 9 | 51.058478 | 19.585386 | 22974.707842 | 6.754749 | |||||||
32 | 2 | True | 300 | 300 | 10 | 0 | 53.463848 | 18.704228 | 38056.073189 | 6.247517 | ||
10 | 1 | 55.518123 | 18.012136 | 38525.581360 | 6.233811 | |||||||
10 | 2 | 53.360695 | 18.740386 | 37970.025539 | 6.246682 | |||||||
10 | 3 | 53.299815 | 18.761791 | 39445.714474 | 6.284975 | |||||||
10 | 4 | 55.700301 | 17.953224 | 38235.680580 | 6.226789 | |||||||
10 | 5 | 56.074075 | 17.833553 | 38272.370815 | 6.632596 | |||||||
10 | 6 | 55.090850 | 18.151835 | 38257.955074 | 6.576888 | |||||||
10 | 7 | 53.035958 | 18.855132 | 38142.452240 | 6.234635 | |||||||
10 | 8 | 52.651272 | 18.992893 | 38927.487135 | 6.274536 | |||||||
10 | 9 | 54.079601 | 18.491261 | 38045.373678 | 6.560322 | |||||||
tensorrt-dynamic | 1 | 2 | True | 300 | 300 | 10 | 0 | 36.257188 | 27.580738 | 4492.929935 | 9.842515 | |
10 | 1 | 38.533234 | 25.951624 | 4472.224474 | 9.761214 | |||||||
10 | 2 | 35.761031 | 27.963400 | 4458.845854 | 9.777784 | |||||||
10 | 3 | 35.651299 | 28.049469 | 4430.665731 | 9.676337 | |||||||
10 | 4 | 37.579665 | 26.610136 | 4474.393845 | 9.764075 | |||||||
10 | 5 | 36.388357 | 27.481318 | 4479.102850 | 9.887338 | |||||||
10 | 6 | 36.222431 | 27.607203 | 4483.099461 | 9.891748 | |||||||
10 | 7 | 37.665721 | 26.549339 | 4507.941723 | 9.858489 | |||||||
10 | 8 | 36.447488 | 27.436733 | 4423.889160 | 9.681463 | |||||||
10 | 9 | 35.044818 | 28.534889 | 4492.774725 | 9.820461 | |||||||
2 | 2 | True | 300 | 300 | 10 | 0 | 43.085229 | 23.209810 | 4354.706287 | 8.053243 | ||
10 | 1 | 43.896201 | 22.781014 | 4459.623098 | 8.087158 | |||||||
10 | 2 | 46.957910 | 21.295667 | 4429.211617 | 8.065522 | |||||||
10 | 3 | 44.158935 | 22.645473 | 4382.166386 | 8.145511 | |||||||
10 | 4 | 45.924461 | 21.774888 | 4426.285744 | 8.045971 | |||||||
10 | 5 | 48.671370 | 20.545959 | 4482.997894 | 8.146882 | |||||||
10 | 6 | 43.603233 | 22.934079 | 4484.375715 | 8.114696 | |||||||
10 | 7 | 45.575895 | 21.941423 | 4462.842941 | 8.069873 | |||||||
10 | 8 | 47.062235 | 21.248460 | 4417.350054 | 8.044362 | |||||||
10 | 9 | 45.151506 | 22.147655 | 4489.324808 | 8.040249 | |||||||
4 | 2 | True | 300 | 300 | 10 | 0 | 50.611835 | 19.758224 | 4439.113617 | 7.771552 | ||
10 | 1 | 49.317193 | 20.276904 | 4527.236700 | 7.988602 | |||||||
10 | 2 | 49.987385 | 20.005047 | 4455.612898 | 7.809043 | |||||||
10 | 3 | 50.471302 | 19.813240 | 4472.424984 | 8.042753 | |||||||
10 | 4 | 52.434863 | 19.071281 | 4436.103582 | 7.985413 | |||||||
10 | 5 | 49.616329 | 20.154655 | 4438.630819 | 7.978261 | |||||||
10 | 6 | 49.702170 | 20.119846 | 4454.273701 | 7.984698 | |||||||
10 | 7 | 50.655845 | 19.741058 | 4485.294819 | 8.020997 | |||||||
10 | 8 | 49.991555 | 20.003378 | 4437.453270 | 7.853121 | |||||||
10 | 9 | 49.685684 | 20.126522 | 4419.140100 | 7.975161 | |||||||
8 | 2 | True | 300 | 300 | 10 | 0 | 51.926814 | 19.257873 | 4410.434723 | 6.691709 | ||
10 | 1 | 51.487227 | 19.422293 | 4386.659861 | 6.940439 | |||||||
10 | 2 | 53.588660 | 18.660665 | 4428.605318 | 6.895855 | |||||||
10 | 3 | 52.078895 | 19.201636 | 4450.277805 | 6.945342 | |||||||
10 | 4 | 55.108358 | 18.146068 | 4473.469496 | 6.976351 | |||||||
10 | 5 | 51.361366 | 19.469887 | 4481.755972 | 6.971747 | |||||||
10 | 6 | 52.652573 | 18.992424 | 4534.485817 | 6.936476 | |||||||
10 | 7 | 49.769403 | 20.092666 | 4488.675356 | 6.753743 | |||||||
10 | 8 | 51.072817 | 19.579887 | 4422.151327 | 6.929055 | |||||||
10 | 9 | 51.597595 | 19.380748 | 4452.725649 | 6.948888 | |||||||
16 | 2 | True | 300 | 300 | 10 | 0 | 55.482276 | 18.023774 | 4458.913326 | 7.088885 | ||
10 | 1 | 52.765676 | 18.951714 | 4457.708359 | 6.583475 | |||||||
10 | 2 | 52.935200 | 18.891022 | 4399.269819 | 6.477609 | |||||||
10 | 3 | 52.940294 | 18.889204 | 4466.050148 | 6.877258 | |||||||
10 | 4 | 52.952868 | 18.884718 | 4449.568748 | 6.659865 | |||||||
10 | 5 | 53.795974 | 18.588752 | 4397.683859 | 6.574184 | |||||||
10 | 6 | 54.138782 | 18.471047 | 4499.639511 | 6.823711 | |||||||
10 | 7 | 53.431773 | 18.715456 | 4428.323269 | 6.462626 | |||||||
10 | 8 | 53.892400 | 18.555492 | 4493.390560 | 6.541923 | |||||||
10 | 9 | 51.793480 | 19.307449 | 4420.616150 | 6.868303 | |||||||
32 | 2 | True | 300 | 300 | 10 | 0 | 53.517334 | 18.685535 | 4455.427647 | 6.305601 | ||
10 | 1 | 54.348094 | 18.399909 | 4469.662666 | 6.552197 | |||||||
10 | 2 | 54.623958 | 18.306985 | 4455.507517 | 6.439712 | |||||||
10 | 3 | 53.370943 | 18.736787 | 4434.459925 | 6.262217 | |||||||
10 | 4 | 54.644907 | 18.299967 | 4389.331341 | 6.248925 | |||||||
10 | 5 | 53.379540 | 18.733770 | 4404.261351 | 6.401818 | |||||||
10 | 6 | 55.426256 | 18.041991 | 4452.430964 | 6.259941 | |||||||
10 | 7 | 53.753897 | 18.603303 | 4411.975145 | 6.275486 | |||||||
10 | 8 | 53.469108 | 18.702388 | 4428.040504 | 6.598327 | |||||||
10 | 9 | 54.834806 | 18.236592 | 4407.277822 | 6.508533 | |||||||
yolo-v3 | cpu | 1 | 2 | True | 416 | 416 | 10 | 0 | 7.459803 | 134.051800 | 826.650381 | 12.364388 |
10 | 1 | 7.406113 | 135.023594 | 761.429787 | 11.766911 | |||||||
10 | 2 | 7.377169 | 135.553360 | 767.985821 | 11.433959 | |||||||
10 | 3 | 7.297196 | 137.038946 | 786.037683 | 12.368202 | |||||||
10 | 4 | 7.427570 | 134.633541 | 792.571783 | 12.083530 | |||||||
10 | 5 | 7.437487 | 134.454012 | 789.049864 | 11.571765 | |||||||
10 | 6 | 7.439809 | 134.412050 | 768.500090 | 11.892796 | |||||||
10 | 7 | 7.557768 | 132.314205 | 769.306660 | 11.978507 | |||||||
10 | 8 | 7.334212 | 136.347294 | 762.162685 | 11.768222 | |||||||
10 | 9 | 7.507874 | 133.193493 | 727.417946 | 11.743665 | |||||||
2 | 2 | True | 416 | 416 | 10 | 0 | 7.557522 | 132.318497 | 828.713655 | 10.014474 | ||
10 | 1 | 7.692893 | 129.990101 | 750.771284 | 10.156333 | |||||||
10 | 2 | 7.741839 | 129.168272 | 777.485132 | 10.104835 | |||||||
10 | 3 | 7.821765 | 127.848387 | 794.567108 | 10.232568 | |||||||
10 | 4 | 7.825603 | 127.785683 | 788.365364 | 10.231614 | |||||||
10 | 5 | 7.866818 | 127.116203 | 768.076181 | 10.247052 | |||||||
