Update app.py

app.py

@@ -75,7 +75,7 @@ def extract_weight(img):
     try:
         if img is None:
             logging.error("No image provided for OCR")
-            return "Not detected", 0.0
+            return "Not detected", 0.0, None
         
         # Convert PIL image to OpenCV format
         img_cv = cv2.cvtColor(np.array(img), cv2.COLOR_RGB2BGR)
@@ -99,30 +99,36 @@ def extract_weight(img):
                 if weight_float >= 0:  # Only accept valid weights
                     confidence = 95.0  # Assume high confidence if we have a valid weight
                     logging.info(f"Weight detected: {weight} (Confidence: {confidence:.2f}%)")
-                    return weight, confidence
+                    return weight, confidence, processed_img
             except ValueError:
                 logging.warning(f"Invalid number format: {weight}")
         
         logging.error("OCR failed to detect a valid weight")
-        return "Not detected", 0.0
+        return "Not detected", 0.0, None
     except Exception as e:
         logging.error(f"OCR processing failed: {str(e)}")
-        return "Not detected", 0.0
+        return "Not detected", 0.0, None
 
 def process_image(img):
     """Process uploaded or captured image and extract weight."""
     if img is None:
         logging.error("No image provided")
-        return "No image uploaded", None, None, None, gr.update(visible=False), gr.update(visible=False)
+        return "No image uploaded", None, gr.update(visible=False), gr.update(visible=False)
     
     ist_time = datetime.now(pytz.timezone("Asia/Kolkata")).strftime("%d-%m-%Y %I:%M:%S %p")
-    weight, confidence = extract_weight(img)
+    weight, confidence, processed_img = extract_weight(img)
     
     if weight == "Not detected" or confidence < 95.0:
         logging.warning(f"Weight detection failed: {weight} (Confidence: {confidence:.2f}%)")
-        return f"{weight} (Confidence: {confidence:.2f}%)", ist_time, None, gr.update(visible=True), gr.update(visible=False)
+        return f"{weight} (Confidence: {confidence:.2f}%)", ist_time, gr.update(visible=True), gr.update(visible=False)
     
-    return f"{weight} kg (Confidence: {confidence:.2f}%)", ist_time, None, gr.update(visible=True), gr.update(visible=True)
+    # Convert processed image back to PIL and encode as base64
+    pil_image = Image.fromarray(processed_img)
+    buffered = io.BytesIO()
+    pil_image.save(buffered, format="PNG")
+    img_base64 = base64.b64encode(buffered.getvalue()).decode()
+    
+    return f"{weight} kg (Confidence: {confidence:.2f}%)", ist_time, img_base64, gr.update(visible=True)
 
 # Gradio Interface
 with gr.Blocks(title="⚖️ Auto Weight Logger") as demo:
@@ -135,7 +141,7 @@ with gr.Blocks(title="⚖️ Auto Weight Logger") as demo:
 
     with gr.Row():
         timestamp = gr.Textbox(label="🕒 Captured At (IST)")
-        snapshot = gr.Image(label="📸 Snapshot Image")
+        snapshot = gr.Image(label="📸 Snapshot Image", type="auto")
 
     submit = gr.Button("🔍 Detect Weight")
     submit.click(