Update app.py

app.py

@@ -1,119 +1,37 @@
 import gradio as gr
-from weight_detector import WeightDetector
-import tempfile
-import os
+from PIL import Image
+from datetime import datetime
+from ocr_engine import extract_weight
 
-detector = WeightDetector()
+def process_image(image):
+    if image is None:
+        return "No image received", None, None
 
-def process_input(image_source: str, image_upload=None, image_url: str = "") -> dict:
-    """Process webcam/image and return weight + IST time"""
-    temp_img_path = None
-    try:
-        # Handle webcam/image upload
-        if image_source == "webcam" and image_upload is not None:
-            img = image_upload
-        elif image_source == "upload" and image_upload is not None:
-            img = image_upload
-        elif image_source == "url" and image_url:
-            import requests
-            from io import BytesIO
-            response = requests.get(image_url)
-            img = Image.open(BytesIO(response.content))
-        else:
-            return {
-                "weight": None,
-                "message": "⚠️ No image provided!",
-                "image": None,
-                "time": detector.get_current_ist()
-            }
-        
-        # Save to temp file
-        with tempfile.NamedTemporaryFile(suffix=".jpg", delete=False) as f:
-            temp_img_path = f.name
-            img.save(f.name)
-        
-        # Detect weight
-        return detector.detect_weight(temp_img_path)
-    
-    except Exception as e:
-        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.remove(temp_img_path)
+    weight = extract_weight(image)
+    now = datetime.now().strftime("%Y-%m-%d %H:%M:%S")
+    return f"{weight} grams", now, image
+
+with gr.Blocks() as demo:
+    gr.Markdown("## 📷 Auto Weight Logger — OCR-Based Smart Scale Reader")
+    gr.Markdown("Upload a snapshot of a digital weight display or use webcam. The app extracts weight using OCR.")
 
-# Gradio UI
-with gr.Blocks(title="Auto Weight Logger") as demo:
-    gr.Markdown("""
-    # **⚖️ Auto Weight Logger (7-Segment OCR)**
-    **Capture weight from digital balances using a webcam or image upload.**
-    - ✅ Optimized for **7-segment displays** (e.g., lab balances)
-    - 📅 Logs **IST time** automatically
-    - 🚫 Detects **blurry/glare** images
-    """)
-    
     with gr.Row():
-        with gr.Column():
-            image_source = gr.Radio(
-                ["webcam", "upload", "url"],
-                label="Input Source",
-                value="webcam"
-            )
-            
-            image_upload = gr.Image(
-                sources=["webcam", "upload"],
-                type="pil",
-                label="Capture/Upload Image",
-                interactive=True
-            )
-            
-            image_url = gr.Textbox(
-                label="Image URL (if selected)",
-                visible=False
-            )
-            
-            submit_btn = gr.Button("Detect Weight", variant="primary")
-        
-        with gr.Column():
-            weight_value = gr.Number(
-                label="Detected Weight (g)",
-                interactive=False
-            )
-            
-            detection_time = gr.Textbox(
-                label="Detection Time (IST)",
-                interactive=False
-            )
-            
-            result_message = gr.Textbox(
-                label="Result",
-                interactive=False
-            )
-            
-            annotated_image = gr.Image(
-                label="Annotated Image",
-                interactive=False
-            )
-    
-    # Show/hide URL input
-    def toggle_url_visibility(source):
-        return gr.Textbox(visible=source == "url")
-    
-    image_source.change(
-        toggle_url_visibility,
-        inputs=image_source,
-        outputs=image_url
-    )
-    
-    # Process input
-    submit_btn.click(
-        process_input,
-        inputs=[image_source, image_upload, image_url],
-        outputs=[weight_value, detection_time, result_message, annotated_image]
-    )
+        webcam = gr.Image(source="webcam", type="pil", label="📸 Capture from Webcam")
+        upload = gr.Image(source="upload", type="pil", label="📁 Or Upload Image")
+
+    image_input = gr.State()
+
+    def choose_image(w, u):
+        return w if w else u
+
+    webcam.change(fn=choose_image, inputs=[webcam, upload], outputs=image_input)
+    upload.change(fn=choose_image, inputs=[webcam, upload], outputs=image_input)
+
+    submit_btn = gr.Button("🚀 Detect Weight")
+    weight_out = gr.Textbox(label="Detected Weight")
+    time_out = gr.Textbox(label="Captured At (IST)")
+    snapshot_out = gr.Image(label="Snapshot")
+
+    submit_btn.click(fn=process_image, inputs=image_input, outputs=[weight_out, time_out, snapshot_out])
 
-demo.launch()
+demo.launch()