10 | 6 | 7.857776 | 127.262473 | 765.919685 | 10.197282 | |||||||
10 | 7 | 7.776648 | 128.590107 | 774.108171 | 10.263085 | |||||||
10 | 8 | 7.818790 | 127.897024 | 771.886349 | 9.763479 | |||||||
10 | 9 | 7.880068 | 126.902461 | 770.621300 | 10.260940 | |||||||
4 | 2 | True | 416 | 416 | 10 | 0 | 8.070625 | 123.906136 | 801.921129 | 9.931475 | ||
10 | 1 | 8.023575 | 124.632716 | 783.029556 | 9.824723 | |||||||
10 | 2 | 8.057489 | 124.108136 | 758.070469 | 9.692401 | |||||||
10 | 3 | 8.038337 | 124.403834 | 783.883572 | 9.921670 | |||||||
10 | 4 | 7.983725 | 125.254810 | 768.750191 | 9.572893 | |||||||
10 | 5 | 7.725530 | 129.440963 | 794.973135 | 10.110289 | |||||||
10 | 6 | 8.027645 | 124.569535 | 766.256332 | 9.763539 | |||||||
10 | 7 | 8.059495 | 124.077260 | 785.444498 | 9.889036 | |||||||
10 | 8 | 7.952784 | 125.742137 | 751.116037 | 9.540707 | |||||||
10 | 9 | 7.957868 | 125.661790 | 754.434824 | 9.631872 | |||||||
8 | 2 | True | 416 | 416 | 10 | 0 | 7.987237 | 125.199735 | 812.329292 | 8.724585 | ||
10 | 1 | 8.096920 | 123.503745 | 793.829918 | 8.596435 | |||||||
10 | 2 | 7.979053 | 125.328153 | 777.197599 | 8.909374 | |||||||
10 | 3 | 8.075955 | 123.824358 | 754.701853 | 8.658290 | |||||||
10 | 4 | 8.084819 | 123.688608 | 754.005432 | 8.825153 | |||||||
10 | 5 | 7.982700 | 125.270903 | 772.009850 | 8.698374 | |||||||
10 | 6 | 8.006997 | 124.890774 | 765.104055 | 8.629158 | |||||||
10 | 7 | 8.002761 | 124.956876 | 766.089916 | 8.645639 | |||||||
10 | 8 | 8.030900 | 124.519050 | 783.808708 | 8.621648 | |||||||
10 | 9 | 8.100998 | 123.441577 | 770.650148 | 8.544594 | |||||||
16 | 2 | True | 416 | 416 | 10 | 0 | 7.783413 | 128.478348 | 826.050043 | 8.524381 | ||
10 | 1 | 7.861007 | 127.210170 | 760.484934 | 8.538470 | |||||||
10 | 2 | 7.858170 | 127.256095 | 775.201321 | 8.575514 | |||||||
10 | 3 | 7.817914 | 127.911359 | 790.518761 | 8.449160 | |||||||
10 | 4 | 7.801944 | 128.173187 | 777.793169 | 8.474402 | |||||||
10 | 5 | 7.843042 | 127.501547 | 768.007994 | 8.512363 | |||||||
10 | 6 | 7.851994 | 127.356187 | 759.419203 | 8.807898 | |||||||
10 | 7 | 7.819607 | 127.883658 | 777.924061 | 8.742295 | |||||||
10 | 8 | 7.841469 | 127.527133 | 769.105196 | 8.449383 | |||||||
10 | 9 | 7.803614 | 128.145754 | 758.054733 | 8.371010 | |||||||
32 | 2 | True | 416 | 416 | 10 | 0 | 7.779773 | 128.538452 | 3009.296656 | 8.442033 | ||
10 | 1 | 7.789319 | 128.380932 | 754.206419 | 8.477602 | |||||||
10 | 2 | 7.796772 | 128.258213 | 794.567108 | 8.463278 | |||||||
10 | 3 | 7.788845 | 128.388740 | 754.859209 | 8.251451 | |||||||
10 | 4 | 7.737622 | 129.238665 | 774.708271 | 8.363865 | |||||||
10 | 5 | 7.766231 | 128.762580 | 778.465033 | 8.292355 | |||||||
10 | 6 | 7.751496 | 129.007362 | 795.592308 | 8.367561 | |||||||
10 | 7 | 7.779671 | 128.540143 | 757.143021 | 8.209728 | |||||||
10 | 8 | 7.780789 | 128.521666 | 770.535707 | 8.316364 | |||||||
10 | 9 | 7.778688 | 128.556386 | 769.662380 | 8.382883 | |||||||
cpu-prebuilt | 1 | 2 | True | 416 | 416 | 10 | 0 | 7.505080 | 133.243084 | 770.616055 | 11.433601 | |
10 | 1 | 7.578552 | 131.951332 | 776.219130 | 11.618733 | |||||||
10 | 2 | 7.637742 | 130.928755 | 741.240501 | 11.794209 | |||||||
10 | 3 | 7.466376 | 133.933783 | 742.387056 | 11.749029 | |||||||
10 | 4 | 7.641596 | 130.862713 | 765.636683 | 11.710882 | |||||||
10 | 5 | 7.463095 | 133.992672 | 742.483616 | 12.343168 | |||||||
10 | 6 | 7.476318 | 133.755684 | 744.406462 | 12.012601 | |||||||
10 | 7 | 7.632752 | 131.014347 | 746.438503 | 12.103677 | |||||||
10 | 8 | 7.545843 | 132.523298 | 746.113300 | 12.069225 | |||||||
10 | 9 | 7.554990 | 132.362843 | 759.110928 | 11.991858 | |||||||
2 | 2 | True | 416 | 416 | 10 | 0 | 7.788873 | 128.388286 | 780.621052 | 10.141850 | ||
10 | 1 | 7.864502 | 127.153635 | 745.664358 | 10.001600 | |||||||
10 | 2 | 7.868057 | 127.096176 | 758.759022 | 9.752929 | |||||||
10 | 3 | 7.704983 | 129.786134 | 742.192984 | 9.903431 | |||||||
10 | 4 | 7.846619 | 127.443433 | 745.921612 | 10.131240 | |||||||
10 | 5 | 7.761947 | 128.833652 | 774.803638 | 10.340035 | |||||||
10 | 6 | 7.772966 | 128.651023 | 727.174759 | 10.143161 | |||||||
10 | 7 | 7.880601 | 126.893878 | 763.806820 | 10.171413 | |||||||
10 | 8 | 7.838436 | 127.576470 | 743.127346 | 9.914815 | |||||||
10 | 9 | 7.817129 | 127.924204 | 741.799593 | 9.956062 | |||||||
4 | 2 | True | 416 | 416 | 10 | 0 | 8.047622 | 124.260306 | 733.114004 | 9.597838 | ||
10 | 1 | 8.085912 | 123.671889 | 787.828684 | 9.945691 | |||||||
10 | 2 | 7.898123 | 126.612365 | 729.163647 | 9.665459 | |||||||
10 | 3 | 7.930611 | 126.093686 | 758.428097 | 9.828657 | |||||||
10 | 4 | 8.129674 | 123.006165 | 744.267941 | 9.881586 | |||||||
10 | 5 | 8.020768 | 124.676347 | 742.209673 | 9.817600 | |||||||
10 | 6 | 8.054070 | 124.160826 | 763.856173 | 9.695083 | |||||||
10 | 7 | 8.112507 | 123.266459 | 758.080959 | 9.725362 | |||||||
10 | 8 | 7.953040 | 125.738084 | 740.075827 | 9.908676 | |||||||
10 | 9 | 8.010194 | 124.840915 | 740.096569 | 9.770602 | |||||||
8 | 2 | True | 416 | 416 | 10 | 0 | 8.000002 | 124.999970 | 735.028505 | 8.663520 | ||
10 | 1 | 7.942802 | 125.900149 | 743.657351 | 8.951396 | |||||||
10 | 2 | 7.997963 | 125.031829 | 728.087425 | 8.647516 | |||||||
10 | 3 | 7.973471 | 125.415891 | 748.322010 | 8.727342 | |||||||
10 | 4 | 8.024255 | 124.622166 | 747.579813 | 8.622497 | |||||||
10 | 5 | 7.932480 | 126.063973 | 729.033232 | 8.685499 | |||||||
10 | 6 | 7.984263 | 125.246376 | 743.060589 | 8.726448 | |||||||
10 | 7 | 7.970761 | 125.458539 | 755.054474 | 8.622214 | |||||||
10 | 8 | 8.084295 | 123.696625 | 742.125750 | 8.901402 | |||||||
10 | 9 | 7.907932 | 126.455307 | 748.281717 | 8.654654 | |||||||
16 | 2 | True | 416 | 416 | 10 | 0 | 7.754572 | 128.956184 | 749.789000 | 8.496441 | ||
10 | 1 | 7.800863 | 128.190950 | 735.840559 | 8.662008 | |||||||
10 | 2 | 7.751390 | 129.009128 | 730.700254 | 8.602113 | |||||||
10 | 3 | 7.757177 | 128.912881 | 747.271299 | 8.516140 | |||||||
10 | 4 | 7.817014 | 127.926081 | 762.900352 | 8.661099 | |||||||
