Update app.py

app.py

@@ -13,58 +13,57 @@ def process_bank_form(image):
         return "Please upload an image."
 
     try:
-        # 1. Initialize if not already done
+        # 1. LAZY LOAD MODEL (Standard 2026 init)
         if ocr_instance is None:
             ocr_instance = PaddleOCR(
                 lang='en', 
-                ocr_version='PP-OCRv4',
+                ocr_version='PP-OCRv5', # Using latest v5 for best handwriting
                 use_angle_cls=True
             )
 
-        # 2. Standardize Image
+        # 2. IMAGE STANDARDIZATION
         img = image.convert("RGB")
-        img = ImageOps.exif_transpose(img)
+        img = ImageOps.exif_transpose(img) # Prevents 'sideways' photo errors
         img_array = np.array(img)
         
-        # 3. Run OCR
+        # 3. RUN OCR
         result = ocr_instance.ocr(img_array)
 
-        # 4. DEFENSIvE PARSING (Fixes 'index out of range')
-        if not result or not isinstance(result, list) or len(result) == 0:
-            return "No text detected."
+        # 4. DEEP DEFENSIVE PARSING (Fixes 'index out of range')
+        if not result or not isinstance(result, list) or len(result) == 0 or result[0] is None:
+            return "No text detected. Try a closer, clearer photo."
 
         extracted_text = []
         
-        # result[0] is the list of detected lines
+        # result[0] is the list of detected lines/boxes
         for line in result[0]:
-            # Each line MUST be a list with at least 2 elements: [coordinates, [text, conf]]
+            # Each 'line' must be a list: [ [coordinates], [text, confidence] ]
             if isinstance(line, list) and len(line) >= 2:
                 content = line[1] # This should be [text, confidence]
                 
-                # Verify content is a list and has at least 1 element (the text)
-                if isinstance(content, (list, tuple)) and len(content) >= 1:
+                # Check if 'content' has a list with at least the text string
+                if isinstance(content, (list, tuple)) and len(content) > 0:
                     text_val = content[0]
                     
-                    # Finally, ensure it's a valid string before adding
+                    # Ensure it's a valid string and skip if empty
                     if text_val and isinstance(text_val, str):
                         extracted_text.append(text_val.strip())
         
         if not extracted_text:
-            return "AI saw boxes but couldn't recognize any characters. Try more light."
+            return "AI found text boxes but couldn't read characters. Try cropping the image."
             
         return "\n".join(extracted_text)
 
     except Exception as e:
-        # Catch the specific error and give better feedback
-        return f"Recognition Error: {str(e)}\nTip: This usually happens with low-quality scans. Try cropping to a smaller area."
+        return f"System Error: {str(e)}\nTip: If it persists, use 'Factory Reboot' in Space Settings."
 
 # UI
 demo = gr.Interface(
     fn=process_bank_form,
-    inputs=gr.Image(type="pil"),
-    outputs=gr.Textbox(label="Result", lines=20),
-    title="🏦 Secure Bank OCR"
+    inputs=gr.Image(type="pil", label="Upload Bank Form"),
+    outputs=gr.Textbox(label="Extracted Text", lines=20),
+    title="🏦 Global Bank OCR"
 )
 
 if __name__ == "__main__":
-    demo.launch()
+    demo.launch(max_threads=1)