main.py

import numpy as np
import cv2
from copy import deepcopy
from PIL import Image
import pytesseract as tess

def preprocess(img):
	cv2.imshow("Input",img)
	imgBlurred = cv2.GaussianBlur(img, (5,5), 0)
	gray = cv2.cvtColor(imgBlurred, cv2.COLOR_BGR2GRAY)

	sobelx = cv2.Sobel(gray,cv2.CV_8U,1,0,ksize=3)
	#cv2.imshow("Sobel",sobelx)
	#cv2.waitKey(0)
	ret2,threshold_img = cv2.threshold(sobelx,0,255,cv2.THRESH_BINARY+cv2.THRESH_OTSU)
	#cv2.imshow("Threshold",threshold_img)
	#cv2.waitKey(0)
	return threshold_img

def cleanPlate(plate):
	print ("CLEANING PLATE. . .")
	gray = cv2.cvtColor(plate, cv2.COLOR_BGR2GRAY)
	#kernel = cv2.getStructuringElement(cv2.MORPH_CROSS, (3, 3))
	#thresh= cv2.dilate(gray, kernel, iterations=1)

	_, thresh = cv2.threshold(gray, 150, 255, cv2.THRESH_BINARY)
	im1,contours,hierarchy = cv2.findContours(thresh.copy(),cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_NONE)

	if contours:
		areas = [cv2.contourArea(c) for c in contours]
		max_index = np.argmax(areas)

		max_cnt = contours[max_index]
		max_cntArea = areas[max_index]
		x,y,w,h = cv2.boundingRect(max_cnt)

		if not ratioCheck(max_cntArea,w,h):
			return plate,None

		cleaned_final = thresh[y:y+h, x:x+w]
		#cv2.imshow("Function Test",cleaned_final)
		return cleaned_final,[x,y,w,h]

	else:
		return plate,None


def extract_contours(threshold_img):
	element = cv2.getStructuringElement(shape=cv2.MORPH_RECT, ksize=(17, 3))
	morph_img_threshold = threshold_img.copy()
	cv2.morphologyEx(src=threshold_img, op=cv2.MORPH_CLOSE, kernel=element, dst=morph_img_threshold)
	cv2.imshow("Morphed",morph_img_threshold)
	cv2.waitKey(0)

	im2,contours, hierarchy= cv2.findContours(morph_img_threshold,mode=cv2.RETR_EXTERNAL,method=cv2.CHAIN_APPROX_NONE)
	return contours


def ratioCheck(area, width, height):
	ratio = float(width) / float(height)
	if ratio < 1:
		ratio = 1 / ratio

	aspect = 4.7272
	min = 15*aspect*15  # minimum area
	max = 125*aspect*125  # maximum area

	rmin = 3
	rmax = 6

	if (area < min or area > max) or (ratio < rmin or ratio > rmax):
		return False
	return True

def isMaxWhite(plate):
	avg = np.mean(plate)
	if(avg>=115):
		return True
	else:
 		return False

def validateRotationAndRatio(rect):
	(x, y), (width, height), rect_angle = rect

	if(width>height):
		angle = -rect_angle
	else:
		angle = 90 + rect_angle

	if angle>15:
	 	return False

	if height == 0 or width == 0:
		return False

	area = height*width
	if not ratioCheck(area,width,height):
		return False
	else:
		return True



def cleanAndRead(img,contours):
	#count=0
	for i,cnt in enumerate(contours):
		min_rect = cv2.minAreaRect(cnt)

		if validateRotationAndRatio(min_rect):

			x,y,w,h = cv2.boundingRect(cnt)
			plate_img = img[y:y+h,x:x+w]


			if(isMaxWhite(plate_img)):
				#count+=1
				clean_plate, rect = cleanPlate(plate_img)

				if rect:
					x1,y1,w1,h1 = rect
					x,y,w,h = x+x1,y+y1,w1,h1
					cv2.imshow("Cleaned Plate",clean_plate)
					cv2.waitKey(0)
					plate_im = Image.fromarray(clean_plate)
					text = tess.image_to_string(plate_im, lang='eng')
					print ("Detected Text : ",text)	
					img = cv2.rectangle(img,(x,y),(x+w,y+h),(0,255,0),2)
					cv2.imshow("Detected Plate",img)
					cv2.waitKey(0)

	#print "No. of final cont : " , count



if __name__ == '__main__':
	print ("DETECTING PLATE . . .")

	#img = cv2.imread("testData/Final.JPG")
	img = cv2.imread("testData/test4.jpg")

	threshold_img = preprocess(img)
	contours= extract_contours(threshold_img)

	#if len(contours)!=0:
		#print len(contours) #Test
		# cv2.drawContours(img, contours, -1, (0,255,0), 1)
		# cv2.imshow("Contours",img)
		# cv2.waitKey(0)


	cleanAndRead(img,contours)