10 | 5 | 7.802087 | 128.170833 | 768.960953 | 8.776374 | |||||||
10 | 6 | 7.761160 | 128.846720 | 777.239323 | 8.589797 | |||||||
10 | 7 | 7.745810 | 129.102051 | 761.098623 | 8.519493 | |||||||
10 | 8 | 7.774493 | 128.625751 | 746.984482 | 8.693248 | |||||||
10 | 9 | 7.731438 | 129.342049 | 750.234842 | 8.449718 | |||||||
32 | 2 | True | 416 | 416 | 10 | 0 | 7.699597 | 129.876934 | 804.311514 | 8.393414 | ||
10 | 1 | 7.700581 | 129.860327 | 746.842146 | 8.290410 | |||||||
10 | 2 | 7.709005 | 129.718430 | 755.871296 | 8.331478 | |||||||
10 | 3 | 7.710922 | 129.686184 | 743.375301 | 8.428369 | |||||||
10 | 4 | 7.711723 | 129.672714 | 741.960049 | 8.426096 | |||||||
10 | 5 | 7.717937 | 129.568309 | 733.941793 | 8.431178 | |||||||
10 | 6 | 7.732280 | 129.327968 | 742.064476 | 8.472528 | |||||||
10 | 7 | 7.689008 | 130.055785 | 749.837399 | 8.439362 | |||||||
10 | 8 | 7.694193 | 129.968144 | 746.048212 | 8.480441 | |||||||
10 | 9 | 7.715597 | 129.607596 | 764.533758 | 8.533400 | |||||||
cuda | 1 | 2 | True | 416 | 416 | 10 | 0 | 33.015097 | 30.289173 | 756.636620 | 11.920929 | |
10 | 1 | 32.440804 | 30.825377 | 720.205069 | 11.973023 | |||||||
10 | 2 | 32.638720 | 30.638456 | 710.690260 | 11.832714 | |||||||
10 | 3 | 32.494337 | 30.774593 | 736.654997 | 11.603832 | |||||||
10 | 4 | 32.126474 | 31.126976 | 747.756481 | 12.080669 | |||||||
10 | 5 | 32.239821 | 31.017542 | 743.244410 | 11.530995 | |||||||
10 | 6 | 32.753670 | 30.530930 | 735.150099 | 11.778235 | |||||||
10 | 7 | 32.872009 | 30.421019 | 731.841564 | 12.060523 | |||||||
10 | 8 | 32.599907 | 30.674934 | 733.180046 | 11.737704 | |||||||
10 | 9 | 32.617146 | 30.658722 | 734.117746 | 11.719584 | |||||||
2 | 2 | True | 416 | 416 | 10 | 0 | 41.050600 | 24.360180 | 767.584801 | 9.929657 | ||
10 | 1 | 41.081157 | 24.342060 | 731.180906 | 10.029256 | |||||||
10 | 2 | 41.724819 | 23.966551 | 738.259077 | 9.691656 | |||||||
10 | 3 | 41.070095 | 24.348617 | 715.700865 | 9.936154 | |||||||
10 | 4 | 41.777393 | 23.936391 | 733.265638 | 10.015130 | |||||||
10 | 5 | 41.593860 | 24.042010 | 736.417055 | 10.241807 | |||||||
10 | 6 | 41.215585 | 24.262667 | 728.220940 | 9.880304 | |||||||
10 | 7 | 41.324006 | 24.199009 | 733.928204 | 9.844542 | |||||||
10 | 8 | 41.747661 | 23.953438 | 716.781855 | 9.973347 | |||||||
10 | 9 | 41.212953 | 24.264216 | 719.955921 | 9.980798 | |||||||
4 | 2 | True | 416 | 416 | 10 | 0 | 48.843390 | 20.473599 | 775.704145 | 9.679258 | ||
10 | 1 | 48.176473 | 20.757020 | 735.307455 | 9.795904 | |||||||
10 | 2 | 48.078589 | 20.799279 | 728.606462 | 9.511650 | |||||||
10 | 3 | 47.934766 | 20.861685 | 737.453222 | 9.882748 | |||||||
10 | 4 | 48.733577 | 20.519733 | 725.023508 | 9.634823 | |||||||
10 | 5 | 48.025603 | 20.822227 | 735.261679 | 9.669513 | |||||||
10 | 6 | 48.073767 | 20.801365 | 738.612890 | 10.017842 | |||||||
10 | 7 | 47.925181 | 20.865858 | 746.457815 | 9.713411 | |||||||
10 | 8 | 47.957923 | 20.851612 | 730.696201 | 9.512872 | |||||||
10 | 9 | 48.148268 | 20.769179 | 733.915806 | 9.631932 | |||||||
8 | 2 | True | 416 | 416 | 10 | 0 | 49.872077 | 20.051301 | 778.191328 | 8.593932 | ||
10 | 1 | 50.699549 | 19.724041 | 731.018305 | 8.717254 | |||||||
10 | 2 | 45.246364 | 22.101223 | 731.523991 | 8.585066 | |||||||
10 | 3 | 49.813587 | 20.074844 | 738.673449 | 8.677602 | |||||||
10 | 4 | 50.128452 | 19.948751 | 735.694170 | 8.610740 | |||||||
10 | 5 | 50.059500 | 19.976228 | 723.472834 | 8.506611 | |||||||
10 | 6 | 45.941941 | 21.766603 | 732.049465 | 8.674756 | |||||||
10 | 7 | 49.874375 | 20.050377 | 742.737532 | 8.846745 | |||||||
10 | 8 | 45.806910 | 21.830767 | 741.208792 | 8.561283 | |||||||
10 | 9 | 45.206192 | 22.120863 | 727.003574 | 8.646011 | |||||||
16 | 2 | True | 416 | 416 | 10 | 0 | 57.646532 | 17.347097 | 776.599169 | 8.510336 | ||
10 | 1 | 57.404123 | 17.420352 | 738.630295 | 8.519799 | |||||||
10 | 2 | 57.397888 | 17.422244 | 734.946012 | 8.575954 | |||||||
10 | 3 | 57.219991 | 17.476410 | 760.316133 | 8.636869 | |||||||
10 | 4 | 57.370802 | 17.430469 | 745.356560 | 8.588895 | |||||||
10 | 5 | 57.377423 | 17.428458 | 733.257771 | 8.496560 | |||||||
10 | 6 | 58.166468 | 17.192036 | 731.886148 | 8.646935 | |||||||
10 | 7 | 57.602642 | 17.360315 | 731.846333 | 8.623302 | |||||||
10 | 8 | 57.351435 | 17.436355 | 742.234945 | 8.781746 | |||||||
10 | 9 | 57.514867 | 17.386809 | 735.044956 | 8.636773 | |||||||
32 | 2 | True | 416 | 416 | 10 | 0 | 59.267480 | 16.872659 | 766.610622 | 8.285634 | ||
10 | 1 | 59.953289 | 16.679652 | 734.985352 | 8.291133 | |||||||
10 | 2 | 52.717345 | 18.969089 | 737.916231 | 8.209787 | |||||||
10 | 3 | 52.571791 | 19.021608 | 756.889105 | 8.212481 | |||||||
10 | 4 | 52.565800 | 19.023776 | 738.118410 | 8.357562 | |||||||
10 | 5 | 59.229582 | 16.883455 | 740.912437 | 8.296773 | |||||||
10 | 6 | 52.939918 | 18.889338 | 719.966888 | 8.205108 | |||||||
10 | 7 | 59.452879 | 16.820043 | 738.403320 | 8.346349 | |||||||
10 | 8 | 52.687959 | 18.979669 | 743.752003 | 8.253429 | |||||||
10 | 9 | 52.519684 | 19.040480 | 732.797861 | 8.360378 | |||||||
tensorrt | 1 | 2 | True | 416 | 416 | 10 | 0 | 32.256185 | 31.001806 | 11862.448454 | 11.571169 | |
10 | 1 | 32.623996 | 30.652285 | 11716.783524 | 11.469364 | |||||||
10 | 2 | 32.519783 | 30.750513 | 11688.913107 | 11.564612 | |||||||
10 | 3 | 32.938353 | 30.359745 | 11777.283192 | 11.774659 | |||||||
10 | 4 | 32.098446 | 31.154156 | 11653.762102 | 11.580467 | |||||||
10 | 5 | 32.552593 | 30.719519 | 11586.960077 | 11.241317 | |||||||
10 | 6 | 32.957765 | 30.341864 | 11689.930916 | 11.301637 | |||||||
10 | 7 | 32.500883 | 30.768394 | 11901.330471 | 11.224627 | |||||||
10 | 8 | 32.231645 | 31.025410 | 11764.339685 | 11.325717 | |||||||
10 | 9 | 32.658034 | 30.620337 | 11768.515825 | 11.432052 | |||||||
2 | 2 | True | 416 | 416 | 10 | 0 | 41.332762 | 24.193883 | 11705.509424 | 9.914577 | ||
10 | 1 | 41.581695 | 24.049044 | 11819.612503 | 9.901166 | |||||||
10 | 2 | 40.985416 | 24.398923 | 11785.220623 | 9.689987 | |||||||
10 | 3 | 41.102091 | 24.329662 | 11800.042629 | 9.913146 | |||||||
