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import numpy as np
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from insightface.app import FaceAnalysis
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import os
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import folder_paths
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class FaceAnalysis2(FaceAnalysis):
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def get(self, img, max_num=0, det_size=(640, 640)):
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if det_size is not None:
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self.det_model.input_size = det_size
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return super().get(img, max_num)
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def analyze_faces(face_analysis: FaceAnalysis, img_data: np.ndarray, det_size=(640, 640)):
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detection_sizes = [None] + [(size, size) for size in range(640, 256, -64)] + [(256, 256)]
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for size in detection_sizes:
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faces = face_analysis.get(img_data, det_size=size)
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if len(faces) > 0:
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return faces
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return []
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def insightface_loader(provider):
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try:
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from insightface.app import FaceAnalysis
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except ImportError as e:
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raise Exception(e)
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path = os.path.join(folder_paths.models_dir, "insightface")
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model = FaceAnalysis(name="buffalo_l", root=path, providers=[provider + 'ExecutionProvider',])
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model.prepare(ctx_id=0, det_size=(640, 640))
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return model
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