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)])