Update app.py

app.py

@@ -59,6 +59,7 @@ def pad_to_size(img, target_h, target_w):
     canvas[top_pad:top_pad+h, left_pad:left_pad+w] = img
     return canvas
 
+# ---------------- Main Function ----------------
 def homography_all_detectors(flat_file, persp_file, json_file, xml_file):
     flat_img = cv2.imread(flat_file)
     persp_img = cv2.imread(persp_file)
@@ -76,17 +77,11 @@ def homography_all_detectors(flat_file, persp_file, json_file, xml_file):
     gallery_paths = []
     download_files = []
 
-    # Perspective image size
-    target_h, target_w = persp_img.shape[:2]
-
     for method in methods:
         kp1,kp2,good_matches = detect_and_match(flat_gray,persp_gray,method)
         if kp1 is None or kp2 is None or len(good_matches)<4: continue
 
-        # Resize/pad flat image to perspective image size
-        flat_pad = pad_to_size(flat_img, target_h, target_w)
-
-        match_img = cv2.drawMatches(flat_pad,kp1,persp_img,kp2,good_matches,None,flags=2)
+        match_img = cv2.drawMatches(flat_img,kp1,persp_img,kp2,good_matches,None,flags=2)
 
         src_pts = np.float32([kp1[m.queryIdx].pt for m in good_matches]).reshape(-1,1,2)
         dst_pts = np.float32([kp2[m.trainIdx].pt for m in good_matches]).reshape(-1,1,2)
@@ -100,7 +95,7 @@ def homography_all_detectors(flat_file, persp_file, json_file, xml_file):
         cv2.polylines(persp_roi,[roi_corners_persp.astype(int)],True,(0,255,0),2)
         for px,py in roi_corners_persp: cv2.circle(persp_roi,(int(px),int(py)),5,(255,0,0),-1)
 
-        # XML GT overlay
+        # XML Ground-Truth overlay
         xml_gt_img = persp_img.copy()
         ordered_pts = ['TopLeft', 'TopRight', 'BottomRight', 'BottomLeft']
         xml_polygon = [xml_points[pt] for pt in ordered_pts]
@@ -108,18 +103,23 @@ def homography_all_detectors(flat_file, persp_file, json_file, xml_file):
         cv2.polylines(xml_gt_img,[pts],isClosed=True,color=(255,0,0),thickness=3)
 
         # Convert to RGB
-        flat_rgb = cv2.cvtColor(flat_pad,cv2.COLOR_BGR2RGB)
+        flat_rgb = cv2.cvtColor(flat_img,cv2.COLOR_BGR2RGB)
         match_rgb = cv2.cvtColor(match_img,cv2.COLOR_BGR2RGB)
         roi_rgb = cv2.cvtColor(persp_roi,cv2.COLOR_BGR2RGB)
         xml_rgb = cv2.cvtColor(xml_gt_img,cv2.COLOR_BGR2RGB)
 
-        # Pad all images to same size (optional here, already same)
-        max_h, max_w = target_h, target_w
+        # Determine max height and width
+        max_h = max(flat_rgb.shape[0], match_rgb.shape[0], roi_rgb.shape[0], xml_rgb.shape[0])
+        max_w = max(flat_rgb.shape[1], match_rgb.shape[1], roi_rgb.shape[1], xml_rgb.shape[1])
+
+        # Pad images
+        flat_pad = pad_to_size(flat_rgb, max_h, max_w)
+        match_pad = pad_to_size(match_rgb, max_h, max_w)
         roi_pad = pad_to_size(roi_rgb, max_h, max_w)
         xml_pad = pad_to_size(xml_rgb, max_h, max_w)
 
         # Merge 2x2 grid
-        top = np.hstack([flat_rgb, match_rgb])
+        top = np.hstack([flat_pad, match_pad])
         bottom = np.hstack([roi_pad, xml_pad])
         combined_grid = np.vstack([top, bottom])
 
@@ -132,6 +132,7 @@ def homography_all_detectors(flat_file, persp_file, json_file, xml_file):
 
     while len(download_files)<5: download_files.append(None)
     return gallery_paths, download_files[0], download_files[1], download_files[2], download_files[3], download_files[4]
+
     
 # ---------------- Gradio UI ----------------
 iface = gr.Interface(