Update app.py

app.py

@@ -9,12 +9,8 @@ from io import BytesIO
 # Initialize detector
 detector = WeightDetector()
 
-def process_input(image_source: str, image_upload=None, image_url: str = "") -> tuple:
-    """
-    Process image from different sources (upload, webcam, or URL)
-    Returns:
-        tuple: (detected_weight, detection_metadata, annotated_image)
-    """
+def process_input(image_source: str, image_upload=None, image_url: str = "") -> dict:
+    """Process image and return results with IST"""
     temp_img_path = None
     
     try:
@@ -25,7 +21,12 @@ def process_input(image_source: str, image_upload=None, image_url: str = "") ->
             response = requests.get(image_url)
             img = Image.open(BytesIO(response.content))
         else:
-            return None, "No valid image provided", None
+            return {
+                "weight": None,
+                "message": "No valid image provided",
+                "image": None,
+                "time": detector.get_current_ist()
+            }
             
         # Save to temp file for processing
         with tempfile.NamedTemporaryFile(suffix=".jpg", delete=False) as f:
@@ -33,29 +34,52 @@ def process_input(image_source: str, image_upload=None, image_url: str = "") ->
             img.save(f.name)
             
         # Detect weight
-        weight, metadata, annotated_img = detector.detect_weight(temp_img_path)
+        weight, time, annotated_img = detector.detect_weight(temp_img_path)
         
         # Format result message
         if weight is not None:
-            message = f"✅ Detected weight: {weight}g"
-            if len(metadata) > 1:
-                message += f" (from {len(metadata)} possible values)"
+            message = f"✅ Detected weight: {weight:.2f}g at {time}"
         else:
-            message = "❌ No weight value detected"
+            message = f"❌ No weight value detected at {time}"
             
-        return weight, message, annotated_img
+        return {
+            "weight": weight,
+            "message": message,
+            "image": annotated_img,
+            "time": time
+        }
         
     except Exception as e:
-        return None, f"Error: {str(e)}", None
+        return {
+            "weight": None,
+            "message": f"Error: {str(e)}",
+            "image": None,
+            "time": detector.get_current_ist()
+        }
     finally:
         if temp_img_path and os.path.exists(temp_img_path):
             os.unlink(temp_img_path)
 
+# Custom CSS for better mobile display
+css = """
+#mobile-view {
+    display: none;
+}
+@media screen and (max-width: 768px) {
+    #desktop-view {
+        display: none;
+    }
+    #mobile-view {
+        display: block;
+    }
+}
+"""
+
 # Gradio interface
-with gr.Blocks(title="Auto Weight Logger") as demo:
+with gr.Blocks(title="Auto Weight Logger", css=css) as demo:
     gr.Markdown("""
-    # Auto Weight Logger
-    Capture or upload an image of a weight measurement to automatically detect and log the value.
+    # 🏋️ Auto Weight Logger
+    Capture or upload an image of a digital scale to automatically detect the weight value.
     """)
     
     with gr.Row():
@@ -63,38 +87,55 @@ with gr.Blocks(title="Auto Weight Logger") as demo:
             image_source = gr.Radio(
                 ["upload", "url"],
                 label="Image Source",
-                value="upload"
+                value="upload",
+                elem_id="source-select"
             )
             
             image_upload = gr.Image(
-                sources=["upload"],
+                sources=["upload", "webcam"],
                 type="pil",
-                label="Upload Image"
+                label="Upload Image or Use Webcam",
+                elem_id="image-upload"
             )
             
             image_url = gr.Textbox(
                 label="Image URL",
-                visible=False
+                visible=False,
+                elem_id="image-url"
             )
             
-            submit_btn = gr.Button("Detect Weight")
+            submit_btn = gr.Button("Detect Weight", variant="primary")
             
         with gr.Column():
             weight_value = gr.Number(
-                label="Detected Weight (g)",
-                interactive=False
+                label="Detected Weight (grams)",
+                interactive=False,
+                elem_id="weight-value"
+            )
+            
+            detection_time = gr.Textbox(
+                label="Detection Time (IST)",
+                interactive=False,
+                elem_id="detection-time"
             )
             
             result_message = gr.Textbox(
-                label="Detection Result",
-                interactive=False
+                label="Result",
+                interactive=False,
+                elem_id="result-message"
             )
             
             annotated_image = gr.Image(
                 label="Annotated Image",
-                interactive=False
+                interactive=False,
+                elem_id="annotated-image"
             )
     
+    # Mobile view toggle
+    with gr.Column(visible=False, elem_id="mobile-view"):
+        gr.Markdown("### Mobile Instructions")
+        gr.Markdown("1. Tap 'Webcam' to capture\n2. Tap 'Detect Weight'")
+    
     # Show/hide URL input based on selection
     def toggle_url_visibility(source):
         return gr.Textbox(visible=source == "url")
@@ -109,7 +150,12 @@ with gr.Blocks(title="Auto Weight Logger") as demo:
     submit_btn.click(
         process_input,
         inputs=[image_source, image_upload, image_url],
-        outputs=[weight_value, result_message, annotated_image]
+        outputs={
+            "weight": weight_value,
+            "message": result_message,
+            "image": annotated_image,
+            "time": detection_time
+        }
     )
 
 # For Hugging Face Spaces