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run_coco_eval.py
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/
run_coco_eval.py
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"""
Runs the coco-supplied cocoeval script to evaluate detections
outputted by using the output_coco_json flag in eval.py.
"""
import argparse
from pycocotools.coco import COCO
from pycocotools.cocoeval import COCOeval
parser = argparse.ArgumentParser(description='COCO Detections Evaluator')
parser.add_argument('--bbox_det_file', default='results/bbox_detections.json', type=str)
parser.add_argument('--mask_det_file', default='results/mask_detections.json', type=str)
parser.add_argument('--gt_ann_file', default='data/coco/annotations/instances_val2017.json', type=str)
parser.add_argument('--eval_type', default='both', choices=['bbox', 'mask', 'both'], type=str)
args = parser.parse_args()
if __name__ == '__main__':
eval_bbox = (args.eval_type in ('bbox', 'both'))
eval_mask = (args.eval_type in ('mask', 'both'))
print('Loading annotations...')
gt_annotations = COCO(args.gt_ann_file)
if eval_bbox:
bbox_dets = gt_annotations.loadRes(args.bbox_det_file)
if eval_mask:
mask_dets = gt_annotations.loadRes(args.mask_det_file)
if eval_bbox:
print('\nEvaluating BBoxes:')
bbox_eval = COCOeval(gt_annotations, bbox_dets, 'bbox')
bbox_eval.evaluate()
bbox_eval.accumulate()
bbox_eval.summarize()
if eval_mask:
print('\nEvaluating Masks:')
bbox_eval = COCOeval(gt_annotations, mask_dets, 'segm')
bbox_eval.evaluate()
bbox_eval.accumulate()
bbox_eval.summarize()