Update app.py

app.py

@@ -88,6 +88,28 @@ def homography_all_detectors(flat_img, persp_img, json_file):
     flat_gray = preprocess_gray_clahe(flat_bgr)
     persp_gray = preprocess_gray_clahe(persp_bgr)
 
+    detectors = ["SIFT", "ORB", "BRISK", "KAZE", "AKAZE"]
+    gallery_images = []
+    download_files = [None] * 5def homography_all_detectors(flat_img, persp_img, json_file):
+    if flat_img is None or persp_img is None:
+        return [None] * 6
+    
+    flat_bgr = cv2.cvtColor(flat_img, cv2.COLOR_RGB2BGR)
+    persp_bgr = cv2.cvtColor(persp_img, cv2.COLOR_RGB2BGR)
+
+    with open(json_file.name, 'r') as f:
+        mockup = json.load(f)
+
+    roi_data = mockup["printAreas"][0]["position"]
+    roi_x = roi_data["x"]
+    roi_y = roi_data["y"]
+    roi_w = mockup["printAreas"][0]["width"]
+    roi_h = mockup["printAreas"][0]["height"]
+    roi_rot_deg = mockup["printAreas"][0]["rotation"]
+
+    flat_gray = preprocess_gray_clahe(flat_bgr)
+    persp_gray = preprocess_gray_clahe(persp_bgr)
+
     detectors = ["SIFT", "ORB", "BRISK", "KAZE", "AKAZE"]
     gallery_images = []
     download_files = [None] * 5
@@ -116,7 +138,37 @@ def homography_all_detectors(flat_img, persp_img, json_file):
         file_name = f"result_{method.lower()}.png"
         cv2.imwrite(file_name, result_rgb[:, :, ::-1])  # save as BGR
 
-        gallery_images.append((f"{method} Result", result_rgb))
+        gallery_images.append(result_rgb)   # ✅ only image
+        download_files[i] = file_name
+
+    return [gallery_images] + download_files
+
+
+    for i, method in enumerate(detectors):
+        kp1, kp2, good_matches = detect_and_match(flat_gray, persp_gray, method=method)
+        if kp1 is None or kp2 is None or len(good_matches) < 4:
+            continue
+        
+        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)
+        H, mask = cv2.findHomography(src_pts, dst_pts, cv2.RANSAC, 5.0)
+
+        if H is None:
+            continue
+
+        roi_corners_flat = get_rotated_rect_corners(roi_x, roi_y, roi_w, roi_h, roi_rot_deg)
+        roi_corners_persp = cv2.perspectiveTransform(roi_corners_flat.reshape(-1,1,2), H).reshape(-1,2)
+
+        persp_debug = persp_bgr.copy()
+        cv2.polylines(persp_debug, [roi_corners_persp.astype(int)], True, (0,255,0), 2)
+        for (px, py) in roi_corners_persp:
+            cv2.circle(persp_debug, (int(px), int(py)), 5, (255,0,0), -1)
+
+        result_rgb = cv2.cvtColor(persp_debug, cv2.COLOR_BGR2RGB)
+        file_name = f"result_{method.lower()}.png"
+        cv2.imwrite(file_name, result_rgb[:, :, ::-1])  # save as BGR
+
+        gallery_images.append(result_rgb)   # ✅ only image
         download_files[i] = file_name
 
     return [gallery_images] + download_files