Opencv学习笔记(一):如何将得到的图片保存在指定目录以及如何将文件夹里所有图片以数组形式输出

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：