turhancan97 commited on
Commit
af03c71
·
1 Parent(s): 6bca9ba
Files changed (1) hide show
  1. app.py +15 -23
app.py CHANGED
@@ -41,7 +41,7 @@ def show_image(img, title):
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  plt.title(title)
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  # Visualize a Single Image
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- def visualize_single_image(image_path, image_name, model, device):
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  img = load_image(image_path, transform).to(device)
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  # Run inference
@@ -56,46 +56,38 @@ def visualize_single_image(image_path, image_name, model, device):
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  # MAE reconstruction pasted with visible patches
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  im_paste = img * (1 - mask) + predicted_img * mask
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- # make the plt figure larger
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- plt.figure(figsize=(12, 4))
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- plt.subplot(1, 4, 1)
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- show_image(img[0], "original")
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- plt.subplot(1, 4, 2)
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- show_image(im_masked[0], "masked")
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- plt.subplot(1, 4, 3)
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- show_image(predicted_img[0], "reconstruction")
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- plt.subplot(1, 4, 4)
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- show_image(im_paste[0], "reconstruction + visible")
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- plt.tight_layout()
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- return plt
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-
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- # Example Usage
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- image_path = 'images/dog.jpg' # Replace with the actual path to your image
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- # take the string after the last '/' as the image name
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- image_name = image_path.split('/')[-1].split('.')[0]
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- visualize_single_image(image_path, image_name, model, device)
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  inputs_image = [
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  gr.components.Image(type="filepath", label="Input Image"),
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  ]
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  outputs_image = [
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- gr.components.Image(type="plot", label="Output Image"),
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  ]
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  gr.Interface(
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  fn=visualize_single_image,
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  inputs=inputs_image,
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  outputs=outputs_image,
 
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  title="MAE-ViT Image Reconstruction",
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  description="This is a demo of the MAE-ViT model for image reconstruction.",
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- allow_flagging=False,
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- allow_screenshot=False,
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- allow_remote_access=False,
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  ).launch()
 
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  plt.title(title)
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  # Visualize a Single Image
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+ def visualize_single_image(image_path):
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  img = load_image(image_path, transform).to(device)
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  # Run inference
 
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  # MAE reconstruction pasted with visible patches
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  im_paste = img * (1 - mask) + predicted_img * mask
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+ # # make the plt figure larger
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+ # plt.figure(figsize=(12, 4))
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+ # plt.subplot(1, 4, 1)
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+ # show_image(img[0], "original")
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+ # plt.subplot(1, 4, 2)
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+ # show_image(im_masked[0], "masked")
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+ # plt.subplot(1, 4, 3)
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+ # show_image(predicted_img[0], "reconstruction")
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+ # plt.subplot(1, 4, 4)
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+ # show_image(im_paste[0], "reconstruction + visible")
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+ # plt.tight_layout()
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+ return img[0].numpy(), im_masked[0].numpy(), predicted_img[0].numpy(), im_paste[0].numpy()
 
 
 
 
 
 
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  inputs_image = [
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  gr.components.Image(type="filepath", label="Input Image"),
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  ]
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  outputs_image = [
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+ gr.components.Image(type="numpy", label="Output Image"),
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  ]
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  gr.Interface(
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  fn=visualize_single_image,
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  inputs=inputs_image,
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  outputs=outputs_image,
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+ examples=path,
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  title="MAE-ViT Image Reconstruction",
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  description="This is a demo of the MAE-ViT model for image reconstruction.",
 
 
 
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  ).launch()