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Update app.py
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app.py
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import gradio as gr
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from ocr_engine import extract_weight_from_image
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from utils import get_ist_time
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def process_image(
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return "No image provided", "-", None, "-"
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weight, confidence = extract_weight_from_image(image)
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timestamp = get_ist_time()
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fn=process_image,
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inputs=gr.Image(type="pil", label="Upload or Capture
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outputs=[
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gr.
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gr.
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gr.Image(label="Snapshot Image"),
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gr.Textbox(label="Salesforce Log URL"),
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],
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title="⚖️ Auto Weight Logger",
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description="Upload or capture a
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)
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if __name__ == "__main__":
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import gradio as gr
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from PIL import Image
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from datetime import datetime
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import pytz
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from ocr_engine import extract_weight_from_image
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def process_image(img):
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# Convert image to RGB in case it's RGBA or grayscale
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img = img.convert("RGB")
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# Get IST timestamp
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ist = datetime.now(pytz.timezone("Asia/Kolkata")).strftime("%Y-%m-%d %H:%M:%S")
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# Run OCR
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weight, confidence = extract_weight_from_image(img)
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# Format output
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result = f"📅 Captured At (IST): {ist}\n"
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if confidence > 0:
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result += f"⚖️ Detected Weight: **{weight}**\n"
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result += f"✅ Confidence: `{confidence:.2f}`"
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else:
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result += "❌ No weight detected. Try a clearer image."
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return img, result
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# Gradio UI
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demo = gr.Interface(
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fn=process_image,
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inputs=gr.Image(type="pil", label="Upload or Capture Image"),
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outputs=[
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gr.Image(type="pil", label="Snapshot"),
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gr.Markdown(label="Weight Result")
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],
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title="⚖️ Auto Weight Logger (PaddleOCR)",
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description="Upload or capture an image of a weighing scale. This app uses PaddleOCR to detect the weight value.",
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allow_flagging="never"
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)
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if __name__ == "__main__":
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demo.launch()
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