In [1]:

import json
import logging
import faster_coco_eval
from faster_coco_eval import COCO, COCOeval_faster
from faster_coco_eval.extra import Curves

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

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

faster_coco_eval.__version__='1.5.4'

In [2]:

prepared_coco_in_dict = COCO.load_json("../tests/kp_dataset/gt_dataset.json")
prepared_anns = COCO.load_json("../tests/kp_dataset/dt_dataset.json")

In [3]:

iouType = "keypoints"

In [4]:

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

cocoEval = COCOeval_faster(
    cocoGt, cocoDt, iouType, extra_calc=True, kpt_oks_sigmas=[0.025] * 4
)

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

In [5]:

cocoEval.stats_as_dict

Out[5]:

{'AP_all': 0.9763163924878505,
 'AP_50': 0.9801980198019802,
 'AP_75': 0.9801980198019802,
 'AP_medium': -1.0,
 'AP_large': 0.9763163924878505,
 'AR_all': 0.982608695652174,
 'AR_second': 0.9855072463768116,
 'AR_third': 0.9855072463768116,
 'AR_medium': -1.0,
 'AR_large': 0.982608695652174,
 'mIoU': 0.9743220702458776,
 'mAUC_50': 0.98}

In [6]:

cur = Curves(cocoGt, cocoDt, iouType=iouType, kpt_oks_sigmas=[0.025] * 4)

cur.plot_ced_metric()
cur.plot_f1_confidence()

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