Update app.py

app.py

@@ -43,19 +43,35 @@ def sample_border_color(image, box, padding=2):
     median_color = np.median(border_pixels, axis=0)
     return tuple(map(int, median_color))
 
+# def detect_text_boxes(image):
+#     results = ocr.ocr(image, cls=True)
+#     if not results or not results[0]:
+#         return []
+#     boxes = []
+#     for line in results[0]:
+#         box, (text, confidence) = line
+#         if text.strip():
+#             x_min = int(min(pt[0] for pt in box))
+#             x_max = int(max(pt[0] for pt in box))
+#             y_min = int(min(pt[1] for pt in box))
+#             y_max = int(max(pt[1] for pt in box))
+#             boxes.append(((x_min, y_min, x_max, y_max), text, confidence))
+#     return boxes
+
 def detect_text_boxes(image):
-    results = ocr.ocr(image, cls=True)
-    if not results or not results[0]:
-        return []
+    results = paddle_ocr.ocr(image, cls=True)
     boxes = []
-    for line in results[0]:
-        box, (text, confidence) = line
-        if text.strip():
-            x_min = int(min(pt[0] for pt in box))
-            x_max = int(max(pt[0] for pt in box))
-            y_min = int(min(pt[1] for pt in box))
-            y_max = int(max(pt[1] for pt in box))
-            boxes.append(((x_min, y_min, x_max, y_max), text, confidence))
+    if results and results[0]:
+        for line in results[0]:
+            box, (text, confidence) = line
+            if text.strip():
+                x_min = int(min(pt[0] for pt in box))
+                x_max = int(max(pt[0] for pt in box))
+                y_min = int(min(pt[1] for pt in box))
+                y_max = int(max(pt[1] for pt in box))
+                boxes.append(((x_min, y_min, x_max, y_max), text, confidence))
+    else:
+        print("No text detected in the image.")
     return boxes
 
 def remove_text_dynamic_fill(img_path, output_path):