Automatic number plate recognition Project Added

Author: r6654kumar

Data Science Project/APNR/.idea/.gitignore

@@ -0,0 +1,15 @@
+# APNR
+Automatic number-plate recognition(Python Project)
+->A basic Python and Data Science project as a part of my college Data Science Club.
+->It detects number plates from the vehicle images provided to it.
+
+# Modules Used
+->OpenCV
+->matplotlib
+->numpy
+->imutils
+-> easyocr
+
+# Screenshot
+
+![](Screenshots/Output.png)

Data Science Project/APNR/.idea/APNR.iml

@@ -0,0 +1,40 @@
+import cv2
+from matplotlib import pyplot as plt
+import numpy as np
+import imutils
+import easyocr
+img = cv2.imread('NumberPlateImage/4.jpeg')
+gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
+plt.imshow(cv2.cvtColor(gray, cv2.COLOR_BGR2RGB))
+bfilter = cv2.bilateralFilter(gray, 11, 17, 17) #Noise reduction
+edged = cv2.Canny(bfilter, 30, 200) #Edge detection
+plt.imshow(cv2.cvtColor(edged, cv2.COLOR_BGR2RGB))
+keypoints = cv2.findContours(edged.copy(), cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)
+contours = imutils.grab_contours(keypoints)
+contours = sorted(contours, key=cv2.contourArea, reverse=True)[:10]
+location = None
+for contour in contours:
+    approx = cv2.approxPolyDP(contour, 10, True)
+    if len(approx) == 4:
+        location = approx
+        break
+mask = np.zeros(gray.shape, np.uint8)
+new_image = cv2.drawContours(mask, [location], 0,255, -1)
+new_image = cv2.bitwise_and(img, img, mask=mask)
+plt.imshow(cv2.cvtColor(new_image, cv2.COLOR_BGR2RGB))
+(x,y) = np.where(mask==255)
+(x1, y1) = (np.min(x), np.min(y))
+(x2, y2) = (np.max(x), np.max(y))
+cropped_image = gray[x1:x2+1, y1:y2+1]
+plt.imshow(cv2.cvtColor(cropped_image, cv2.COLOR_BGR2RGB))
+reader = easyocr.Reader(['en'])
+result = reader.readtext(cropped_image)
+result
+text = result[0][-2]
+font = cv2.FONT_HERSHEY_SIMPLEX
+res = cv2.putText(img, text=text, org=(approx[0][0][0], approx[1][0][1]+60), fontFace=font, fontScale=1, color=(0,255,0), thickness=2, lineType=cv2.LINE_AA)
+res = cv2.rectangle(img, tuple(approx[0][0]), tuple(approx[2][0]), (0,255,0),3)
+cv2.imshow("Detected",cv2.cvtColor(res, cv2.COLOR_BGR2RGB))
+cv2.waitKey(0)
+cv2.destroyAllWindows()
+print("Detected Number:",text)