Python evaluate_masks Examples

Example #1

File: task_evaluation.py Project: Jakaria08/Detectron

def evaluate_masks(dataset, all_boxes, all_segms, output_dir):
    """Evaluate instance segmentation."""
    logger.info('Evaluating segmentations')
    not_comp = not cfg.TEST.COMPETITION_MODE
    if _use_json_dataset_evaluator(dataset):
        coco_eval = json_dataset_evaluator.evaluate_masks(
            dataset,
            all_boxes,
            all_segms,
            output_dir,
            use_salt=not_comp,
            cleanup=not_comp
        )
        mask_results = _coco_eval_to_mask_results(coco_eval)
    elif _use_cityscapes_evaluator(dataset):
        cs_eval = cs_json_dataset_evaluator.evaluate_masks(
            dataset,
            all_boxes,
            all_segms,
            output_dir,
            use_salt=not_comp,
            cleanup=not_comp
        )
        mask_results = _cs_eval_to_mask_results(cs_eval)
    else:
        raise NotImplementedError(
            'No evaluator for dataset: {}'.format(dataset.name)
        )
    return OrderedDict([(dataset.name, mask_results)])

Example #2

File: task_evaluation.py Project: stoa-xh91/AMA-net

def evaluate_masks(dataset, all_boxes, all_segms, output_dir):
    """Evaluate instance segmentation."""
    logger.info('Evaluating segmentations')
    not_comp = not cfg.TEST.COMPETITION_MODE
    if _use_json_dataset_evaluator(dataset):
        coco_eval = json_dataset_evaluator.evaluate_masks(
            dataset,
            all_boxes,
            all_segms,
            output_dir,
            use_salt=not_comp,
            cleanup=not_comp
        )
        mask_results = _coco_eval_to_mask_results(coco_eval)
    elif _use_cityscapes_evaluator(dataset):
        cs_eval = cs_json_dataset_evaluator.evaluate_masks(
            dataset,
            all_boxes,
            all_segms,
            output_dir,
            use_salt=not_comp,
            cleanup=not_comp
        )
        mask_results = _cs_eval_to_mask_results(cs_eval)
    else:
        raise NotImplementedError(
            'No evaluator for dataset: {}'.format(dataset.name)
        )
    return OrderedDict([(dataset.name, mask_results)])