app.py

import numpy as np
import cv2
import imutils
import pytesseract
import pandas as pd
import time
import os

from PIL import Image
import streamlit as st

#
# Create a directory for storing data
if not os.path.exists("data"):
    os.makedirs("data")



bytes_data = None

img_file_buffer = st.camera_input("Take a picture")
if img_file_buffer is not None:
    test_image = Image.open(img_file_buffer)
    st.image(test_image, use_column_width=True)
    image = np.asarray(test_image)

    image = imutils.resize(image, width=500)

    gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
    gray = cv2.bilateralFilter(gray, 11, 17, 17)
    edged = cv2.Canny(gray, 170, 200)

    cnts, new = cv2.findContours(edged.copy(), cv2.RETR_LIST, cv2.CHAIN_APPROX_SIMPLE)
    image1 = image.copy()
    cv2.drawContours(image1, cnts, -1, (0, 255, 0), 3)

    cnts = sorted(cnts, key=cv2.contourArea, reverse=True)[:30]
    screenCnt = None
    image2 = image.copy()
    cv2.drawContours(image2, cnts, -1, (0, 0, 255), 3)

    for c in cnts:
        perimeter = cv2.arcLength(c, True)
        approx = cv2.approxPolyDP(c, 0.018 * perimeter, True)
        if len(approx) == 4:
            screenCnt = approx
            x, y, w, h = cv2.boundingRect(c)
            new_img = image[y:y + h, x:x + w]
            break

    image_with_contours = image.copy()
    cv2.drawContours(image_with_contours, [screenCnt], -1, (0, 255, 0), 3)

    # Display the image with contours
    st.image(image_with_contours, caption="Image with detected license plate")

    # Configuration for tesseract
    # tesseract_path = r"D:\number_plate\tessract\tesseract.exe"
    # pytesseract.pytesseract.tesseract_cmd = tesseract_path
    
    # Run tesseract OCR on the cropped image
    text = pytesseract.image_to_string(new_img, lang="eng")

    # Data is stored in CSV file
    raw_data = {'date': [time.asctime(time.localtime(time.time()))], 'v_number': [text]}
    df = pd.DataFrame(raw_data, columns=['date', 'v_number'])

   # Check if the CSV file exists
    file_path = os.path.join("data", "data.csv")
    if os.path.exists(file_path):
        df.to_csv(file_path, mode='a', header=False, index=False)  # Append to existing file
    else:
        df.to_csv(file_path, index=False)  # Create new file
    
    # Print some debug information
    st.write("CSV File Path:", file_path)
    st.write("CSV File Exists:", os.path.exists(file_path))

    # Print recognized text
    st.write("Recognized Text:",text)

if bytes_data is None:
    st.stop()