Update app.py

app.py

@@ -1,6 +1,6 @@
 import numpy as np
 import cv2
-import  imutils
+import imutils
 import pytesseract
 import pandas as pd
 import time
@@ -8,9 +8,10 @@ import os.path
 
 from PIL import Image
 import streamlit as st
-bytes_data=None
 
-img_file_buffer=st.camera_input("Take a picture")
+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)
@@ -18,75 +19,49 @@ if img_file_buffer is not None:
 
     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)
 
+    cnts = sorted(cnts, key=cv2.contourArea, reverse=True)[:30]
+    screenCnt = None
+    image2 = image.copy()
+    cv2.drawContours(image2, cnts, -1, (0, 0, 255), 3)
 
-    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]
-            
+            x, y, w, h = cv2.boundingRect(c)
+            new_img = image[y:y + h, x:x + w]
             break
- 
+
     cv2.drawContours(image, [screenCnt], -1, (0, 255, 0), 3)
-    # cv2.imshow("image with detected license plate", image)
- 
-    Cropped_loc = 'assets/1.png'
-    cv2.imshow("cropped", cv2.imread(Cropped_loc))
- 
 
+    # Display the cropped image
+    st.image(new_img, caption="Cropped License Plate")
 
     # Configuration for tesseract
-    pytesseract.pytesseract.tesseract_cmd=r"tessract1\tesseract.exe"
+    pytesseract.pytesseract.tesseract_cmd = r"tesseract1\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'])
+    # 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'])
     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.
-     """
-
+    header = not os.path.exists(file_path)
 
+    df.to_csv('data.csv', mode='a', header=header, index=False)
 
     # Print recognized text
     st.write(text)
+
 if bytes_data is None:
-    st.stop()
+    st.stop()