def evaluate_keypoints(dataset, all_boxes, all_keyps, output_dir):
logger.info('Evaluating detections')
not_comp = not cfg.TEST.COMPETITION_MODE
if dataset.name.startswith('keypoints_coco_'):
import datasets.json_dataset_evaluator as json_dataset_evaluator
json_dataset_evaluator.evaluate_keypoints(
dataset, all_boxes, all_keyps, output_dir,
use_salt=not_comp, cleanup=not_comp)
else:
raise NotImplementedError(
'No evaluator for dataset: {}'.format(dataset.name))
def evaluate_keypoints(dataset, all_boxes, all_keyps, output_dir):
"""Evaluate human keypoint detection (i.e., 2D pose estimation)."""
logger.info('Evaluating detections')
not_comp = not cfg.TEST.COMPETITION_MODE
assert dataset.name.startswith('keypoints_coco_'), \
'Only COCO keypoints are currently supported'
coco_eval = json_dataset_evaluator.evaluate_keypoints(dataset,
all_boxes,
all_keyps,
output_dir,
use_salt=not_comp,
cleanup=not_comp)
keypoint_results = _coco_eval_to_keypoint_results(coco_eval)
return OrderedDict([(dataset.name, keypoint_results)])
def evaluate_keypoints(dataset, all_boxes, all_keyps, output_dir):
"""Evaluate human keypoint detection (i.e., 2D pose estimation)."""
logger.info('Evaluating detections')
not_comp = not cfg.TEST.COMPETITION_MODE
assert dataset.name.startswith('keypoints_coco_'), \
'Only COCO keypoints are currently supported'
coco_eval = json_dataset_evaluator.evaluate_keypoints(
dataset,
all_boxes,
all_keyps,
output_dir,
use_salt=not_comp,
cleanup=not_comp
)
keypoint_results = _coco_eval_to_keypoint_results(coco_eval)
return OrderedDict([(dataset.name, keypoint_results)])
