Update app.py

app.py

@@ -93,6 +93,7 @@ def get_bounding_box_points(json_data):
 def process_and_plot_all_detectors(image1_np, image2_np, json_file):
     """
     Processes the images with all available detectors and returns image data for display and download.
+    Keeps original RGB colors intact.
     """
     if image1_np is None or image2_np is None:
         return [None] * 6
@@ -114,29 +115,34 @@ def process_and_plot_all_detectors(image1_np, image2_np, json_file):
         if H is not None:
             box_points = get_bounding_box_points(data)
             
-            output_flat_img = image1_np.copy()
+            # Convert RGB → BGR for OpenCV drawing
+            output_flat_img = cv2.cvtColor(image1_np, cv2.COLOR_RGB2BGR)
             cv2.polylines(output_flat_img, [np.int32(box_points)], isClosed=True, color=(0, 0, 255), thickness=5)
 
             transformed_box_points = cv2.perspectiveTransform(box_points, H)
 
-            output_perspective_img = image2_np.copy()
+            output_perspective_img = cv2.cvtColor(image2_np, cv2.COLOR_RGB2BGR)
             cv2.polylines(output_perspective_img, [np.int32(transformed_box_points)], isClosed=True, color=(0, 0, 255), thickness=5)
 
+            # Convert BGR → RGB for display
+            output_flat_img = cv2.cvtColor(output_flat_img, cv2.COLOR_BGR2RGB)
+            output_perspective_img = cv2.cvtColor(output_perspective_img, cv2.COLOR_BGR2RGB)
+
+            # Plot images side by side
             fig, axes = plt.subplots(1, 3, figsize=(18, 6))
-            axes[0].imshow(cv2.cvtColor(output_flat_img, cv2.COLOR_BGR2RGB))
+            axes[0].imshow(output_flat_img)
             axes[0].set_title(f'Original (Flat) - {detector_type}')
             axes[0].axis('off')
 
-            axes[1].imshow(cv2.cvtColor(image2_np, cv2.COLOR_BGR2RGB))
+            axes[1].imshow(image2_np)  # original perspective image in RGB
             axes[1].set_title('Original (Perspective)')
             axes[1].axis('off')
 
-            axes[2].imshow(cv2.cvtColor(output_perspective_img, cv2.COLOR_BGR2RGB))
+            axes[2].imshow(output_perspective_img)
             axes[2].set_title('Projected Bounding Box')
             axes[2].axis('off')
             
             plt.tight_layout()
-            
             file_name = f"result_{detector_type.lower()}.png"
             plt.savefig(file_name)
             plt.close(fig)
@@ -145,11 +151,11 @@ def process_and_plot_all_detectors(image1_np, image2_np, json_file):
             download_files[i] = file_name
         else:
             print(f"Warning: Homography matrix could not be found with {detector_type} detector. Skipping this result.")
-            # We don't append None to the gallery_images list to avoid the error.
-            # download_files[i] remains None, which is handled correctly by gr.File.
-    
+            # download_files[i] remains None
+
     return [gallery_images] + download_files
 
+
 iface = gr.Interface(
     fn=process_and_plot_all_detectors,
     inputs=[