| import warnings | |
| from typing import Union | |
| import cv2 | |
| import numpy as np | |
| from PIL import Image | |
| from ..util import HWC3, resize_image | |
| from .mediapipe_face_common import generate_annotation | |
| class MediapipeFaceDetector: | |
| def __call__(self, | |
| input_image: Union[np.ndarray, Image.Image] = None, | |
| max_faces: int = 1, | |
| min_confidence: float = 0.5, | |
| output_type: str = "pil", | |
| detect_resolution: int = 512, | |
| image_resolution: int = 512, | |
| **kwargs): | |
| if "image" in kwargs: | |
| warnings.warn("image is deprecated, please use `input_image=...` instead.", DeprecationWarning) | |
| input_image = kwargs.pop("image") | |
| if input_image is None: | |
| raise ValueError("input_image must be defined.") | |
| if "return_pil" in kwargs: | |
| warnings.warn("return_pil is deprecated. Use output_type instead.", DeprecationWarning) | |
| output_type = "pil" if kwargs["return_pil"] else "np" | |
| if type(output_type) is bool: | |
| warnings.warn("Passing `True` or `False` to `output_type` is deprecated and will raise an error in future versions") | |
| if output_type: | |
| output_type = "pil" | |
| if not isinstance(input_image, np.ndarray): | |
| input_image = np.array(input_image, dtype=np.uint8) | |
| input_image = HWC3(input_image) | |
| input_image = resize_image(input_image, detect_resolution) | |
| detected_map = generate_annotation(input_image, max_faces, min_confidence) | |
| detected_map = HWC3(detected_map) | |
| img = resize_image(input_image, image_resolution) | |
| H, W, C = img.shape | |
| detected_map = cv2.resize(detected_map, (W, H), interpolation=cv2.INTER_LINEAR) | |
| if output_type == "pil": | |
| detected_map = Image.fromarray(detected_map) | |
| return detected_map | |