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Create app.py
Browse files
app.py
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import streamlit as st
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import cv2
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import pytesseract
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from PIL import Image
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import numpy as np
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st.title("Candy Label Scanner")
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# Function to capture video from the camera
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def capture_video():
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cap = cv2.VideoCapture(0)
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stframe = st.empty()
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while cap.isOpened():
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ret, frame = cap.read()
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if not ret:
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break
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# Display the video frame
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stframe.image(frame, channels="BGR")
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# Capture the frame when the button is pressed
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if st.button("Capture", key="capture_button"):
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cap.release()
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return frame
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# Function to analyze the captured image for nutritional values
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def analyze_image(image):
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# Convert the image to grayscale
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gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
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# Use Tesseract to do OCR on the image
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text = pytesseract.image_to_string(gray, lang='kor')
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# Display the extracted text
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st.subheader("Extracted Text")
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st.text(text)
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# Extract the sugar content using a regex pattern
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import re
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pattern = re.compile(r"당류\s*:\s*(\d+(\.\d+)?)\s*g")
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match = pattern.search(text)
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if match:
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sugar_content = float(match.group(1))
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st.subheader("Sugar Content")
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st.write(f"Sugar content: {sugar_content}g")
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# Determine the potential harm based on the sugar content
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if sugar_content > 20:
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st.markdown('<p style="color:red;">Dangerous</p>', unsafe_allow_html=True)
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elif sugar_content > 10:
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st.markdown('<p style="color:yellow;">Normal</p>', unsafe_allow_html=True)
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else:
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st.markdown('<p style="color:green;">Good</p>', unsafe_allow_html=True)
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else:
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st.write("Sugar content not found")
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# Main application logic
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if __name__ == "__main__":
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st.write("Click 'Start Camera' to scan a candy label")
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if st.button("Start Camera"):
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frame = capture_video()
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if frame is not None:
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analyze_image(frame)
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