dvj4 commited on
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39bf10f
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1 Parent(s): 9d44b11

Update app.py

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Files changed (1) hide show
  1. app.py +1 -13
app.py CHANGED
@@ -7,35 +7,23 @@ from huggingface_hub import hf_shiny as hf
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  def process_image(image):
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  # Convert image to numpy array
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  img_array = np.array(image)
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-
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- # Dummy sidewalk segmentation (replace with your actual segmentation algorithm)
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  patch_size = 128
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  step = 128
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-
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  all_img_patches = []
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-
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  for i in range(0, img_array.shape[0] - patch_size + 1, step):
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  for j in range(0, img_array.shape[1] - patch_size + 1, step):
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  single_patch_img = img_array[i:i + patch_size, j:j + patch_size]
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  all_img_patches.append(single_patch_img)
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-
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  images = np.array(all_img_patches)
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-
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- # Perform your actual image processing here
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- # Replace the code below with your segmentation algorithm or any other processing you need
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- # This is just a dummy example to show how to process the image
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  processed_images = []
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  for img in images:
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  processed_image = np.mean(img, axis=-1) # Example: Convert to grayscale
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  processed_images.append(processed_image)
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-
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  processed_images = np.array(processed_images)
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-
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  return processed_images
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-
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  # Define Shiny app
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  app = hf.start()
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-
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  @app.streamlit_app(
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  title="Sidewalk Segmentation App",
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  uploaders={"Upload an image": ["jpg", "jpeg", "png"]}
 
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  def process_image(image):
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  # Convert image to numpy array
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  img_array = np.array(image)
 
 
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  patch_size = 128
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  step = 128
 
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  all_img_patches = []
 
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  for i in range(0, img_array.shape[0] - patch_size + 1, step):
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  for j in range(0, img_array.shape[1] - patch_size + 1, step):
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  single_patch_img = img_array[i:i + patch_size, j:j + patch_size]
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  all_img_patches.append(single_patch_img)
 
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  images = np.array(all_img_patches)
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+ # This is just a example to process the image
 
 
 
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  processed_images = []
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  for img in images:
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  processed_image = np.mean(img, axis=-1) # Example: Convert to grayscale
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  processed_images.append(processed_image)
 
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  processed_images = np.array(processed_images)
 
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  return processed_images
 
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  # Define Shiny app
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  app = hf.start()
 
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  @app.streamlit_app(
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  title="Sidewalk Segmentation App",
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  uploaders={"Upload an image": ["jpg", "jpeg", "png"]}