yizhangliu commited on
Commit
bb4525d
·
1 Parent(s): 5a166e2

Update app.py

Browse files
Files changed (1) hide show
  1. app.py +28 -6
app.py CHANGED
@@ -71,6 +71,27 @@ def get_image_ext(img_bytes):
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  def diffuser_callback(i, t, latents):
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  pass
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  def process(init_image, mask):
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  global model
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  '''
@@ -188,7 +209,8 @@ def read_content(file_path: str) -> str:
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  return content
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- def predict(dict, prompt=""):
 
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  init_image = dict["image"] # .convert("RGB") #.resize((512, 512))
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  print(f'liuyz_1_', init_image)
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  print(f'liuyz_2_', init_image.convert("RGB"))
@@ -202,8 +224,8 @@ def predict(dict, prompt=""):
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  css = '''
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  .container {max-width: 1150px;margin: auto;padding-top: 1.5rem}
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- #image_upload{min-height:400px}
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- #image_upload [data-testid="image"], #image_upload [data-testid="image"] > div{min-height: 400px}
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  #mask_radio .gr-form{background:transparent; border: none}
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  #word_mask{margin-top: .75em !important}
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  #word_mask textarea:disabled{opacity: 0.3}
@@ -252,9 +274,9 @@ with image_blocks as demo:
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  with gr.Row(elem_id="prompt-container").style(mobile_collapse=False, equal_height=True):
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  # prompt = gr.Textbox(placeholder = 'Your prompt (what you want in place of what is erased)', show_label=False, elem_id="input-text")
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  btn = gr.Button("Done!").style(
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- margin=False,
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- rounded=(False, True, True, False),
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- full_width=False,
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  )
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  '''
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  with gr.Column():
 
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  def diffuser_callback(i, t, latents):
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  pass
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+ def preprocess_image(image):
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+ w, h = image.size
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+ w, h = map(lambda x: x - x % 32, (w, h)) # resize to integer multiple of 32
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+ image = image.resize((w, h), resample=PIL.Image.LANCZOS)
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+ image = np.array(image).astype(np.float32) / 255.0
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+ image = image[None].transpose(0, 3, 1, 2)
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+ image = torch.from_numpy(image)
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+ return 2.0 * image - 1.0
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+
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+ def preprocess_mask(mask):
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+ mask = mask.convert("L")
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+ w, h = mask.size
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+ w, h = map(lambda x: x - x % 32, (w, h)) # resize to integer multiple of 32
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+ mask = mask.resize((w // 8, h // 8), resample=PIL.Image.NEAREST)
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+ mask = np.array(mask).astype(np.float32) / 255.0
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+ mask = np.tile(mask, (4, 1, 1))
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+ mask = mask[None].transpose(0, 1, 2, 3) # what does this step do?
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+ mask = 1 - mask # repaint white, keep black
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+ mask = torch.from_numpy(mask)
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+ return mask
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+
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  def process(init_image, mask):
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  global model
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  '''
 
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  return content
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+ def predict(dict):
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+ print(f'liuyz_0_', dict)
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  init_image = dict["image"] # .convert("RGB") #.resize((512, 512))
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  print(f'liuyz_1_', init_image)
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  print(f'liuyz_2_', init_image.convert("RGB"))
 
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  css = '''
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  .container {max-width: 1150px;margin: auto;padding-top: 1.5rem}
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+ #image_upload{min-height:auto}
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+ #image_upload [data-testid="image"], #image_upload [data-testid="image"] > div{min-height: auto}
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  #mask_radio .gr-form{background:transparent; border: none}
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  #word_mask{margin-top: .75em !important}
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  #word_mask textarea:disabled{opacity: 0.3}
 
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  with gr.Row(elem_id="prompt-container").style(mobile_collapse=False, equal_height=True):
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  # prompt = gr.Textbox(placeholder = 'Your prompt (what you want in place of what is erased)', show_label=False, elem_id="input-text")
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  btn = gr.Button("Done!").style(
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+ margin=True,
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+ rounded=(True, True, True, True),
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+ full_width=True,
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  )
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  '''
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  with gr.Column():