Create app.py

app.py

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+import numpy as np
+import cv2
+import  imutils
+import pytesseract
+import pandas as pd
+import time
+import os.path
+
+image = cv2.imread('vehicle.jpg')
+
+image = imutils.resize(image, width=500)
+
+cv2.imshow("Original Image", image)
+
+gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
+#cv2.imshow("1 - Grayed image", gray)
+
+gray = cv2.bilateralFilter(gray, 11, 17, 17)
+#cv2.imshow("2 - Smoothened image", gray)
+
+edged = cv2.Canny(gray, 170, 200)
+# cv2.imshow("3 - Edged image", edged)
+
+
+
+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)
+# cv2.imshow("countours",image1)
+
+cnts=sorted(cnts,key=cv2.contourArea,reverse=True)[:30]
+screenCnt=None
+image2=image.copy()
+cv2.drawContours(image2,cnts,-1,(0,0,255),3)
+# cv2.imshow("Top 30 contours",image2)
+
+i=1
+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]
+                cv2.imwrite('./'+str(i)+'.png',new_img)
+                i+=1
+                break
+
+cv2.drawContours(image, [screenCnt], -1, (0, 255, 0), 3)
+# cv2.imshow("image with detected license plate", image)
+
+Cropped_loc = './1.png'
+cv2.imshow("cropped", cv2.imread(Cropped_loc))
+
+
+
+# Configuration for tesseract
+pytesseract.pytesseract.tesseract_cmd=r"D:\number plate\tessract\tesseract.exe"
+
+# Run tesseract OCR on image
+text = pytesseract.image_to_string(Cropped_loc,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'])
+
+file_path = 'data.csv'
+header = not os.path.exists(file_path)  # Check if the file exists and set header flag accordingly
+
+
+df.to_csv('data.csv',mode='a',header=header,index=False)
+"""the mode='a' parameter ensures that each new entry is appended to the existing CSV
+ file instead of replacing it. The header=False parameter prevents the column headers 
+ from being written repeatedly when appending entries. The index=False parameter 
+ excludes the index column from being written to the CSV file."""
+
+
+
+# Print recognized text
+print(text)
+cv2.waitKey(0)