Update app.py

app.py

@@ -101,6 +101,9 @@ def process_image(image_path):
     # Load the image
     image = cv2.imread(image_path)
 
+    # Convert the image to RGB format
+    image_rgb = cv2.cvtColor(image, cv2.COLOR_BGR2RGB)
+
     # Resize segmentation mask to match the input image dimensions
     segmentation_mask_resized = cv2.resize(segmentation_mask, (image.shape[1], image.shape[0]))
 
@@ -110,14 +113,20 @@ def process_image(image_path):
         # Crop the segmented region based on the bounding box
         cropped_segment = image[int(y1):int(y2), int(x1):int(x2)]
 
+        # Convert the cropped segment to RGB
+        cropped_segment_rgb = cv2.cvtColor(cropped_segment, cv2.COLOR_BGR2RGB)
+
         # Save the cropped segmented image
         cropped_image_path = 'output/cropped_segment.jpg'
         cv2.imwrite(cropped_image_path, cropped_segment)
         print(f"Cropped segmented image saved to {cropped_image_path}")
 
-        st.image(cropped_segment, caption="Uploaded Image", use_column_width=True)
-        # Return the cropped image
-        return cropped_segment
+        # Display the image in Streamlit
+        st.image(cropped_segment_rgb, caption="Uploaded Image (Cropped)", use_column_width=True)
+
+        # Return the cropped RGB image
+        return cropped_segment_rgb
+
 
 def transform_string(input_str):
     # Remove extra spaces and convert to lowercase