# from mmdet.evaluation import CocoMetric

# data_root = "/mnt/home/datasets/manual/coco_2017"

val_evaluator = dict(  # Validation evaluator config
    type='CocoMetric',  # The coco metric used to evaluate AR, AP, and mAP for detection and instance segmentation
    ann_file="/mnt/home/datasets/manual/coco_2017/annotations/instances_val2017.json",  # Annotation file path
    # metric=['bbox', 'segm'],  # Metrics to be evaluated, `bbox` for detection and `segm` for instance segmentation
    metric=['bbox'],  # Metrics to be evaluated, `bbox` for detection and `segm` for instance segmentation
    format_only=False,
    backend_args=None)

test_evaluator = val_evaluator