scbc_repos/ssat_sdk/picture/DoubleImage.py

# encoding: utf-8
'''
用于两张图片比对检测
'''
import cv2 as cv
import numpy as np
import random
# from matplotlib import pyplot as plt

GRAY_LEVEL = 255

class DoubleImage():
    def __init__(self):
        pass

    #裁剪图片
    def cutImage(self, img_addr):
        img = cv.imread(img_addr)
        img_arr = np.array(img)
        hight = img_arr.shape[0]
        wight = img_arr.shape[1]
        dest_img = img_arr[hight-280:hight-180,wight-280:wight-180]
        return dest_img


    '''
    比较两张图片，如果根据threshold设定的容错值，有1%的点超过范围，则图片不一致。
    :param picPath1:第一个参数为为标准图地址，
    :param picPath2:第二个参数为测试图地址
    :param threshold: RGB颜色偏差容错范围
    '''
    def cmpPicTotal(self, picPath1, picPath2, threshold=20, expDotRate=0.01):
        srcImg1 = cv.imread(picPath1)
        srcImg2 = cv.imread(picPath2)
        return self.cmpImgTotal(srcImg1, srcImg2, threshold, expDotRate)

    '''
    比较两张图片，如果根据threshold设定的容错值，有1%的点超过范围，则图片不一致。
    :param picPath1:第一个参数为为标准图对象，
    :param picPath2:第二个参数为测试图对象
    :param threshold: RGB颜色偏差容错范围
    '''
    def cmpImgTotal(self, srcImg1, srcImg2, threshold=20, expDotRate=0.01):
        shape = srcImg2.shape
        dstImg = srcImg1 - srcImg2
        cv.imwrite("D:/dstImg.png", dstImg)
        bArr = dstImg[:,:,0].ravel()
        gArr = dstImg[:,:,1].ravel()
        rArr = dstImg[:,:,2].ravel()
        dotSum = shape[0]*shape[1]+0.0
        bCount = np.where((bArr>threshold)&(bArr<=255))[0].__len__()
        gCount = np.where((gArr>threshold)&(gArr<=255))[0].__len__()
        rCount = np.where((rArr>threshold)&(rArr<=255))[0].__len__()
        print "cmpImgTotal BGR点异常个数比例：", bCount/dotSum,gCount/dotSum,rCount/dotSum
        if bCount/dotSum>expDotRate or gCount/dotSum > expDotRate or rCount/dotSum>expDotRate:
            return False
        else:
            return True

    '''
    缺少衡量等级数字量化
    '''
    def cmpORB(self, im1, im2):
        orb = cv.ORB_create()
        kp = orb.detect(im1, None)
        kp, des1 = orb.compute(im1,kp)
        print "des1:",des1.__len__()
        # draw only keypoints location,not size and orientation
        # img1 = cv.drawKeypoints(im1, kp, None, color=(0, 255, 0), flags=0)
        # plt.imshow(img1), plt.show()

        orb = cv.ORB_create()
        kp2 = orb.detect(im2, None)
        kp2, des2 = orb.compute(im2, kp2)
        print "des2:",des2.__len__()
        # draw only keypoints location,not size and orientation
        # img2 = cv.drawKeypoints(im2, kp, None, color=(0, 255, 0), flags=0)
        # plt.imshow(img2), plt.show()

if __name__ == '__main__':

    dImg = DoubleImage()
    # dImg.cmpPicTotal('flower.jpg', 'flower.jpg')
    im1 = cv.imread('std.jpg')

    im2 = cv.imread('test.jpg')
    # psnr = dImg.psnr(im1, im2)
    # print "im1,im2 psnr:", psnr
    # dImg.cmpHist(im1 , im2)
    dImg.cmpORB(im1,im2)