Update app.py

app.py

@@ -1,34 +1,41 @@
 import gradio as gr
-from PIL import Image
+from PIL import Image, ImageEnhance, ImageOps
 import torch
 from transformers import TrOCRProcessor, VisionEncoderDecoderModel
 from datetime import datetime
 import pytz
+import re
 
-# Load the model and processor from Hugging Face
+# Load model and processor
 processor = TrOCRProcessor.from_pretrained("microsoft/trocr-base-stage1")
 model = VisionEncoderDecoderModel.from_pretrained("microsoft/trocr-base-stage1")
 
-# Function to detect weight text from image
+# Enhance image before OCR
+def enhance_image(image):
+    image = image.convert("L")  # grayscale
+    image = ImageOps.invert(image)  # invert colors
+    image = ImageEnhance.Contrast(image).enhance(2)  # boost contrast
+    image = ImageEnhance.Sharpness(image).enhance(2)  # sharpen
+    image = image.resize((image.width * 2, image.height * 2))  # enlarge
+    return image
+
+# Extract weight
 def detect_weight(image):
     try:
-        # Preprocess image
-        pixel_values = processor(images=image, return_tensors="pt").pixel_values
-        # Run model
+        processed_image = enhance_image(image)
+        pixel_values = processor(images=processed_image, return_tensors="pt").pixel_values
         generated_ids = model.generate(pixel_values)
         generated_text = processor.batch_decode(generated_ids, skip_special_tokens=True)[0]
 
-        # Try to extract weight-like number
-        import re
-        match = re.search(r"(\d{1,3}(\.\d{1,2})?)", generated_text)
+        # Extract number
+        match = re.search(r"(\d{1,4}(?:\.\d{1,2})?)", generated_text)
         weight = match.group(1) if match else "Not detected"
 
-        # Get IST time
+        # Timestamp
         ist = pytz.timezone('Asia/Kolkata')
         current_time = datetime.now(ist).strftime("%Y-%m-%d %H:%M:%S")
 
         return f"Weight: {weight} kg\nCaptured At: {current_time}", image
-
     except Exception as e:
         return f"Error: {str(e)}", image
 
@@ -38,7 +45,7 @@ interface = gr.Interface(
     inputs=gr.Image(type="pil", label="Upload or Capture Image"),
     outputs=[gr.Textbox(label="Weight Info"), gr.Image(label="Snapshot")],
     title="⚖️ Auto Weight Detector (No Tesseract)",
-    description="Detects weight from digital scale image using AI-based OCR (no Tesseract)."
+    description="Detects weight from digital scale image using Hugging Face TrOCR."
 )
 
 interface.launch()