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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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import cv2
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import numpy as np
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from paddleocr import PaddleOCR
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from datetime import datetime
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from pytz import timezone
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import re
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from PIL import Image
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#
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ocr = PaddleOCR(use_angle_cls=True, lang='en')
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def detect_weight(image):
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try:
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enhanced = cv2.equalizeHist(gray)
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rgb_image = cv2.cvtColor(enhanced, cv2.COLOR_GRAY2RGB)
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# OCR (without cls= argument for compatibility)
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result = ocr.ocr(rgb_image)
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best_match = None
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for line in result:
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for box in line:
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if best_match:
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now_ist = datetime.now(timezone('Asia/Kolkata')).strftime("%Y-%m-%d %H:%M:%S IST")
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except Exception as e:
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return f"Error: {str(e)}", "Error", None
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gr.
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gr.
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gr.
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import gradio as gr
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from paddleocr import PaddleOCR
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from PIL import Image
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import numpy as np
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import cv2
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import re
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from datetime import datetime
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from pytz import timezone
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ocr = PaddleOCR(use_angle_cls=False, lang='en') # cls removed
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def detect_weight(image):
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try:
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enhanced = cv2.equalizeHist(gray)
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rgb_image = cv2.cvtColor(enhanced, cv2.COLOR_GRAY2RGB)
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result = ocr.ocr(rgb_image)
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best_match = None
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for line in result:
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for box in line:
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if len(box) > 1 and isinstance(box[1], tuple):
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text, conf = box[1]
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match = re.search(r"\d+\.\d+", text)
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if match and conf > best_conf:
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best_match = match.group()
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best_conf = conf
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if best_match:
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now_ist = datetime.now(timezone('Asia/Kolkata')).strftime("%Y-%m-%d %H:%M:%S IST")
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except Exception as e:
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return f"Error: {str(e)}", "Error", None
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with gr.Blocks() as demo:
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gr.Markdown("## Auto Weight Logger\nUpload or capture a digital scale image. This app detects the weight automatically using AI.")
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with gr.Row():
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image_input = gr.Image(type="pil", label="Upload or Capture Weight Image", tool="editor", sources=["upload", "camera"])
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with gr.Column():
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output_text = gr.Textbox(label="Detected Weight")
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output_time = gr.Textbox(label="Captured At (IST)")
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snapshot_output = gr.Image(label="📷 Snapshot")
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image_input.change(fn=detect_weight, inputs=image_input, outputs=[output_text, output_time, snapshot_output])
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demo.launch()
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