10 | 4 | 40.803798 | 24.507523 | 11820.136547 | 9.708226 | |||||||
10 | 5 | 41.586849 | 24.046063 | 11747.811556 | 10.325491 | |||||||
10 | 6 | 41.356807 | 24.179816 | 11744.561195 | 9.793341 | |||||||
10 | 7 | 41.803208 | 23.921609 | 11721.886873 | 9.730399 | |||||||
10 | 8 | 41.358031 | 24.179101 | 11648.236513 | 9.858608 | |||||||
10 | 9 | 41.076732 | 24.344683 | 12031.765938 | 9.903312 | |||||||
4 | 2 | True | 416 | 416 | 10 | 0 | 48.808434 | 20.488262 | 11897.512436 | 9.983242 | ||
10 | 1 | 48.520195 | 20.609975 | 11693.880796 | 9.728044 | |||||||
10 | 2 | 47.965738 | 20.848215 | 11817.900896 | 9.706616 | |||||||
10 | 3 | 47.937642 | 20.860434 | 11917.607069 | 9.643972 | |||||||
10 | 4 | 48.326764 | 20.692468 | 11596.016884 | 9.389549 | |||||||
10 | 5 | 48.561625 | 20.592391 | 11940.795422 | 9.587616 | |||||||
10 | 6 | 48.615238 | 20.569682 | 11711.360693 | 9.485662 | |||||||
10 | 7 | 48.106437 | 20.787239 | 11645.892620 | 9.732932 | |||||||
10 | 8 | 48.652880 | 20.553768 | 11828.845024 | 9.661496 | |||||||
10 | 9 | 48.276980 | 20.713806 | 11688.106298 | 9.573609 | |||||||
8 | 2 | True | 416 | 416 | 10 | 0 | 50.509593 | 19.798219 | 11651.144028 | 8.472502 | ||
10 | 1 | 50.355265 | 19.858897 | 11687.902927 | 8.901447 | |||||||
10 | 2 | 50.044045 | 19.982398 | 11889.169455 | 8.548275 | |||||||
10 | 3 | 49.831045 | 20.067811 | 11802.555561 | 8.690566 | |||||||
10 | 4 | 49.940217 | 20.023942 | 11680.688381 | 8.634180 | |||||||
10 | 5 | 50.684692 | 19.729823 | 11726.379395 | 8.637890 | |||||||
10 | 6 | 50.666554 | 19.736886 | 11607.134819 | 8.601561 | |||||||
10 | 7 | 49.614715 | 20.155311 | 11641.483545 | 8.741736 | |||||||
10 | 8 | 45.288991 | 22.080421 | 11725.649595 | 8.792400 | |||||||
10 | 9 | 49.951368 | 20.019472 | 11664.314985 | 8.556172 | |||||||
16 | 2 | True | 416 | 416 | 10 | 0 | 57.895791 | 17.272413 | 11757.075310 | 8.454420 | ||
10 | 1 | 57.394599 | 17.423242 | 11903.642178 | 8.384913 | |||||||
10 | 2 | 57.901486 | 17.270714 | 11781.234503 | 8.474089 | |||||||
10 | 3 | 57.257827 | 17.464861 | 11862.584114 | 8.416958 | |||||||
10 | 4 | 57.900886 | 17.270893 | 11722.855806 | 8.738019 | |||||||
10 | 5 | 57.874970 | 17.278627 | 11779.921055 | 8.446746 | |||||||
10 | 6 | 58.184522 | 17.186701 | 11815.725088 | 8.558780 | |||||||
10 | 7 | 57.248497 | 17.467707 | 11799.353600 | 8.438826 | |||||||
10 | 8 | 57.323218 | 17.444938 | 11851.527452 | 8.447371 | |||||||
10 | 9 | 58.060687 | 17.223358 | 11700.683117 | 8.359380 | |||||||
32 | 2 | True | 416 | 416 | 10 | 0 | 59.918013 | 16.689472 | 11949.890852 | 8.227546 | ||
10 | 1 | 52.954268 | 18.884219 | 11936.690807 | 8.245900 | |||||||
10 | 2 | 59.252540 | 16.876914 | 11856.063366 | 8.250069 | |||||||
10 | 3 | 59.453221 | 16.819946 | 11819.866657 | 8.245450 | |||||||
10 | 4 | 52.823782 | 18.930867 | 11652.352810 | 8.260824 | |||||||
10 | 5 | 59.937814 | 16.683958 | 11699.779034 | 8.226626 | |||||||
10 | 6 | 59.195336 | 16.893223 | 11725.577354 | 8.300830 | |||||||
10 | 7 | 59.434976 | 16.825110 | 11632.177114 | 8.197069 | |||||||
10 | 8 | 53.711670 | 18.617928 | 11683.812618 | 8.247960 | |||||||
10 | 9 | 59.461808 | 16.817518 | 11692.517519 | 8.225493 | |||||||
tensorrt-dynamic | 1 | 2 | True | 416 | 416 | 10 | 0 | 33.722234 | 29.654026 | 10214.663744 | 11.405230 | |
10 | 1 | 33.344760 | 29.989719 | 10163.130760 | 11.441231 | |||||||
10 | 2 | 32.207885 | 31.048298 | 10030.030966 | 11.518478 | |||||||
10 | 3 | 33.368635 | 29.968262 | 9938.854694 | 11.760235 | |||||||
10 | 4 | 32.228426 | 31.028509 | 9924.241066 | 11.911869 | |||||||
10 | 5 | 33.119637 | 30.193567 | 10087.437153 | 11.619210 | |||||||
10 | 6 | 32.753670 | 30.530930 | 9938.045979 | 11.651874 | |||||||
10 | 7 | 34.520452 | 28.968334 | 10115.472555 | 11.228919 | |||||||
10 | 8 | 32.833924 | 30.456305 | 9982.085705 | 11.464119 | |||||||
10 | 9 | 31.725999 | 31.519890 | 10169.567823 | 11.517763 | |||||||
2 | 2 | True | 416 | 416 | 10 | 0 | 36.674076 | 27.267218 | 10154.089928 | 9.788334 | ||
10 | 1 | 34.905992 | 28.648376 | 10108.564377 | 9.919822 | |||||||
10 | 2 | 38.682671 | 25.851369 | 10135.166883 | 9.725690 | |||||||
10 | 3 | 37.770189 | 26.475906 | 10128.602505 | 9.730458 | |||||||
10 | 4 | 38.220550 | 26.163936 | 10192.887545 | 9.962976 | |||||||
10 | 5 | 35.161893 | 28.439879 | 10098.555088 | 9.943366 | |||||||
10 | 6 | 34.940304 | 28.620243 | 10168.661118 | 9.785891 | |||||||
10 | 7 | 38.465914 | 25.997043 | 10097.043514 | 9.609044 | |||||||
10 | 8 | 38.029604 | 26.295304 | 9929.991961 | 10.007560 | |||||||
10 | 9 | 38.326197 | 26.091814 | 10142.686605 | 9.811342 | |||||||
4 | 2 | True | 416 | 416 | 10 | 0 | 40.641496 | 24.605393 | 11178.858280 | 9.646863 | ||
10 | 1 | 40.764834 | 24.530947 | 11536.217451 | 9.618133 | |||||||
10 | 2 | 40.525459 | 24.675846 | 10812.536478 | 9.865493 | |||||||
10 | 3 | 40.309304 | 24.808168 | 10403.804064 | 9.634823 | |||||||
10 | 4 | 36.667102 | 27.272403 | 11289.476871 | 9.460688 | |||||||
10 | 5 | 40.309110 | 24.808288 | 10769.871712 | 9.692043 | |||||||
10 | 6 | 40.637657 | 24.607718 | 10642.199755 | 9.489983 | |||||||
10 | 7 | 40.178886 | 24.888694 | 10468.506336 | 9.643734 | |||||||
10 | 8 | 39.946703 | 25.033355 | 10529.506445 | 9.732276 | |||||||
10 | 9 | 40.112889 | 24.929643 | 10472.413301 | 9.521335 | |||||||
8 | 2 | True | 416 | 416 | 10 | 0 | 41.125919 | 24.315566 | 10136.513948 | 8.508503 | ||
10 | 1 | 40.832945 | 24.490029 | 10148.459196 | 8.661255 | |||||||
10 | 2 | 40.678350 | 24.583101 | 10214.094400 | 8.521974 | |||||||
10 | 3 | 40.708652 | 24.564803 | 10059.355497 | 8.677438 | |||||||
10 | 4 | 37.725898 | 26.506990 | 10028.834343 | 8.544073 | |||||||
10 | 5 | 40.822265 | 24.496436 | 9911.667585 | 8.550242 | |||||||
10 | 6 | 40.799978 | 24.509817 | 10052.909613 | 8.539915 | |||||||
10 | 7 | 40.863677 | 24.471611 | 10235.522270 | 8.539960 | |||||||
10 | 8 | 40.510879 | 24.684727 | 10168.982029 | 8.608490 | |||||||
10 | 9 | 40.664990 | 24.591178 | 10139.875412 | 8.745968 | |||||||
