annotate the parking images

annotation.py

# -*- coding: UTF-8 -*-
import cv2
import numpy as np
import os
import random


def car_position(input_file):
	position = []
	img_gray = cv2.imread(input_file,cv2.IMREAD_GRAYSCALE)
	#图片的预处理
	ret,thresh = cv2.threshold(img_gray,254,255,cv2.THRESH_BINARY) #对图片进行二值化处理
	kernel = np.array(cv2.getStructuringElement(cv2.MORPH_RECT, (3, 3), (-1, -1))) #内核是3x3的全1矩阵，(-1,-1)锚位于中心
	img_open = cv2.morphologyEx(thresh, cv2.MORPH_OPEN, kernel) #先膨胀后腐蚀，开运算
	#img_close = cv2.morphologyEx(thresh1, cv2.MORPH_CLOSE, kernel)
	ret1,thresh1 = cv2.threshold(img_open,254,255,cv2.THRESH_BINARY_INV) #再次对图片进行二值化反转处理，为了不把整张图片框住
	contours, hierarchy = cv2.findContours(thresh1, cv2.RETR_CCOMP ,cv2.CHAIN_APPROX_NONE)

	for i in range(len(contours)):
		if len(contours[i]) > 30:
			x, y, w, h = cv2.boundingRect(contours[i])
			#cv2.rectangle(img, (x, y), (x+w, y+h), (0, 255, 0), 2)
			#print (x, y),(x+w, y+h)
			position.append([x, y, x+w, y+h])
	return position

def readFolderImages(input_dir, file_name):
	doc = open(input_dir+ file_name +"/position.txt",'w')
	print(input_dir+ file_name +"/position.txt")
	for root, dirs, files in os.walk(input_dir+ file_name + "/images2", topdown=True):
		for name in files:
			print root, name
			doc.write(os.path.join(root,name).replace("0001","").replace("images2","images"))
			input_file = os.path.join(root,name)
			position = car_position(input_file)	
			doc.write(" "+ str(len(position))  )
			for i in range(len(position)):
				
				for j in range(len(position[i])):
					position_point = position[i][j]
					doc.write(" "+ str(position_point))
			doc.write(" \n")
	doc.close()

if __name__=="__main__":

	folders = [
               "20","25","35","45","55","60","65","75","85","(30,30)",
               "(30,45)","(30,60)","(45,30)","(45,45)","(45,60)","(60,30)",
               "(60,45)","(60,60)",
               "parking_line_3","parking_line_30","parking_line_40","parking_line_50","parking_line_60",
				"25_change_22", "(30,75)1","25_change11","30_75","88888","60_30_3","60_30_2","60_30_1"
              ]
	input_dir = os.path.dirname(os.path.abspath(__file__))+"/JPEGImages/"
	for folder in folders:
		print(folder)
		readFolderImages(input_dir ,folder)

	annotation_file = os.path.dirname(os.path.abspath(__file__))+"/Annotations/annotation.txt"
	training_file = os.path.dirname(os.path.abspath(__file__))+"/ImageSets/train.txt"
	testing_file = os.path.dirname(os.path.abspath(__file__))+"/ImageSets/test.txt"
	annotation_doc = open(annotation_file,'w')
	training_doc = open(training_file,'w')
	testing_doc = open(testing_file,'w')
	for folder in folders:
		with open(input_dir+ folder +"/position.txt",'r') as f:
			for line in f.readlines():
				
				path = line.split(" ")[0]
				if(random.random() < 0.9):
					training_doc.write(path+"\n")
					annotation_doc.write(line)
				else:
					testing_doc.write(path+"\n")				

	annotation_doc.close()
	training_doc.close()
	testing_doc.close()



#img_output = np.ones(img_gray.shape,dtype = np.uint8)*255
#cv2.drawContours(img,contours,-1,(0,0,255),3) 

'''
cv2.imshow('img_open',thresh)
cv2.waitKey(0)  
cv2.destroyAllWindows()
'''