1.图片保存在指定目录

在opencv中用于保存图片所用到的语句是cv2.imwrite(filepath，image)
filepath是用于保存的地址路径(可用绝对和相对路径)，此路径必须真实存在。如果不存在，则可以通过os模块创建，也就是说在后面一排加上os.makedirs(os.path.dirname(filename), exist_ok=True)，这里的filename指的是filepath指向的文件。

1.1实际实例

import cv2
import os
import numpy as np

class TestLoader:
    # imdb image_path(list)
    def __init__(self, imdb, batch_size=1, shuffle=False):
        self.imdb = imdb
        self.batch_size = batch_size
        self.shuffle = shuffle
        self.size = len(imdb)  # num of data
        # self.index = np.arange(self.size)

        self.cur = 0
        self.data = None
        self.label = None

        self.reset()
        self.get_batch()

    def reset(self):
        self.cur = 0
        if self.shuffle:
            # shuffle test image
            np.random.shuffle(self.imdb)

    def iter_next(self):
        return self.cur + self.batch_size <= self.size

    # realize __iter__() and next()--->iterator
    # return iter object
    def __iter__(self):
        return self

    def __next__(self):
        return self.next()

    def next(self):
        if self.iter_next():
            self.get_batch()
            self.cur += self.batch_size
            return self.data
        else:
            raise StopIteration

    def getindex(self):
        return self.cur / self.batch_size

    def getpad(self):
        if self.cur + self.batch_size > self.size:
            return self.cur + self.batch_size - self.size
        else:
            return 0

    def get_batch(self):
        imdb = self.imdb[self.cur]
        '''
        cur_from = self.cur
        cur_to = min(cur_from + self.batch_size, self.size)
        #picked image
        imdb = [self.imdb[self.index[i]] for i in range(cur_from, cur_to)]
        # print(imdb)
        '''
        # print type(imdb)
        # print len(imdb)
        # assert len(imdb) == 1, "Single batch only"
        im = cv2.imread(imdb)
        self.data = im

path = "F:/Dataset/MTCNN_DATA/test/" # 保存测试图片的地方
gt_imdb=[]
for item in os.listdir(path):
    gt_imdb.append(os.path.join(path,item))
test_data = TestLoader(gt_imdb)

count = 0
for imagepath in gt_imdb:
    print(imagepath)
    image = cv2.imread(imagepath)
    save_path = 'D:/pycharm/test/'   # 图片保存的路径
    count += 1
    cv2.imwrite(save_path+'%d.jpg'%(count),image)
    # os.path.dirname(path)
    # 语法：os.path.dirname(path)
    # 功能：去掉文件名，返回目录
    os.makedirs(os.path.dirname(save_path),exist_ok=True)

运行结果:

2.文件夹里所有图片以数组形式输出

2.1实际代码

import os
import cv2
import numpy as np
def read_pic(path):
    if os.path.exists(path):
        print(1)
    else:
        print(2)
    dirnames = sorted(os.listdir(path))
    # print(dirname)
    n = len(dirnames)
    print(n)
    # f = open('neg.txt', 'w')
    Srcimg= []
    for dirname in dirnames:
        # print("正在读取第%d张图片" % i)
        # fromfile()函数读回数据时需要用户指定元素类型，并对数组的形状进行适当的修改,indecode下中文路径也可以运行
        img = cv2.imdecode(np.fromfile(path + dirname, dtype=np.uint8), -1)
        #####保存图片#########

        cv2.imwrite(output_path + "/" + dirname, img)
        img_path = os.path.join(input_path, dirname)
        # f.write(img_path+'\n')
        Srcimg.append(img)
        # cv2.imshow('pic',img)
        # cv2.waitKey(0)
        # print(img_path)
    Srcimg = np.array(Srcimg)

    return Srcimg
if __name__ == '__main__':
    input_path='D:/pycharm/10kinds-light-face-detector-align-recognition-master/test/'
    output_path='D:/pycharm/compare_three_module/result/'
    Srcimg=read_pic(input_path)
    print(Srcimg)

运行结果：