Update app.py

app.py

@@ -1,29 +1,44 @@
 import gradio as gr
+from PIL import Image
+import torch
+from transformers import TrOCRProcessor, VisionEncoderDecoderModel
 from datetime import datetime
 import pytz
-from ocr_engine import extract_weight_from_image
 
-def process_image(img):
-    if img is None:
-        return "No image uploaded", None, None
+# Load the model and processor from Hugging Face
+processor = TrOCRProcessor.from_pretrained("microsoft/trocr-base-stage1")
+model = VisionEncoderDecoderModel.from_pretrained("microsoft/trocr-base-stage1")
 
-    ist_time = datetime.now(pytz.timezone("Asia/Kolkata")).strftime("%d-%m-%Y %I:%M:%S %p")
-    weight, _ = extract_weight_from_image(img)
-    return weight, ist_time, img
+# Function to detect weight text from image
+def detect_weight(image):
+    try:
+        # Preprocess image
+        pixel_values = processor(images=image, return_tensors="pt").pixel_values
+        # Run model
+        generated_ids = model.generate(pixel_values)
+        generated_text = processor.batch_decode(generated_ids, skip_special_tokens=True)[0]
 
-with gr.Blocks(title="⚖️ Auto Weight Logger") as demo:
-    gr.Markdown("# ⚖️ Auto Weight Logger")
-    gr.Markdown("Upload or capture an image of a **digital scale display** to auto-detect the weight in kilograms.")
+        # Try to extract weight-like number
+        import re
+        match = re.search(r"(\d{1,3}(\.\d{1,2})?)", generated_text)
+        weight = match.group(1) if match else "Not detected"
 
-    with gr.Row():
-        image_input = gr.Image(type="pil", label="📷 Upload or Capture Image")
-        output_weight = gr.Textbox(label="⚖️ Detected Weight")
+        # Get IST time
+        ist = pytz.timezone('Asia/Kolkata')
+        current_time = datetime.now(ist).strftime("%Y-%m-%d %H:%M:%S")
 
-    with gr.Row():
-        timestamp = gr.Textbox(label="🕒 Captured At (IST)")
-        snapshot = gr.Image(label="📸 Snapshot Image")
+        return f"Weight: {weight} kg\nCaptured At: {current_time}", image
 
-    submit = gr.Button("🔍 Detect Weight")
-    submit.click(process_image, inputs=image_input, outputs=[output_weight, timestamp, snapshot])
+    except Exception as e:
+        return f"Error: {str(e)}", image
 
-demo.launch()
+# Gradio UI
+interface = gr.Interface(
+    fn=detect_weight,
+    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)."
+)
+
+interface.launch()