ashawkey commited on
Commit
02a7da8
·
1 Parent(s): d396bca
Files changed (1) hide show
  1. app.py +3 -3
app.py CHANGED
@@ -70,7 +70,6 @@ def get_random_seed(randomize_seed, seed):
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  @spaces.GPU(duration=10)
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  def process_image(image_path):
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  image = cv2.imread(image_path, cv2.IMREAD_UNCHANGED)
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- image = cv2.resize(image, (518, 518), interpolation=cv2.INTER_AREA)
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  if image.shape[-1] == 4:
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  image = cv2.cvtColor(image, cv2.COLOR_BGRA2RGBA)
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  else:
@@ -79,6 +78,7 @@ def process_image(image_path):
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  image = rembg.remove(image, session=bg_remover) # [H, W, 4]
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  mask = image[..., -1] > 0
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  image = recenter_foreground(image, mask, border_ratio=0.1)
 
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  image = image.astype(np.float32) / 255.0
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  image = image[..., :3] * image[..., 3:4] + (1 - image[..., 3:4]) # white background
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  image = (image * 255).astype(np.uint8)
@@ -166,8 +166,8 @@ with block:
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  with gr.Column(scale=1):
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  with gr.Row():
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  # input image
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- input_image = gr.Image(label="Input Image", type="filepath") # use file_path and load manually
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- seg_image = gr.Image(label="Segmentation Result", type="numpy", interactive=False)
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  with gr.Accordion("Settings", open=True):
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  # inference steps
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  num_steps = gr.Slider(label="Inference steps", minimum=1, maximum=100, step=1, value=50)
 
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  @spaces.GPU(duration=10)
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  def process_image(image_path):
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  image = cv2.imread(image_path, cv2.IMREAD_UNCHANGED)
 
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  if image.shape[-1] == 4:
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  image = cv2.cvtColor(image, cv2.COLOR_BGRA2RGBA)
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  else:
 
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  image = rembg.remove(image, session=bg_remover) # [H, W, 4]
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  mask = image[..., -1] > 0
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  image = recenter_foreground(image, mask, border_ratio=0.1)
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+ image = cv2.resize(image, (518, 518), interpolation=cv2.INTER_AREA)
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  image = image.astype(np.float32) / 255.0
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  image = image[..., :3] * image[..., 3:4] + (1 - image[..., 3:4]) # white background
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  image = (image * 255).astype(np.uint8)
 
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  with gr.Column(scale=1):
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  with gr.Row():
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  # input image
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+ input_image = gr.Image(label="Input Image", type="filepath", image_mode="RGBA") # use file_path and load manually
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+ seg_image = gr.Image(label="Segmentation Result", type="numpy", interactive=False, image_mode="RGBA")
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  with gr.Accordion("Settings", open=True):
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  # inference steps
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  num_steps = gr.Slider(label="Inference steps", minimum=1, maximum=100, step=1, value=50)