In [1]:

import json
import logging
import faster_coco_eval
from faster_coco_eval import COCO, COCOeval_faster

print(f"{faster_coco_eval.__version__=}")

logging.root.setLevel("INFO")
logging.debug("Запись.")

faster_coco_eval.__version__='1.4.2'

In [2]:

def load(file):
    with open(file) as io:
        _data = json.load(io)

    return _data

In [3]:

prepared_coco_in_dict = load("../tests/dataset/gt_dataset.json")
prepared_anns = load("../tests/dataset/dt_dataset.json")

In [4]:

iouType = "segm"
useCats = False

In [5]:

cocoGt = COCO(prepared_coco_in_dict)
cocoDt = cocoGt.loadRes(prepared_anns)

cocoEval = COCOeval_faster(cocoGt, cocoDt, iouType, extra_calc=True)
cocoEval.params.maxDets = [len(cocoGt.anns)]

if not useCats:
    cocoEval.params.useCats = 0  # Выключение labels

cocoEval.evaluate()
cocoEval.accumulate()
cocoEval.summarize()

In [6]:

cocoEval.stats

Out[6]:

array([ 0.78327833,  0.78327833,  0.78327833, -1.        ,  1.        ,
        0.        ,  0.88888889,  0.        ,  0.        , -1.        ,
        1.        ,  0.        ])

In [7]:

cocoEval.stats_as_dict

Out[7]:

{'AP_all': 0.7832783278327835,
 'AP_50': 0.7832783278327836,
 'AP_75': 0.7832783278327836,
 'AP_small': -1.0,
 'AP_medium': 1.0,
 'AP_large': 0.0,
 'AR_all': 0.888888888888889,
 'AR_second': 0.0,
 'AR_third': 0.0,
 'AR_small': -1.0,
 'AR_medium': 1.0,
 'AR_large': 0.0,
 'AR_50': 0.8888888888888888,
 'AR_75': 0.8888888888888888,
 'mIoU': 1.0,
 'mAUC_50': 0.594074074074074}