imgutils.detect.hand

Overview:

Detect human hands in anime images.

Trained on dataset deepghs/anime_hand_detection with YOLOv8.

This is an overall benchmark of all the hand detect models:

detect_hands

imgutils.detect.hand.detect_hands(image: str | PathLike | bytes | bytearray | BinaryIO | Image, level: str = 's', version: str = 'v1.0', max_infer_size=640, conf_threshold: float = 0.35, iou_threshold: float = 0.7) → List[Tuple[Tuple[int, int, int, int], str, float]]

Overview:

Detect human hand points in anime images.

Parameters:

• image – Image to detect.

• level – The model level being used can be either s or n. The n model runs faster with smaller system overhead, while the s model achieves higher accuracy. The default value is s.

• version – Version of model, default is v1.0.

• max_infer_size – The maximum image size used for model inference, if the image size exceeds this limit, the image will be resized and used for inference. The default value is 640 pixels.

• conf_threshold – The confidence threshold, only detection results with confidence scores above this threshold will be returned. The default value is 0.3.

• iou_threshold – The detection area coverage overlap threshold, areas with overlaps above this threshold will be discarded. The default value is 0.7.

Returns:

The detection results list, each item includes the detected area (x0, y0, x1, y1), the target type (always hand) and the target confidence score.