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我想对整个图像文件夹进行二值化并保存它们。我已经找到了将单个图像二值化并将其存储在同一文件夹中的代码：

import cv2
im_gray = cv2.imread('blurredimg1.png', cv2.IMREAD_GRAYSCALE)
(thresh, im_bw) = cv2.threshold(im_gray, 128, 255, cv2.THRESH_BINARY | cv2.THRESH_OTSU)
thresh = 127
im_bw = cv2.threshold(im_gray, thresh, 255, cv2.THRESH_BINARY)[1]
cv2.imwrite('bw_image.png', im_bw)

这是输出

图片

这是文件夹中的文件

现在，我想一次使用整个集合的阈值。我该怎么做？

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3 回答 3

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这里是 ：

from glob import glob import cv2 img_mask = r'C:\Users\Bsi\Desktop\PFE\Mine\*.png' img_names = glob(img_mask) for fn in img_names: print('processing %s...' % fn,) im_gray = cv2.imread(fn, 0) (thresh, im_bw) = cv2.threshold(im_gray, 128, 255, cv2.THRESH_BINARY | cv2.THRESH_OTSU) thresh = 127 im_bw = cv2.threshold(im_gray, thresh, 255, cv2.THRESH_BINARY)[1]

于 2020-03-24T21:25:48.403 回答
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以下内容在我的 Mac 上的 Python/OpenCV 中经过测试并适用于 Unix 路径语法。而且我不是 Windows 用户。因此，您需要为您的操作系统适当修改路径并将我的“/”更改为“\”，它们在路径中特别显示

您需要定义要放置输出目录的路径以保存创建的图像。我使用了 in_dir 和 out_dir。out_dir 目录需要已经存在。

所以像下面这样。我在循环外获得 OTSU 阈值并从模糊图像中保存阈值。然后我通过你的 img_mask 遍历输入目录中的所有图像。我使用保存的阈值对每个图像进行阈值处理，然后将文件写入循环内的磁盘。

from glob import glob
import os
import cv2

# read your one blurred image and convert to gray
im_gray = cv2.imread('test/lena.png', 0)

# threshold it with OTSU thresholding and get the threshold value
thresh, im_bw = cv2.threshold(im_gray, 0, 255, cv2.THRESH_BINARY_INV + cv2.THRESH_OTSU)
print(thresh)

# define the paths to your input images and to where you want to put the output images    
in_dir = 'test'
out_dir = 'test2'

# read the input image file names with paths into a list
infiles = in_dir + '/*.png'
img_names = glob(infiles)
print(img_names)

# loop over each input image in a for loop
for fn in img_names:
    print('processing %s...' % fn)

    # read an input image as gray
    im_gray = cv2.imread(fn, 0)

    # threshold it with your saved threshold
    im_bw = cv2.threshold(im_gray, thresh, 255, cv2.THRESH_BINARY)[1]

    # write the result to disk in the previously created output directory
    name = os.path.basename(fn)
    outfile = out_dir + '/' + name
    cv2.imwrite(outfile, im_bw)


于 2020-03-24T21:45:30.527 回答
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您可以使用两个 for 循环来执行此操作。我面临着同样的问题。

for i, val in enumerate(images_gray):
    ret,thresh1 = cv2.threshold(images_gray[i],110,255,cv2.THRESH_BINARY)
    ret,thresh2 = cv2.threshold(images_gray[i],70,255,cv2.THRESH_BINARY_INV)
    ret,thresh3 = cv2.threshold(images_gray[i],127,255,cv2.THRESH_TRUNC)
    ret,thresh4 = cv2.threshold(images_gray[i],77,255,cv2.THRESH_TOZERO)
    ret,thresh5 = cv2.threshold(images_gray[i],127,255,cv2.THRESH_TOZERO_INV)
    titles = ['Original Image','BINARY','BINARY_INV','TRUNC','TOZERO','TOZERO_INV']
    images = [images_gray[i], thresh1, thresh2, thresh3, thresh4, thresh5]
    for k in range(6):
        plt.rcParams["figure.figsize"] = (20,10)
        plt.subplot(45,6,k+1),plt.imshow(images_gray[i],'gray', vmin=0,vmax=255)
        plt.title(titles[k])
        k+=1
    plt.xticks([]),plt.yticks([])
    plt.show()
    i+=1

我使用了 45 张图片。并想展示一个 6 阈值比较。

于 2022-02-23T00:35:40.443 回答