Update app.py

app.py

@@ -12,77 +12,73 @@ 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)
+    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)
+    image = imutils.resize(image, width=500)
 
-     cv2.imshow("Original Image", image)
+    cv2.imshow("Original Image", image)
 
-     gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
+    gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
     #cv2.imshow("1 - Grayed image", gray)
 
-     gray = cv2.bilateralFilter(gray, 11, 17, 17)
+    gray = cv2.bilateralFilter(gray, 11, 17, 17)
     #cv2.imshow("2 - Smoothened image", gray)
 
-     edged = cv2.Canny(gray, 170, 200)
+    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,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
+    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
  
-                     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)
  
-     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))
+    Cropped_loc = './1.png'
+    cv2.imshow("cropped", cv2.imread(Cropped_loc))
  
 
 
-     # Configuration for tesseract
-     pytesseract.pytesseract.tesseract_cmd=r"tessract1\tesseract.exe"
+    # Configuration for tesseract
+    pytesseract.pytesseract.tesseract_cmd=r"tessract1\tesseract.exe"
 
-     # Run tesseract OCR on image
-     text = pytesseract.image_to_string(Cropped_loc,lang="eng")
+    # 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] }
+    #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'])
+    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
+    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. 
+    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. 
 
@@ -91,7 +87,7 @@ if img_file_buffer is not None:
 
 
 
-     # Print recognized text
-     st.write(text)
-# if bytes_data is None:
-#        st.stop()
+    # Print recognized text
+    st.write(text)
+if bytes_data is None:
+    st.stop()