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Merge pull request #22 from faceshiftlabs/build/dev

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Build/dev
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Jeremy Hummel 2019-08-15 21:06:25 +00:00 • committed by GitHub
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3 changed files with 20 additions and 26 deletions
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8
README.md
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@ -1,4 +1,4 @@
![](doc/DFL_welcome.jpg) ![](doc/DFL_welcome.jpg)
![](doc/logo_cuda.jpg)![](doc/logo_opencl.jpg)![](doc/logo_keras.jpg)![](doc/logo_tensorflow.jpg)![](doc/logo_plaidml.jpg) ![](doc/logo_cuda.jpg)![](doc/logo_opencl.jpg)![](doc/logo_keras.jpg)![](doc/logo_tensorflow.jpg)![](doc/logo_plaidml.jpg)
@ -10,12 +10,6 @@ If you like this software, please consider a donation.
GOAL: next DeepFacelab update. GOAL: next DeepFacelab update.
[Donate via Yandex.Money](https://money.yandex.ru/to/41001142318065)
[Donate via Paypal](https://www.paypal.com/cgi-bin/webscr?cmd=_donations&business=lepersorium@gmail.com&lc=US&no_note=0&item_name=Support+DeepFaceLab&cn=&curency_code=USD&bn=PP-DonationsBF:btn_donateCC_LG.gif:NonHosted)
bitcoin:31mPd6DxPCzbpCMZk4k1koWAbErSyqkAXr
- ### [Gallery](doc/gallery/doc_gallery.md) - ### [Gallery](doc/gallery/doc_gallery.md)
- ### Manuals: - ### Manuals:

36
facelib/LandmarksProcessor.py
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@ -116,7 +116,7 @@ def transform_points(points, mat, invert=False):
points = cv2.transform(points, mat, points.shape) points = cv2.transform(points, mat, points.shape)
points = np.squeeze(points) points = np.squeeze(points)
return points return points
def get_transform_mat (image_landmarks, output_size, face_type, scale=1.0): def get_transform_mat (image_landmarks, output_size, face_type, scale=1.0):
if not isinstance(image_landmarks, np.ndarray): if not isinstance(image_landmarks, np.ndarray):
image_landmarks = np.array (image_landmarks) image_landmarks = np.array (image_landmarks)
@ -142,28 +142,28 @@ def get_transform_mat (image_landmarks, output_size, face_type, scale=1.0):
if face_type == FaceType.FULL_NO_ALIGN: if face_type == FaceType.FULL_NO_ALIGN:
face_type = FaceType.FULL face_type = FaceType.FULL
remove_align = True remove_align = True
if face_type == FaceType.HALF:
padding = 0
elif face_type == FaceType.FULL:
padding = (output_size / 64) * 12
elif face_type == FaceType.HEAD:
padding = (output_size / 64) * 24
else:
raise ValueError ('wrong face_type: ', face_type)
mat = umeyama(image_landmarks[17:], landmarks_2D, True)[0:2] if face_type == FaceType.HALF:
mat = mat * (output_size - 2 * padding) padding = 0
mat[:,2] += padding elif face_type == FaceType.FULL:
mat *= (1 / scale) padding = (output_size / 64) * 12
mat[:,2] += -output_size*( ( (1 / scale) - 1.0 ) / 2 ) elif face_type == FaceType.HEAD:
padding = (output_size / 64) * 24
else:
raise ValueError ('wrong face_type: ', face_type)
mat = umeyama(image_landmarks[17:], landmarks_2D, True)[0:2]
mat = mat * (output_size - 2 * padding)
mat[:,2] += padding
mat *= (1 / scale)
mat[:,2] += -output_size*( ( (1 / scale) - 1.0 ) / 2 )
if remove_align: if remove_align:
bbox = transform_points ( [ (0,0), (0,output_size-1), (output_size-1, output_size-1), (output_size-1,0) ], mat, True) bbox = transform_points ( [ (0,0), (0,output_size-1), (output_size-1, output_size-1), (output_size-1,0) ], mat, True)
area = mathlib.polygon_area(bbox[:,0], bbox[:,1] ) area = mathlib.polygon_area(bbox[:,0], bbox[:,1] )
side = math.sqrt(area) / 2 side = math.sqrt(area) / 2
center = transform_points ( [(output_size/2,output_size/2)], mat, True) center = transform_points ( [(output_size/2,output_size/2)], mat, True)
pts1 = np.float32([ center+[-side,-side], center+[side,-side], center+[-side,side] ]) pts1 = np.float32([ center+[-side,-side], center+[side,-side], center+[-side,side] ])
pts2 = np.float32([[0,0],[output_size-1,0],[0,output_size-1]]) pts2 = np.float32([[0,0],[output_size-1,0],[0,output_size-1]])
mat = cv2.getAffineTransform(pts1,pts2) mat = cv2.getAffineTransform(pts1,pts2)
@ -321,7 +321,7 @@ def draw_landmarks (image, image_landmarks, color=(0,255,0), transparent_mask=Fa
mask = get_image_hull_mask (image.shape, image_landmarks, ie_polys) mask = get_image_hull_mask (image.shape, image_landmarks, ie_polys)
image[...] = ( image * (1-mask) + image * mask / 2 )[...] image[...] = ( image * (1-mask) + image * mask / 2 )[...]
def draw_rect_landmarks (image, rect, image_landmarks, face_size, face_type, transparent_mask=False, ie_polys=None, landmarks_color=(0,255,0)): def draw_rect_landmarks (image, rect, image_landmarks, face_size, face_type, transparent_mask=False, ie_polys=None, landmarks_color=(0,255,0) ):
draw_landmarks(image, image_landmarks, color=landmarks_color, transparent_mask=transparent_mask, ie_polys=ie_polys) draw_landmarks(image, image_landmarks, color=landmarks_color, transparent_mask=transparent_mask, ie_polys=ie_polys)
imagelib.draw_rect (image, rect, (255,0,0), 2 ) imagelib.draw_rect (image, rect, (255,0,0), 2 )

2
requirements-cuda.txt
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@ -2,7 +2,7 @@ numpy==1.16.3
h5py==2.9.0 h5py==2.9.0
Keras==2.2.4 Keras==2.2.4
opencv-python==4.0.0.21 opencv-python==4.0.0.21
tensorflow-gpu==1.12.0 tensorflow-gpu==1.14.0
plaidml==0.6.0 plaidml==0.6.0
plaidml-keras==0.5.0 plaidml-keras==0.5.0
scikit-image scikit-image