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Harisreedhar 2024-03-26 13:09:09 +05:30 committed by GitHub
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facefusion/face_analyser.py
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@ -399,14 +399,12 @@ def detect_face_landmark_68(temp_vision_frame : VisionFrame, bounding_box : Boun
def expand_face_landmark_68_from_5(face_landmark_5 : FaceLandmark5) -> FaceLandmark68: def expand_face_landmark_68_from_5(face_landmark_5 : FaceLandmark5) -> FaceLandmark68:
face_landmarker = get_face_analyser().get('face_landmarkers').get('68_5') face_landmarker = get_face_analyser().get('face_landmarkers').get('68_5')
affine_matrix = estimate_matrix_by_face_landmark_5(face_landmark_5, 'ffhq_512', (512, 512)) affine_matrix = estimate_matrix_by_face_landmark_5(face_landmark_5, 'ffhq_512', (1, 1))
face_landmark_5 = cv2.transform(face_landmark_5.reshape(1, -1, 2), affine_matrix).reshape(-1, 2) face_landmark_5 = cv2.transform(face_landmark_5.reshape(1, -1, 2), affine_matrix).reshape(-1, 2)
face_landmark_5 = face_landmark_5 / 512
face_landmark_68_5 = face_landmarker.run(None, face_landmark_68_5 = face_landmarker.run(None,
{ {
face_landmarker.get_inputs()[0].name: [ face_landmark_5 ] face_landmarker.get_inputs()[0].name: [ face_landmark_5 ]
})[0][0] })[0][0]
face_landmark_68_5 = (face_landmark_68_5 * 512).reshape(68, 2)
face_landmark_68_5 = cv2.transform(face_landmark_68_5.reshape(1, -1, 2), cv2.invertAffineTransform(affine_matrix)).reshape(-1, 2) face_landmark_68_5 = cv2.transform(face_landmark_68_5.reshape(1, -1, 2), cv2.invertAffineTransform(affine_matrix)).reshape(-1, 2)
return face_landmark_68_5 return face_landmark_68_5