16 | 2 | True | 416 | 416 | 10 | 0 | 38.212976 | 26.169121 | 10636.604786 | 8.877695 | ||
10 | 1 | 38.328517 | 26.090235 | 10321.853638 | 8.753181 | |||||||
10 | 2 | 41.660788 | 24.003386 | 10284.081936 | 8.482546 | |||||||
10 | 3 | 41.403296 | 24.152666 | 10617.761612 | 8.488871 | |||||||
10 | 4 | 41.592596 | 24.042740 | 10567.626476 | 8.564413 | |||||||
10 | 5 | 41.526041 | 24.081275 | 10933.218002 | 8.424073 | |||||||
10 | 6 | 40.946929 | 24.421856 | 10555.508852 | 8.465439 | |||||||
10 | 7 | 41.796725 | 23.925319 | 10436.465979 | 8.487754 | |||||||
10 | 8 | 41.767356 | 23.942143 | 10323.004246 | 8.584604 | |||||||
10 | 9 | 42.019910 | 23.798242 | 10236.896515 | 8.871555 | |||||||
32 | 2 | True | 416 | 416 | 10 | 0 | 42.181365 | 23.707151 | 10011.900425 | 8.353427 | ||
10 | 1 | 42.641372 | 23.451403 | 10015.968561 | 8.194283 | |||||||
10 | 2 | 42.212262 | 23.689799 | 10113.837481 | 8.239280 | |||||||
10 | 3 | 38.904930 | 25.703683 | 10202.510595 | 8.308575 | |||||||
10 | 4 | 38.740709 | 25.812641 | 10094.983816 | 8.282896 | |||||||
10 | 5 | 42.082953 | 23.762591 | 10029.658556 | 8.198120 | |||||||
10 | 6 | 42.069419 | 23.770235 | 10193.944931 | 8.187093 | |||||||
10 | 7 | 42.496558 | 23.531318 | 10064.801931 | 8.159630 | |||||||
10 | 8 | 38.847153 | 25.741912 | 10182.497501 | 8.184604 | |||||||
10 | 9 | 42.213536 | 23.689084 | 10184.962988 | 8.262347 |
def plot_accuracy(df, groupby_level='batch_enabled',
accuracy_metric=['mAP','mAP_large','mAP_medium','mAP_small'],
save_fig=False, save_fig_name='accuracy.resizing.', resize_type=['internal','external'],
title='', figsize=[default_figwidth, 8], rot=90, colormap=cm.autumn):
# Bars.
df_bar = pd.DataFrame(
data=df[accuracy_metric].values, columns=accuracy_metric,
index=pd.MultiIndex.from_tuples(
tuples=[ (m,be,nr) for (m,b,bs,bc,be,ih,iw,nr) in df.index.values ],
names=[ 'model','batch_enabled','num_reps' ]
)
)
# Plot.
mean = df_bar.groupby(level=df_bar.index.names[:-1]).mean()
std = pd.Series()
axes = mean \
.groupby(level=groupby_level) \
.plot(yerr=std, kind='bar', grid=True, rot=rot,
figsize=figsize, width=default_barwidth, fontsize=default_fontsize, colormap=colormap)
xlabel = 'Model'
xtics = df_bar.index.get_level_values('model').drop_duplicates()
ylabel = 'mAP %'
for count, ax in enumerate(axes):
# Title.
ax.set_title('Accuracy with %s resizing' % resize_type[count])
# X label.
ax.set_xlabel(xlabel)
# X ticks.
ax.set_xticklabels(xtics)
# Y axis.
ax.set_ylabel(ylabel)
if save_fig:
save_fig_path = os.path.join(save_fig_dir, '%s.%s' % (save_fig_name+resize_type[count], save_fig_ext))
ax.figure.savefig(save_fig_path, dpi=default_figdpi, bbox_inches='tight')
plot_accuracy(dfs, save_fig=True)
There are two types of resizing: fixed and keep_aspect_ratio.
The first one takes as input the image and returns an image of fixed dimensions, changing from network to network. Using this layer are the following networks:
- 'ssd_mobilenet_v1_fpn_coco', 640*640
- 'faster_rcnn_nas_lowproposals_coco', 1200*1200
- 'faster_rcnn_nas', 1200*1200
- 'ssd_inception_v2_coco', 300*300
- 'ssd_mobilenet_v1_coco', 300*300
- 'ssd_mobilenet_v1_quantized_coco', 300*300
- 'ssd_resnet_50_fpn_coco', 640*640
- 'ssdlite_mobilenet_v2_coco', 300*300
- 'yolo v3', 416*416
The second one behaviour is actually not completely clear, and have a minimum and maximum dimension of the output images. network using this layer are:
- 'faster_rcnn_inception_resnet_v2_atrous_lowproposals_coco', min: 600 max: 1024
- 'faster_rcnn_inception_resnet_v2_atrous_coco', min: 600 max: 1024
- 'faster_rcnn_resnet101_lowproposal_coco', min: 600 max: 1024
- 'faster_rcnn_resnet50_lowproposals_coco', min: 600 max: 1024
From the analysis on the performance-accuracy benchmarks, it seems that the models using fixed resizing performs better than the one with the keep aspect ratio.
YOLO-v3 is actually in the middle ground: its preprocessing is doing a fixed resize to 416 * 416, however the resize is done keeping the aspect ratio and padding, outside the graph. The graph doesn't perform any resizing, but takes 416 * 416 images as input.
def plot_accuracy_compare_resizing(df_raw, resize_type=['internal','external'],
unstack_level='batch_enabled', groupby_level='batch_size',
accuracy_metric=['mAP','mAP_large','mAP_medium','mAP_small'],
save_fig=False, save_fig_name='accuracy.resizing.internal_vs_external',
title='', figsize=[default_figwidth, 8], rot=90):
# Bars.
df_bar = pd.DataFrame(
data=df_raw[accuracy_metric].values, columns=accuracy_metric,
index=pd.MultiIndex.from_tuples(
tuples=[ (m,be,bs,nr) for (m,b,bs,bc,be,ih,iw,nr) in df_raw.index.values ],
names=[ 'model','batch_enabled','batch_size','num_reps' ]
)
)
for index, row in df_bar.iterrows():
(model, batch_enabled, batch_size, num_reps) = index
if model == 'yolo-v3':
# batch_size and num_reps are both 1 for accuracy experiments.
df_bar.loc[(model, True, 1, 1)] = df_bar.loc[(model, False, 1, 1)][accuracy_metric]
# Colormap.
colornames = [ 'lightcoral','cyan','indianred','darkturquoise','brown','cadetblue','darkred','steelblue' ]
colormap = mp.colors.ListedColormap(colornames, name='from_list', N=len(colornames))
# Plot.
mean = df_bar.groupby(level=df_bar.index.names[:-1]).mean().unstack(unstack_level)
std = df_bar.groupby(level=df_bar.index.names[:-1]).std().unstack(unstack_level)
axes = mean \
.groupby(level=groupby_level) \
.plot(yerr=std, kind='bar', grid=True, rot=rot,
figsize=figsize, width=default_barwidth, fontsize=default_fontsize, colormap=colormap)
xlabel = 'Model'
ylabel = 'mAP %'
xtics = df_bar.index.get_level_values('model').drop_duplicates()
for count, ax in enumerate(axes):
# Title.
ax.set_title('Compare resizing: %s vs %s' % (resize_type[0], resize_type[1]))
# X label.
ax.set_xlabel(xlabel)
# X ticks.
ax.set_xticklabels(xtics)
# Y axis.
ax.set_ylabel(ylabel)
patches, labels = ax.get_legend_handles_labels()
# Legend.
labels = [x.strip('(') for x in labels]
labels = [x.strip(')') for x in labels]
ax.legend(patches, labels, loc='best', title='Metric, External resizing?')
