sczhou commited on
Commit
9928d25
1 Parent(s): e2cccc2

add pre_face_align option.

Browse files
Files changed (1) hide show
  1. app.py +13 -7
app.py CHANGED
@@ -57,6 +57,9 @@ torch.hub.download_url_to_file(
57
  torch.hub.download_url_to_file(
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  'https://replicate.com/api/models/sczhou/codeformer/files/7cf19c2c-e0cf-4712-9af8-cf5bdbb8d0ee/012.jpg',
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  '05.jpg')
 
 
 
60
 
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  def imread(img_path):
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  img = cv2.imread(img_path)
@@ -101,11 +104,11 @@ codeformer_net.eval()
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102
  os.makedirs('output', exist_ok=True)
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104
- def inference(image, background_enhance, face_upsample, upscale, codeformer_fidelity):
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  """Run a single prediction on the model"""
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  try: # global try
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  # take the default setting for the demo
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- has_aligned = False
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  only_center_face = False
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  draw_box = False
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  detection_model = "retinaface_resnet50"
@@ -114,6 +117,7 @@ def inference(image, background_enhance, face_upsample, upscale, codeformer_fide
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  background_enhance = background_enhance if background_enhance is not None else True
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  face_upsample = face_upsample if face_upsample is not None else True
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  upscale = upscale if (upscale is not None and upscale > 0) else 2
 
117
 
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  img = cv2.imread(str(image), cv2.IMREAD_COLOR)
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  print('\timage size:', img.shape)
@@ -271,6 +275,7 @@ td {
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  demo = gr.Interface(
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  inference, [
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  gr.Image(type="filepath", label="Input"),
 
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  gr.Checkbox(value=True, label="Background_Enhance"),
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  gr.Checkbox(value=True, label="Face_Upsample"),
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  gr.Number(value=2, label="Rescaling_Factor (up to 4)"),
@@ -282,11 +287,12 @@ demo = gr.Interface(
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  description=description,
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  article=article,
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  examples=[
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- ['01.png', True, True, 2, 0.7],
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- ['02.jpg', True, True, 2, 0.7],
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- ['03.jpg', True, True, 2, 0.7],
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- ['04.jpg', True, True, 2, 0.1],
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- ['05.jpg', True, True, 2, 0.1]
 
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  ])
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292
  DEBUG = os.getenv('DEBUG') == '1'
 
57
  torch.hub.download_url_to_file(
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  'https://replicate.com/api/models/sczhou/codeformer/files/7cf19c2c-e0cf-4712-9af8-cf5bdbb8d0ee/012.jpg',
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  '05.jpg')
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+ torch.hub.download_url_to_file(
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+ 'https://raw.githubusercontent.com/sczhou/CodeFormer/master/inputs/cropped_faces/0729.png',
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+ '06.png')
63
 
64
  def imread(img_path):
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  img = cv2.imread(img_path)
 
104
 
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  os.makedirs('output', exist_ok=True)
106
 
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+ def inference(image, face_align, background_enhance, face_upsample, upscale, codeformer_fidelity):
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  """Run a single prediction on the model"""
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  try: # global try
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  # take the default setting for the demo
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+ has_aligned = not face_align
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  only_center_face = False
113
  draw_box = False
114
  detection_model = "retinaface_resnet50"
 
117
  background_enhance = background_enhance if background_enhance is not None else True
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  face_upsample = face_upsample if face_upsample is not None else True
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  upscale = upscale if (upscale is not None and upscale > 0) else 2
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+ upscale = 1 if has_aligned else upscale
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122
  img = cv2.imread(str(image), cv2.IMREAD_COLOR)
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  print('\timage size:', img.shape)
 
275
  demo = gr.Interface(
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  inference, [
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  gr.Image(type="filepath", label="Input"),
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+ gr.Checkbox(value=True, label="Pre_Face_Align"),
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  gr.Checkbox(value=True, label="Background_Enhance"),
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  gr.Checkbox(value=True, label="Face_Upsample"),
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  gr.Number(value=2, label="Rescaling_Factor (up to 4)"),
 
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  description=description,
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  article=article,
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  examples=[
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+ ['01.png', True, True, True, 2, 0.7],
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+ ['02.jpg', True, True, True, 2, 0.7],
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+ ['03.jpg', True, True, True, 2, 0.7],
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+ ['04.jpg', True, True, True, 2, 0.1],
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+ ['05.jpg', True, True, True, 2, 0.1],
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+ ['06.png', False, True, True, 1, 0.5]
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  ])
297
 
298
  DEBUG = os.getenv('DEBUG') == '1'