Create app.py

app.py

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+import gradio as gr
+import cv2
+import numpy as np
+from PIL import Image
+import logging
+from ocr_engine import extract_weight_from_image
+from datetime import datetime
+import pytz
+import sys
+
+# Set up logging
+logging.basicConfig(level=logging.INFO, format='%(asctime)s - %(levelname)s - %(message)s', handlers=[logging.StreamHandler(sys.stdout)])
+
+def process_image(img):
+    try:
+        # Convert Gradio image (PIL) to process
+        if img is None:
+            return "No image provided", 0.0, "", None
+        
+        # Resize if > 5MB
+        img_bytes = img.tobytes()
+        size_mb = len(img_bytes) / (1024 * 1024)
+        if size_mb > 5:
+            scale = 0.9
+            while size_mb > 5:
+                w, h = img.size
+                img = img.resize((int(w * scale), int(h * scale)), Image.Resampling.LANCZOS)
+                img_bytes = img.tobytes()
+                size_mb = len(img_bytes) / (1024 * 1024)
+                scale *= 0.9
+            logging.info(f"Resized image to {size_mb:.2f} MB")
+
+        # Extract weight
+        weight, confidence, unit = extract_weight_from_image(img)
+        
+        # Return results
+        return f"{weight} {unit} (Confidence: {confidence:.2f}%)", f"Processed at {datetime.now(pytz.timezone('Asia/Kolkata')).strftime('%d-%m-%Y %I:%M:%S %p IST')}", img
+    except Exception as e:
+        logging.error(f"Error in process_image: {str(e)}")
+        return f"Error: {str(e)}", "", None
+
+# Gradio interface
+with gr.Blocks(title="Auto Weight Logger") as demo:
+    gr.Markdown("""
+    # 📷 Auto Weight Logger — OCR-Based Smart Scale Reader
+    This app detects weight from uploaded or captured images of digital balance displays. Optimized for 7-segment displays and various formats, it extracts numeric weights with high accuracy.
+    """)
+    
+    with gr.Row():
+        with gr.Column():
+            image_input = gr.Image(source="upload", tool="select", type="pil", label="Upload Weight Display Image")
+            webcam_input = gr.Image(source="webcam", type="pil", label="Or Capture with Webcam")
+            submit_btn = gr.Button("Detect Weight")
+        
+        with gr.Column():
+            output_text = gr.Textbox(label="Detected Weight", interactive=False)
+            timestamp_text = gr.Textbox(label="Processed At", interactive=False)
+            output_image = gr.Image(label="Processed Image")
+
+    submit_btn.click(
+        fn=process_image,
+        inputs=[image_input],
+        outputs=[output_text, timestamp_text, output_image]
+    )
+    
+    webcam_input.change(
+        fn=process_image,
+        inputs=[webcam_input],
+        outputs=[output_text, timestamp_text, output_image]
+    )
+
+demo.launch()