if save_fig:
save_fig_path = os.path.join(save_fig_dir, '%s.%s' % (save_fig_name, save_fig_ext))
ax.figure.savefig(save_fig_path, dpi=default_figdpi, bbox_inches='tight')
plot_accuracy_compare_resizing(dfs, save_fig=True)
def plot_performance_per_backend(df_raw, groupby_level='backend', unstack_level=['batch_size'],
performance_metric=['avg_fps','avg_time_ms','graph_load_time_ms','images_load_time_avg_ms'],
save_fig=False, save_fig_name='performance.backend.',
title=None, figsize=[default_figwidth, 8], rot=90, colormap=cm.autumn):
# Bars.
df_bar = pd.DataFrame(
data=df_raw[performance_metric].values, columns=performance_metric,
index=pd.MultiIndex.from_tuples(
tuples=[ (m,b,bs,be,nr) for (m,b,bs,bc,be,ih,iw,nr) in df_raw.index.values ],
names=[ 'model','backend','batch_size','batch_enabled','num_reps' ]
)
)
# Plot.
mean = df_bar.groupby(level=df_bar.index.names[:-1]).mean().unstack(unstack_level)
std = df_bar.groupby(level=df_bar.index.names[:-1]).std().unstack(unstack_level)
axes = mean \
.groupby(level=groupby_level) \
.plot(yerr=std, kind='bar', grid=True, rot=rot, legend=False,
figsize=figsize, width=default_barwidth, fontsize=default_fontsize, colormap=colormap)
xlabel = 'Model'
xtics = df_bar.index.get_level_values('model').drop_duplicates()
ylabel = 'Images Per Second'
for num, ax in enumerate(axes):
# Title.
ax.set_title('TensorFlow with the \'{}\' Backend'.format(axes.keys().to_numpy().item(num)))
# X label.
ax.set_xlabel(xlabel)
# X ticks.
ax.set_xticklabels(xtics)
# Y axis.
ax.set_ylabel(ylabel)
# Legend.
patches, labels = ax.get_legend_handles_labels()
labels = [label[1] for label in [x.split(',') for x in labels]]
labels = [x.strip(')') for x in labels]
ax.legend(patches, labels, loc='best', title='Batch Size')
# Save figure.
if save_fig:
save_fig_path = os.path.join(save_fig_dir, '%s.%s' % (save_fig_name+axes.keys().to_numpy().item(num), save_fig_ext))
ax.figure.savefig(save_fig_path, dpi=default_figdpi, bbox_inches='tight')
plot_performance_per_backend(dfs_perf, performance_metric=['avg_fps'], save_fig=True)
def plot_performance_per_model(df_raw, groupby_level='model', unstack_level=['batch_size'],
performance_metric=['avg_fps','avg_time_ms','graph_load_time_ms','images_load_time_avg_ms'],
save_fig=False, save_fig_name='performance.model.',
title=None, figsize=[default_figwidth, 8], rot=0, colormap=cm.autumn):
# Bars.
df_bar = pd.DataFrame(
data=df_raw[performance_metric].values, columns=performance_metric,
index=pd.MultiIndex.from_tuples(
tuples=[ (m,b,bs,be,nr) for (m,b,bs,bc,be,ih,iw,nr) in df_raw.index.values ],
names=[ 'model','backend','batch_size','batch_enabled','num_reps' ]
)
)
# Plot.
mean = df_bar.groupby(level=df_bar.index.names[:-1]).mean().unstack(unstack_level)
std = df_bar.groupby(level=df_bar.index.names[:-1]).std().unstack(unstack_level)
axes = mean \
.groupby(level=groupby_level) \
.plot(yerr=std, kind='bar', grid=True, rot=rot,
figsize=figsize, width=default_barwidth, fontsize=default_fontsize, legend=False, colormap=colormap)
xlabel = 'Backend'
xtics = df_bar.index.get_level_values('backend').drop_duplicates()
ylabel = 'Images Per Second'
for num, ax in enumerate(axes):
# Title.
ax.set_title(axes.keys().to_numpy().item(num))
# X label.
ax.set_xlabel(xlabel)
# X ticks.
ax.set_xticklabels(xtics)
# Y axis.
ax.set_ylabel(ylabel)
# Legend.
patches, labels = ax.get_legend_handles_labels()
labels = [label[1] for label in [x.split(',') for x in labels]]
labels = [x.strip(')') for x in labels]
ax.legend(patches, labels, loc='best', title='Batch Size')
# Save figure.
if save_fig:
save_fig_path = os.path.join(save_fig_dir, '%s.%s' % (save_fig_name+axes.keys().to_numpy().item(num), save_fig_ext))
ax.figure.savefig(save_fig_path, dpi=default_figdpi, bbox_inches='tight')
plot_performance_per_model(dfs_perf, performance_metric=['avg_fps'], save_fig=True)
def plot_performance_compare_backends(df_raw, backends=['cuda','tensorrt-dynamic'],
groupby_level='batch_enabled', unstack_level = ['backend','batch_size'],
performance_metric=['avg_fps','avg_time_ms','graph_load_time_ms','images_load_time_avg_ms'],
save_fig=False, save_fig_name='performance.backend.cuda_vs_tensorrt-dynamic',
title='', figsize=[default_figwidth, 8], rot=90):
# Bars.
df_bar = pd.DataFrame(
data=df_raw[performance_metric].values, columns=performance_metric,
index=pd.MultiIndex.from_tuples(
tuples=[ (m,b,bs,be,nr) for (m,b,bs,bc,be,ih,iw,nr) in df_raw.index.values ],
names=[ 'model','backend','batch_size','batch_enabled','num_reps' ]
)
)
df_bar = df_bar.query('backend in @backends')
# Colormap.
colormap = mp.colors.ListedColormap(['darkred','steelblue'], name='from_list', N=12)
# Plot.
mean = df_bar.groupby(level=df_bar.index.names[:-1]).mean().unstack(unstack_level[1]).unstack(unstack_level[0])
std = df_bar.groupby(level=df_bar.index.names[:-1]).std().unstack(unstack_level[1]).unstack(unstack_level[0])
axes = mean \
.groupby(level=groupby_level) \
.plot(yerr=std, kind='bar', grid=True, rot=rot, legend=False,
figsize=figsize, width=default_barwidth, fontsize=default_fontsize, colormap=colormap)
xlabel = 'Model'
xtics = df_bar.index.get_level_values('model').drop_duplicates()
ylabel = 'Images Per Second'
for num, ax in enumerate(axes):
# Title.
ax.set_title('Compare Backends: \'%s\' vs \'%s\'' % (backends[0], backends[1]))
# X label.
ax.set_xlabel(xlabel)
# X ticks.
ax.set_xticklabels(xtics)
# Y axis.
ax.set_ylabel(ylabel)
# Legend.
patches, labels = ax.get_legend_handles_labels()
labels = [label[2] for label in [x.split(',') for x in labels]]
labels = [x.strip(')') for x in labels]
ax.legend(patches[:2], labels[:2], loc='left', title='Backend')
# Save figure.
if save_fig:
save_fig_path = os.path.join(save_fig_dir, '%s.%s' % (save_fig_name+str(num), save_fig_ext))
ax.figure.savefig(save_fig_path, dpi=default_figdpi, bbox_inches='tight')
plot_performance_compare_backends(dfs_perf, performance_metric=['avg_fps'], save_fig=True)
plot_performance_compare_backends(dfs_perf, performance_metric=['avg_fps'], save_fig=True,
backends=['cpu-prebuilt','cpu'], save_fig_name='performance.backend.cpu-prebuilt_vs_cpu')
/usr/local/lib/python3.6/dist-packages/ipykernel_launcher.py:43: MatplotlibDeprecationWarning: Unrecognized location 'left'. Falling back on 'best'; valid locations are best upper right upper left lower left lower right right center left center right lower center upper center center This will raise an exception in 3.3.
