10172100262
/
duplicate_image_detection_system


								from __future__ import print_function

								import cv2

								import numpy as np

								import os

								from flask import render_template

								import zipfile


								MAX_MATCHES = 500

								GOOD_MATCH_PERCENT = 0.15


								class feat:

								    def call_feature_extraction_1(self, folder_path, list, index, tmp):

								        # 按相似度排序

								        list = sorted(list, key=(lambda x: [x[2], x[5]]),reverse=True)

								        print(list)

								        print('---------------')

								        print(index)


								        for i in range(int(index/10)):

								            # 取第一组比较并返回

								            refFilename = list[i][0]

								            # imgname1 = '/home/Jupyterlab/wrl/pic/xiagao/pic/11.jpeg'

								            print("Reading reference image : ", refFilename)

								            imReference = cv2.imread(refFilename, cv2.IMREAD_COLOR)


								            imFilename = list[i][1]

								            # imgname2 = '/home/Jupyterlab/wrl/pic/xiagao/pic/12.jpeg'

								            print("Reading image to align : ", imFilename);

								            im = cv2.imread(imFilename, cv2.IMREAD_COLOR)


								            print(refFilename)

								            print(imFilename)

								            print(folder_path[7:])

								            p1 = refFilename.rfind('/')

								            name1 = refFilename[p1:-4]

								            print(name1)

								            p2 = imFilename.rfind('/')

								            name2 = imFilename[p2 + 1:]

								            print(name2)


								            # Write aligned image to disk.

								            outFilename = "output/" + folder_path[7:]

								            pre = os.getcwd()

								            print("Saving aligned image : ", outFilename)


								            print("Aligning images ...")

								            # Registered image will be resotred in imReg.

								            # The estimated homography will be stored in h.

								            imReg, h, img5 = feat().alignImages(im, imReference)

								            if (str(img5) == 'white'):

								                print('white')

								                # continue

								            else:

								                print(outFilename)

								                # imgwrite需要建好路径！！！！！！

								                if not os.path.exists(outFilename):

								                    os.makedirs(outFilename)

								                outFilename1 = outFilename + name1 + name2

								                cv2.imwrite(outFilename1, img5)

								                # continue


								        outFullName = feat.zipDir(outFilename)

								        pre1 = "/home/wwwroot/default/" + outFilename + ".zip"

								        # return str(pre) + '/' + outFilename

								        # return pre1

								        return outFullName


								    def alignImages(self, im1, im2):

								        # Convert images to grayscale

								        im1Gray = cv2.cvtColor(im1, cv2.COLOR_BGR2GRAY)

								        im2Gray = cv2.cvtColor(im2, cv2.COLOR_BGR2GRAY)


								        # Detect ORB features and compute descriptors.

								        orb = cv2.ORB_create(MAX_MATCHES)

								        keypoints1, descriptors1 = orb.detectAndCompute(im1Gray, None)

								        keypoints2, descriptors2 = orb.detectAndCompute(im2Gray, None)


								        if keypoints1  and keypoints2:

								            # Match features.

								            matcher = cv2.DescriptorMatcher_create(cv2.DESCRIPTOR_MATCHER_BRUTEFORCE_HAMMING)

								            matches = matcher.match(descriptors1, descriptors2, None)


								            # Sort matches by score

								            matches.sort(key=lambda x: x.distance, reverse=False)


								            # Remove not so good matches

								            numGoodMatches = int(len(matches) * GOOD_MATCH_PERCENT)

								            matches = matches[:numGoodMatches]


								            # Draw top matches

								            imMatches = cv2.drawMatches(im1, keypoints1, im2, keypoints2, matches, None)

								            cv2.imwrite("matches.jpg", imMatches)


								            # Extract location of good matches

								            points1 = np.zeros((len(matches), 2), dtype=np.float32)

								            points2 = np.zeros((len(matches), 2), dtype=np.float32)


								            for i, match in enumerate(matches):

								                points1[i, :] = keypoints1[match.queryIdx].pt

								                points2[i, :] = keypoints2[match.trainIdx].pt


								            if (points1.size == 0) or (points2.size == 0):

								                return 'white', 'white', 'white'


								            # Find homography

								            h, mask = cv2.findHomography(points1, points2, cv2.RANSAC)


								            # Use homography

								            height, width, channels = im2.shape

								            im1Reg = cv2.warpPerspective(im1, h, (width, height))

								            img1 = cv2.drawKeypoints(im1, keypoints1, im1, color=(255, 0, 255))

								            img2 = cv2.drawKeypoints(im2, keypoints2, im2, color=(255, 0, 255))

								            img5 = cv2.drawMatches(img1, keypoints1, img2, keypoints2, matches, None, flags=2)


								            return im1Reg, h, img5


								        else:

								            return 'white', 'white', 'white'


								    def return_img_stream(self, img_local_path):

								        # """

								        # 工具函数:

								        # 获取本地图片流

								        # :param img_local_path:文件单张图片的本地绝对路径

								        # :return: 图片流

								        # """

								        import base64

								        img_stream = ''

								        with open(img_local_path, 'r') as img_f:

								            img_stream = img_f.read()

								            img_stream = base64.b64encode(img_stream)

								        return img_local_path


								    def zipDir(dirpath):

								        """

								        压缩指定文件夹

								        :param dirpath: 目标文件夹路径

								        :param outFullName: 压缩文件保存路径+xxxx.zip

								        :return: 无

								        """

								        outFullName = "/home/wwwroot/default/" + dirpath[21:] + ".zip"

								        outFullName1 = "http://106.75.226.23/"  + dirpath[21:] + ".zip"

								        # if not os.path.exists(outFullName):

								        #     os.makedirs(outFullName)

								        zip = zipfile.ZipFile(outFullName, "w", zipfile.ZIP_DEFLATED)

								        for path, dirnames, filenames in os.walk(dirpath):

								            # 去掉目标跟路径，只对目标文件夹下边的文件及文件夹进行压缩

								            fpath = path.replace(dirpath, '')


								            for filename in filenames:

								                zip.write(os.path.join(path, filename), os.path.join(fpath, filename))

								        zip.close()

								        return outFullName1


								# im1 = '/Users/wrl/Desktop/test0506/pic/2303.png'

								# im2 = '/Users/wrl/Desktop/test0506/pic/2304.png'

								# img1 = cv2.imread(im1, cv2.IMREAD_COLOR)

								# img2 = cv2.imread(im2, cv2.IMREAD_COLOR)

								# imReg, h, img5 =feat().alignImages(img1,img2)