Update app.py

app.py

@@ -6,30 +6,32 @@ from datetime import datetime
 import re
 from PIL import Image
 
-ocr = PaddleOCR(use_angle_cls=True, lang='en')  # Better for clean numbers
+# Initialize PaddleOCR (only once)
+ocr = PaddleOCR(use_angle_cls=True, lang='en')  # Use English OCR model
 
 def detect_weight(image):
     if image is None:
         return "No image uploaded", "N/A", None
 
-    # Convert to OpenCV format
+    # Convert PIL Image to OpenCV format (NumPy array)
+    image = image.convert("RGB")
     image_np = np.array(image)
 
-    # Preprocessing: Convert to grayscale, enhance contrast
+    # Preprocess: Grayscale + contrast enhancement (optional)
     gray = cv2.cvtColor(image_np, cv2.COLOR_RGB2GRAY)
-    gray = cv2.equalizeHist(gray)
-    gray = cv2.cvtColor(gray, cv2.COLOR_GRAY2RGB)  # Convert back to 3 channel for PaddleOCR
+    gray_eq = cv2.equalizeHist(gray)
+    processed_image = cv2.cvtColor(gray_eq, cv2.COLOR_GRAY2RGB)  # convert back to RGB for PaddleOCR
 
     # Run OCR
-    result = ocr.ocr(gray, cls=True)
+    result = ocr.ocr(processed_image, cls=True)
 
     best_match = None
     best_conf = 0
 
+    # Search for a decimal number like 25.52
     for line in result:
         for box in line:
-            text = box[1][0]
-            conf = box[1][1]
+            text, conf = box[1]
             match = re.search(r"\d+\.\d+", text)
             if match and conf > best_conf:
                 best_match = match.group()
@@ -37,10 +39,11 @@ def detect_weight(image):
 
     if best_match:
         now = datetime.now().strftime("%Y-%m-%d %H:%M:%S")
-        return f"Weight: {best_match} kg (Confidence: {round(best_conf*100, 2)}%)", now, image
+        return f"Weight: {best_match} kg (Confidence: {round(best_conf * 100, 2)}%)", now, image
     else:
         return "No weight detected kg (Confidence: 0.0%)", "N/A", image
 
+# Gradio UI
 gr.Interface(
     fn=detect_weight,
     inputs=gr.Image(type="pil", label="Upload or Capture Weight Image"),
@@ -50,5 +53,5 @@ gr.Interface(
         gr.Image(label="Snapshot")
     ],
     title="Auto Weight Logger",
-    description="Upload or capture a weight scale image. The app will detect and log the weight automatically."
+    description="Upload or capture a digital scale image. This app detects the weight automatically using AI."
 ).launch()