mirror of https://github.com/vladmandic/automatic
32 lines
1.3 KiB
Python
32 lines
1.3 KiB
Python
from typing import Union
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import cv2
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import numpy as np
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from PIL import Image
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from modules.control.util import HWC3, resize_image
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class MediapipeFaceDetector:
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def __call__(self,
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input_image: Union[np.ndarray, Image.Image] = None,
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max_faces: int = 1,
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min_confidence: float = 0.5,
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output_type: str = "pil",
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detect_resolution: int = 512,
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image_resolution: int = 512,
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**kwargs):
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from .mediapipe_face_util import generate_annotation
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if input_image is None:
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raise ValueError("input_image must be defined.")
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if not isinstance(input_image, np.ndarray):
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input_image = np.array(input_image, dtype=np.uint8)
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input_image = HWC3(input_image)
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input_image = resize_image(input_image, detect_resolution)
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detected_map = generate_annotation(input_image, max_faces, min_confidence)
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detected_map = HWC3(detected_map)
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img = resize_image(input_image, image_resolution)
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H, W, _C = img.shape
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detected_map = cv2.resize(detected_map, (W, H), interpolation=cv2.INTER_LINEAR)
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if output_type == "pil":
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detected_map = Image.fromarray(detected_map)
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return detected_map
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