def plot_performance_compare_docker_vs_native(df_docker, df_native,
groupby_level='batch_enabled', unstack_level=['batch_size','backend'],
save_fig=False, save_fig_name='performance.docker_vs_native',
title='', figsize=[default_figwidth, 8], rot=90):
# Bars.
df_docker = df_docker[df_docker.index.get_level_values('batch_enabled').isin([True])]
df_bar = pd.merge(
df_docker, df_native,
how='inner', suffixes=('_docker', '_native'),
on=[ 'model', 'backend', 'batch_size', 'batch_enabled', 'num_reps' ])
df_bar = df_bar[['avg_fps_docker', 'avg_fps_native']]
df_bar['avg_fps_norm'] = df_bar['avg_fps_docker'] / df_bar['avg_fps_native']
df_bar = df_bar[['avg_fps_norm']]
# Colormap.
reds = ['red', 'indianred', 'brown', 'firebrick', 'maroon', 'darkred']
yellows = ['cornsilk', 'lemonchiffon', 'palegoldenrod', 'khaki', 'yellow', 'gold']
greens = ['palegreen', 'lightgreen', 'limegreen', 'green', 'forestgreen', 'darkgreen']
blues = ['cornflowerblue', 'royalblue', 'mediumblue', 'blue', 'navy', 'midnightblue']
purples = ['orchid', 'fuchsia', 'mediumorchid', 'darkviolet', 'purple', 'indigo']
colornames = reds + yellows + greens + blues + purples
colormap = mp.colors.ListedColormap(colornames, name='from_list', N=len(colornames))
# Plot.
mean = df_bar.groupby(level=df_bar.index.names[:-1]).mean().unstack(unstack_level[1]).unstack(unstack_level[0])
std = df_bar.groupby(level=df_bar.index.names[:-1]).std().unstack(unstack_level[1]).unstack(unstack_level[0])
axes = mean \
.groupby(level=groupby_level) \
.plot(yerr=std, kind='bar', grid=True, rot=rot, ylim=[0.0,1.201],
figsize=figsize, width=default_barwidth, fontsize=default_fontsize, colormap=colormap)
title = 'Compare Docker vs Native Performance (Normalized to Native) on 5 Models from the Pareto Frontier'
xtics = df_bar.groupby(level=df_bar.index.names[:-1]).median().index.get_level_values('model').drop_duplicates()
xlabel = 'Model'
ylabel = ''
for num, ax in enumerate(axes):
# Title.
ax.set_title(title)
# X label.
ax.set_xlabel(xlabel)
# X ticks.
ax.set_xticklabels(xtics)
# Y axis.
ax.set_ylabel(ylabel)
# Shrink current axis by 20%
box = ax.get_position()
ax.set_position([box.x0, box.y0, box.width * 0.8, box.height])
patches, labels = ax.get_legend_handles_labels()
# Legend.
labels = [x.strip('(avg_fps_norm,') for x in labels]
labels = [x.strip(')') for x in labels]
ax.legend(patches, labels, title='Backend, Batch Size', loc='center left', bbox_to_anchor=(1, 0.5),fontsize=default_fontsize)
# Put a legend to the right of the current axis.
if save_fig:
save_fig_path = os.path.join(save_fig_dir, '%s.%s' % (save_fig_name, save_fig_ext))
ax.figure.savefig(save_fig_path, dpi=default_figdpi, bbox_inches='tight')
plot_performance_compare_docker_vs_native(dfs_perf, dfs_perf_native, rot=45, save_fig=True)
# Plotting settings.
model_to_color = {
'rcnn-inception-resnet-v2-lowproposals' : 'gold',
'rcnn-inception-v2' : 'goldenrod',
'rcnn-nas-lowproposals' : 'red',
'rcnn-resnet101-lowproposals' : 'brown',
'rcnn-resnet50-lowproposals' : 'orangered',
'ssd-mobilenet-v1-fpn' : 'cyan',
'ssd-inception-v2' : 'cadetblue',
'ssd-mobilenet-v1-non-quantized-mlperf' : 'deepskyblue',
'ssd-mobilenet-v1-quantized-mlperf' : 'royalblue',
'ssd-resnet50-fpn' : 'navy',
'ssdlite-mobilenet-v2' : 'violet',
'yolo-v3' : 'gray'
}
backend_to_marker = {
'tensorrt' : '1',
'tensorrt-dynamic' : '2',
'cuda' : '3',
'cpu' : '4',
'cpu-prebuilt' : '+'
}
resize_to_marker = {
'no-resize' : 'x',
'model-resize' : '*'
}
bs_to_size = {
1 : 1.0,
2 : 1.5,
4 : 2.0,
8 : 2.5,
16 : 3.0,
32 : 3.5
}
### not used anymore, left in case should change the policy
# model_to_real_name = {
# 'ssd-mobilenet-v1-fpn' : 'ssd_mobilenet_v1_fpn_coco',
# 'rcnn-inception-resnet-v2-lowproposals' : 'faster_rcnn_inception_resnet_v2_atrous_lowproposals_coco',
# 'rcnn-nas-lowproposals' : 'faster_rcnn_nas_lowproposals_coco',
# 'rcnn-resnet101-lowproposals' : 'faster_rcnn_resnet101_lowproposals_coco',
# 'rcnn-inception-v2' : 'faster_rcnn_inception_resnet_v2_atrous_coco',
# 'rcnn-nas-non-lowproposal' : 'faster_rcnn_nas',
# 'ssd-inception-v2' : 'ssd_inception_v2_coco',
# 'ssd-mobilenet-v1-non-quantized-mlperf' : 'ssd_mobilenet_v1_coco',
# 'ssd-mobilenet-v1-quantized-mlperf' : 'ssd_mobilenet_v1_quantized_coco',
# 'ssd-resnet50-fpn' : 'ssd_resnet_50_fpn_coco',
# 'ssdlite-mobilenet-v2' : 'ssdlite_mobilenet_v2_coco',
# 'rcnn-resnet50-lowproposals' : 'faster_rcnn_resnet50_lowproposals_coco',
# 'yolo-v3' : 'yolo v3'
# }
import matplotlib.lines as mlines
mark1 = mlines.Line2D([], [], color='black', marker='1', linestyle='None',
markersize=5, label='tensorrt')
mark2 = mlines.Line2D([], [], color='black', marker='2', linestyle='None',
markersize=5, label='tensorrt-dynamic')
mark3 = mlines.Line2D([], [], color='black', marker='3', linestyle='None',
markersize=5, label='cuda')
mark4 = mlines.Line2D([], [], color='black', marker='4', linestyle='None',
markersize=5, label=' cpu')
mark5 = mlines.Line2D([], [], color='black', marker='+', linestyle='None',
markersize=5, label=' cpu-prebuilt')
handles2 = [ mark1, mark2, mark3, mark4, mark5 ]
#mark1 = mlines.Line2D([], [], color='black', marker='x', linestyle='None',
# markersize=5, label='no resize')
#mark2 = mlines.Line2D([], [], color='black', marker='*', linestyle='None',
# markersize=5, label='model resize')
#handles2 = [ mark1,mark2 ]
def merge_performance_accuracy(df_performance, df_accuracy,
performance_metric='avg_fps', accuracy_metric='mAP', ideal=False):
df = df_performance[[performance_metric]]
for metric in accuracy_metric:
accuracy_list = []
for index, row in df.iterrows():
(model, backend, batch_size, batch_count, batch_enabled, image_height, image_width, num_reps) = index
if ideal:
accuracy = df_accuracy.loc[(model, 'cuda', 1, 5000, False, image_height, image_width, 1)][metric]
else:
resize = 'no-resize' if batch_size == 1 else 'model-resize'
if resize == 'no-resize' or model == 'yolo-v3':
accuracy = df_accuracy.loc[(model, 'cuda', 1, 5000, False, image_height, image_width, 1)][metric]
else:
accuracy = df_accuracy.loc[(model, 'cuda', 1, 5000, True, image_height, image_width, 1)][metric]
accuracy_list.append(accuracy)
# Assign to the value of accuracy_metric.
kwargs = { metric : accuracy_list }
df = df.assign(**kwargs)
return df
def finalize_plot(ax, xmin, xmax, xstep, ymin, ymax, ystep, save_fig, save_fig_name, accuracy_metric):
# X axis.
xlabel = 'Images Per Second'
ax.set_xlabel(xlabel)
ax.set_xlim(xmin, xmax)
ax.set_xticks(np.arange(xmin, xmax, xstep))
for xtick in ax.xaxis.get_major_ticks(): xtick.label.set_fontsize(5)
