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Adjust model url

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This commit is contained in:
henryruhs 2024-03-25 21:03:30 +01:00
parent 971055da5f
commit ad5b598a30
1 changed files with 13 additions and 10 deletions
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21
facefusion/face_helper.py
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@ -20,8 +20,8 @@ MODELS : ModelSet =\
{ {
'face_landmark_converter': 'face_landmark_converter':
{ {
'url': 'https://github.com/facefusion/facefusion-assets/releases/download/models/5_to_68_landmark_converter.onnx', 'url': 'https://github.com/facefusion/facefusion-assets/releases/download/models/face_landmarker_5_68.onnx',
'path': resolve_relative_path('../.assets/models/5_to_68_landmark_converter.onnx') 'path': resolve_relative_path('../.assets/models/face_landmarker_5_68.onnx')
} }
} }
@ -160,14 +160,14 @@ def distance_to_face_landmark_5(points : numpy.ndarray[Any, Any], distance : num
return face_landmark_5 return face_landmark_5
def convert_face_landmark_68_to_5(landmark_68 : FaceLandmark68) -> FaceLandmark5: def convert_face_landmark_68_to_5(face_landmark_68 : FaceLandmark68) -> FaceLandmark5:
face_landmark_5 = numpy.array( face_landmark_5 = numpy.array(
[ [
numpy.mean(landmark_68[36:42], axis = 0), numpy.mean(face_landmark_68[36:42], axis = 0),
numpy.mean(landmark_68[42:48], axis = 0), numpy.mean(face_landmark_68[42:48], axis = 0),
landmark_68[30], face_landmark_68[30],
landmark_68[48], face_landmark_68[48],
landmark_68[54] face_landmark_68[54]
]) ])
return face_landmark_5 return face_landmark_5
@ -178,7 +178,10 @@ def convert_face_landmark_5_to_68(face_landmark_5 : FaceLandmark5) -> FaceLandma
affine_matrix = cv2.estimateAffinePartial2D(face_landmark_5, normed_warp_template, method = cv2.RANSAC, ransacReprojThreshold = 100)[0] affine_matrix = cv2.estimateAffinePartial2D(face_landmark_5, normed_warp_template, method = cv2.RANSAC, ransacReprojThreshold = 100)[0]
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_5 = face_landmark_5 / 512
face_landmark_68 = face_landmarker_converter.run(None, {"input": [face_landmark_5]})[0][0] face_landmark_68 = face_landmarker_converter.run(None,
{
face_landmarker_converter.get_inputs()[0].name.get: [ face_landmark_5 ]
})[0][0]
face_landmark_68 = (face_landmark_68 * 512).reshape(68, 2) face_landmark_68 = (face_landmark_68 * 512).reshape(68, 2)
face_landmark_68 = cv2.transform(face_landmark_68.reshape(1, -1, 2), cv2.invertAffineTransform(affine_matrix)).reshape(-1, 2) face_landmark_68 = cv2.transform(face_landmark_68.reshape(1, -1, 2), cv2.invertAffineTransform(affine_matrix)).reshape(-1, 2)
return face_landmark_68 return face_landmark_68