carlosriverat commited on
Commit
ae2249b
·
verified ·
1 Parent(s): b883a76

Update app.py

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Files changed (1) hide show
  1. app.py +9 -5
app.py CHANGED
@@ -33,15 +33,19 @@ def compare_images(image1, image2, blur_value, technique, threshold_value):
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  filtered_contours = [cnt for cnt in contours if cv2.contourArea(cnt) > 500]
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  # Create a mask to isolate only the significant added object
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- mask = np.zeros_like(image1)
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  cv2.drawContours(mask, filtered_contours, -1, (255, 255, 255), thickness=cv2.FILLED)
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  # Apply the mask to highlight the object added in the second image
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  highlighted = cv2.bitwise_and(image2, mask)
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- # Overlay the difference in magenta over the first image
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- diff_colored = cv2.cvtColor(diff, cv2.COLOR_GRAY2BGR)
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- diff_colored[:, :, 1:] = 0 # Keep only red channel for magenta effect
 
 
 
 
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  overlayed = cv2.addWeighted(image1, 0.7, diff_colored, 0.3, 0)
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  return highlighted, overlayed
@@ -68,4 +72,4 @@ with gr.Blocks() as demo:
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  btn = gr.Button("Process")
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  btn.click(compare_images, inputs=[img1, img2, blur_slider, technique_dropdown, threshold_slider], outputs=[output1, output2])
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- demo.launch()
 
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  filtered_contours = [cnt for cnt in contours if cv2.contourArea(cnt) > 500]
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  # Create a mask to isolate only the significant added object
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+ mask = np.zeros_like(image1, dtype=np.uint8)
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  cv2.drawContours(mask, filtered_contours, -1, (255, 255, 255), thickness=cv2.FILLED)
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  # Apply the mask to highlight the object added in the second image
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  highlighted = cv2.bitwise_and(image2, mask)
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+ # Create a magenta overlay where changes occurred
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+ diff_colored = np.zeros_like(image1, dtype=np.uint8)
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+ diff_colored[:, :, 0] = thresh # Set blue channel to zero
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+ diff_colored[:, :, 1] = 0 # Set green channel to zero
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+ diff_colored[:, :, 2] = thresh # Set red channel to highlight in magenta
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+
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+ # Combine the original image with the magenta overlay
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  overlayed = cv2.addWeighted(image1, 0.7, diff_colored, 0.3, 0)
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  return highlighted, overlayed
 
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  btn = gr.Button("Process")
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  btn.click(compare_images, inputs=[img1, img2, blur_slider, technique_dropdown, threshold_slider], outputs=[output1, output2])
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+ demo.launch()