yizhangliu commited on
Commit
31e7adc
1 Parent(s): 98d0e5b

Update app.py

Browse files
Files changed (1) hide show
  1. app.py +6 -6
app.py CHANGED
@@ -223,7 +223,7 @@ def model_process(input): #image, mask):
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  # {'image': '/tmp/tmp8mn9xw93.png', 'mask': '/tmp/tmpn5ars4te.png'}
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  # input = request.files
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  # RGB
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- origin_image_bytes = input["image"].read()
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  print(f'origin_image_bytes = ', type(origin_image_bytes), len(origin_image_bytes))
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  image, alpha_channel = load_img(origin_image_bytes)
@@ -274,7 +274,7 @@ def model_process(input): #image, mask):
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  logger.info(f"Resized image shape: {image.shape} / {type(image)}")
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  print(f"Resized image shape: {image.shape} / {image[250][250]}")
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- mask, _ = load_img(input["mask"].read(), gray=True)
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  mask = resize_max_size(mask, size_limit=size_limit, interpolation=interpolation)
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  print(f"mask image shape: {mask.shape} / {type(mask)} / {mask[250][250]}")
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@@ -339,8 +339,8 @@ def read_content(file_path: str) -> str:
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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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  '''
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  image = dict["image"] # .convert("RGB") #.resize((512, 512))
@@ -351,7 +351,7 @@ def predict(dict):
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  # mask = dict["mask"] # .convert("RGB") #.resize((512, 512))
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  '''
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- output = model_process(dict) # dict["image"], dict["mask"])
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  # output = mask #output.images[0]
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  # output = pipe(prompt = prompt, image=init_image, mask_image=mask,guidance_scale=7.5)
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@@ -447,7 +447,7 @@ with image_blocks as demo:
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  with gr.Box():
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  with gr.Row():
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  with gr.Column():
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- image = gr.Image(source='upload', tool='sketch', type='file',label="Upload").style(height=512)
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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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  # {'image': '/tmp/tmp8mn9xw93.png', 'mask': '/tmp/tmpn5ars4te.png'}
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  # input = request.files
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  # RGB
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+ origin_image_bytes = open(input["image"],'rb').read()
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  print(f'origin_image_bytes = ', type(origin_image_bytes), len(origin_image_bytes))
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  image, alpha_channel = load_img(origin_image_bytes)
 
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  logger.info(f"Resized image shape: {image.shape} / {type(image)}")
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  print(f"Resized image shape: {image.shape} / {image[250][250]}")
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+ mask, _ = load_img(open(input["mask"],'rb').read(), gray=True)
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  mask = resize_max_size(mask, size_limit=size_limit, interpolation=interpolation)
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  print(f"mask image shape: {mask.shape} / {type(mask)} / {mask[250][250]}")
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  return content
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+ def predict(input):
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+ print(f'liuyz_0_', input)
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  '''
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  image = dict["image"] # .convert("RGB") #.resize((512, 512))
 
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  # mask = dict["mask"] # .convert("RGB") #.resize((512, 512))
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  '''
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+ output = model_process(input) # dict["image"], dict["mask"])
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  # output = mask #output.images[0]
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  # output = pipe(prompt = prompt, image=init_image, mask_image=mask,guidance_scale=7.5)
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  with gr.Box():
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  with gr.Row():
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  with gr.Column():
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+ image = gr.Image(source='upload', tool='sketch', type='filepath',label="Upload").style(height=512)
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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(