Update app.py

app.py

@@ -6,48 +6,48 @@ import re
 from paddleocr import PaddleOCR
 from datetime import datetime
 
-# Initialize OCR model once
+# Load OCR model
 ocr = PaddleOCR(use_angle_cls=True, lang='en')
 
-# Preprocessing: Convert to grayscale and threshold
 def preprocess_image(image):
     img = np.array(image.convert("RGB"))
     gray = cv2.cvtColor(img, cv2.COLOR_RGB2GRAY)
     _, thresh = cv2.threshold(gray, 150, 255, cv2.THRESH_BINARY)
     return Image.fromarray(thresh)
 
-# OCR detection + regex filtering
 def extract_weight_text(image):
-    results = ocr.ocr(np.array(image), cls=True)
-    for line in results[0]:
-        text = line[1][0]
-        match = re.search(r"\d+\.\d+", text)
-        if match:
-            return match.group()
-    return None
+    try:
+        results = ocr.ocr(np.array(image), cls=True)
+        texts = []
+        for line in results[0]:
+            text = line[1][0]
+            texts.append(text)
+            match = re.search(r"\d+\.\d+", text)
+            if match:
+                return match.group(), texts
+        return None, texts
+    except Exception as e:
+        return f"Error: {str(e)}", []
 
-# Main function
 def detect_weight(image):
     if image is None:
-        return "No image uploaded.", "", None
+        return "No image uploaded.", "", None, ""
     pre_img = preprocess_image(image)
-    weight = extract_weight_text(pre_img)
-    if weight:
-        return f"Detected Weight: {weight} kg", datetime.now().strftime("Captured At: %Y-%m-%d %H:%M:%S"), pre_img
+    weight, texts = extract_weight_text(pre_img)
+    if weight and "Error" not in weight:
+        return f"Detected Weight: {weight} kg", datetime.now().strftime("Captured At: %Y-%m-%d %H:%M:%S"), pre_img, "\n".join(texts)
     else:
-        return "Weight Not Detected", "", pre_img
+        return "Weight Not Detected", "", pre_img, "\n".join(texts)
 
-# Gradio UI
-interface = gr.Interface(
+gr.Interface(
     fn=detect_weight,
     inputs=gr.Image(type="pil", label="Upload or Capture Image"),
     outputs=[
         gr.Textbox(label="Weight"),
         gr.Textbox(label="Timestamp"),
-        gr.Image(label="Preprocessed Image")
+        gr.Image(label="Preprocessed Image"),
+        gr.Textbox(label="Detected Text (Debug)")
     ],
-    title="Auto Weight Logger",
-    description="Upload or click image of digital scale. It will detect and show the weight (kg).",
-)
-
-interface.launch()
+    title="Auto Weight Logger (Debug Mode)",
+    description="Upload a clear image of a digital scale. This version shows detected text for debugging."
+).launch()