# Y axis.
ylabel = accuracy_metric + ' %'
ax.set_ylabel(ylabel)
ax.set_ylim(ymin, ymax)
ax.set_yticks(np.arange(ymin, ymax, ystep))
for ytick in ax.yaxis.get_major_ticks(): ytick.label.set_fontsize(5)
# Legend.
handles = [
mp.patches.Patch(color=color, label=model)
for (model, color) in sorted(model_to_color.items())
]
handles += handles2
plt.legend(title='', handles=handles[::-1], loc='best', prop={'size': 5})
# Show with grid on.
plt.grid(True)
fig1 = plt.gcf()
plt.show()
plt.draw()
# Save figure.
if save_fig:
save_fig_path = os.path.join(save_fig_dir, '%s.%s' % (save_fig_name, save_fig_ext))
fig1.savefig(save_fig_path, dpi=default_figdpi, bbox_inches='tight')
def plot_dse(ideal=False,
performance_metric='avg_fps', accuracy_metric=['mAP'],
xmin=0.00, xmax=85.01, xstep=5,
ymin=18.00, ymax=46.01, ystep=4,
save_fig=False, save_fig_name='dse.full'):
fig = plt.figure(figsize=(8,4), dpi=default_figdpi)
ax = fig.gca()
if ideal:
save_fig_name += '.ideal'
ax.set_title('Full Space Exploration with Ideal Accuracy')
else:
ax.set_title('Full Space Exploration with Measured Accuracy')
df_performance_accuracy = merge_performance_accuracy(
dfs_perf, dfs, performance_metric=performance_metric, accuracy_metric=accuracy_metric, ideal=ideal)
df = df_performance_accuracy
df = df.groupby(level=df.index.names[:-1]).mean()
#display_in_full(df)
accuracy_metric=accuracy_metric[0]
for index, row in df.iterrows():
(model, backend, batch_size, batch_count, batch_enabled, image_height, image_width) = index
performance = row[performance_metric]
accuracy = row[accuracy_metric]
# Mark Pareto-optimal points.
is_on_pareto = True
for index1, row1 in df.iterrows():
is_no_slower = row1[performance_metric] >= row[performance_metric]
is_no_less_accurate = row1[accuracy_metric] >= row[accuracy_metric]
is_faster = row1[performance_metric] > row[performance_metric]
is_more_accurate = row1[accuracy_metric] > row[accuracy_metric]
if ((is_faster and is_no_less_accurate) or (is_more_accurate and is_no_slower)):
is_on_pareto = False
break
# Select marker, color and size.
marker = backend_to_marker[backend]
color = model_to_color[model]
size = 2 + 4*bs_to_size[batch_size]
# Plot.
ax.plot(performance, accuracy, marker, markerfacecolor=color, markeredgecolor=color, markersize=size)
# Mark Pareto-optimal points with scaled black pluses.
if is_on_pareto:
ax.plot(performance, accuracy, 'o', markersize=4,markerfacecolor='black', markeredgecolor='black')
finalize_plot(ax, xmin, xmax, xstep, ymin, ymax, ystep, save_fig, save_fig_name, accuracy_metric)
# NB: The accuracy metric has to be an array of 1 element for this function.
plot_dse (ideal=False, ystep=2, save_fig=True, save_fig_name='dse.full')
plot_dse (ideal=True, ystep=2, save_fig=True, save_fig_name='dse.full')
plot_dse (ideal=True, accuracy_metric=['mAP_small'], ymin=0, ymax=22.01, ystep=2, save_fig=True, save_fig_name='dse.full.small')
plot_dse (ideal=True, accuracy_metric=['mAP_large'], ymin=30, ymax=78.01, ystep=4, save_fig=True, save_fig_name='dse.full.large')
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def plot_fastest(ideal=False,
performance_metric='avg_fps', accuracy_metric=['mAP','mAP_large','mAP_medium','mAP_small'],
xmin=0.0, xmax=85.01, xstep=5,
ymin=[22,42,16,0], ymax=[46.01,78.01,56.01,22.01], ystep=[2,4,4,2],
labelsize=5, ticksize=4,
save_fig=False, save_fig_name='dse.fastest'):
fig,ax = plt.subplots(2,2,sharex='col')
if ideal:
save_fig_name += '.ideal'
fig.suptitle('Fastest Configuration with Ideal Accuracy')
else:
fig.suptitle('Fastest Configuration with Measured Accuracy')
df_performance_accuracy = merge_performance_accuracy(
dfs_perf, dfs, performance_metric=performance_metric, accuracy_metric=accuracy_metric, ideal=ideal)
df_full = df_performance_accuracy
for num,metric in enumerate (accuracy_metric):
pos = (int(num/2),num%2)
df = df_full[[metric,performance_metric]]
df = df.groupby(level=df.index.names[:-1]).mean()
df = df.groupby(level=df.index.names[:-4]).max()
#display_in_full(df)
points_to_plot=[]
for index, row in df.iterrows():
(model,backend, batch_size) = index
performance = row[performance_metric]
accuracy = row[metric]
plot = True
# Analyze points of the same model.
for index1, row1 in df.iterrows():
if index == index1:
continue
if index1[0] != model:
continue
is_faster = row1[performance_metric] > row[performance_metric]
if is_faster:
plot = False
continue
if plot: # no faster points have been found with the same model.
# Select marker, color and size.
marker = backend_to_marker[backend]
color = model_to_color[model]
size = 2 + 4*bs_to_size[batch_size]
# Plot.
ax[pos[0],pos[1]].plot(performance, accuracy, marker, markerfacecolor=color, markeredgecolor=color, markersize=size)
ax[pos[0],pos[1]].grid(True)
# X axis.
xlabel = 'Images Per Second'
ax[1,0].set_xlabel(xlabel, fontsize=labelsize)
ax[1,0].set_xlim(xmin, xmax)
ax[1,0].set_xticks(np.arange(xmin, xmax, xstep))
for xtick in ax[1,0].xaxis.get_major_ticks(): xtick.label.set_fontsize(ticksize)
ax[1,1].set_xlabel(xlabel, fontsize=labelsize)
ax[1,1].set_xlim(xmin, xmax)
ax[1,1].set_xticks(np.arange(xmin, xmax, xstep))
for xtick in ax[1,1].xaxis.get_major_ticks(): xtick.label.set_fontsize(ticksize)
# Y axis.
ylabel = accuracy_metric[0]+' %'
ax[0,0].set_ylabel(ylabel, fontsize=labelsize)
ax[0,0].set_ylim(ymin[0], ymax[0])
ax[0,0].set_yticks(np.arange(ymin[0], ymax[0], ystep[0]))
for ytick in ax[0,0].yaxis.get_major_ticks(): ytick.label.set_fontsize(ticksize)
ylabel = accuracy_metric[1]+' %'
ax[0,1].set_ylabel(ylabel, fontsize=labelsize)
ax[0,1].set_ylim(ymin[1], ymax[1])
ax[0,1].set_yticks(np.arange(ymin[1], ymax[1], ystep[1]))
for ytick in ax[0,1].yaxis.get_major_ticks(): ytick.label.set_fontsize(ticksize)
ylabel = accuracy_metric[2]+' %'
ax[1,0].set_ylabel(ylabel, fontsize=labelsize)
ax[1,0].set_ylim(ymin[2], ymax[2])
ax[1,0].set_yticks(np.arange(ymin[2], ymax[2], ystep[2]))
for ytick in ax[1,0].yaxis.get_major_ticks(): ytick.label.set_fontsize(ticksize)
ylabel = accuracy_metric[3]+' %'
ax[1,1].set_ylabel(ylabel, fontsize=labelsize)
ax[1,1].set_ylim(ymin[3], ymax[3])
ax[1,1].set_yticks(np.arange(ymin[3], ymax[3], ystep[3]))
for ytick in ax[1,1].yaxis.get_major_ticks(): ytick.label.set_fontsize(ticksize)
# Legend.
handles = [
mp.patches.Patch(color=color, label=model)
for (model, color) in sorted(model_to_color.items())
]
handles += handles2
fig.legend(title='', handles=handles[::-1],
loc='center right',
borderaxespad=0.1,
fontsize=4)
plt.subplots_adjust(right=0.78)
# Show with grid on.
plt.grid(True)
fig1 = plt.gcf()
plt.show()
plt.draw()
# Save figure.
if save_fig:
save_fig_path = os.path.join(save_fig_dir, '%s.%s' % (save_fig_name, save_fig_ext))
fig1.savefig(save_fig_path, dpi=default_figdpi, bbox_inches='tight')
plot_fastest(ideal=True, save_fig=True)
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