How to compare the differences between images in python

How to compare images in python: first use [pylab.imread] to read the image; then use [matplotlib.pylab - plt.imshow] to display the image; then convert the grayscale image to the RGB image; and finally save it Pictures are enough.

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How to compare images in python:

1. Read pictures

pylab.imread and PIL.Image.open read both RBG order,

and cv2.imread reads in BGR order, special attention should be paid when mixed use

1 matplotlib.pylab

import pylab as plt
import numpy as np
img = plt.imread('examples.png')
print(type(img), img.dtype, np.min(img), np.max(img))
[out]
(<type &#39;numpy.ndarray&#39;>, dtype(&#39;float32&#39;), 0.0, 1.0)    # matplotlib读取进来的图片是float，0-1

2 PIL.image. open

from PIL import Image
import numpy as np
img = Image.open('examples.png')
print(type(img), np.min(img), np.max(img))
img = np.array(img)     # 将PIL格式图片转为numpy格式
print(type(img), img.dtype, np.min(img), np.max(img))
[out]
(<class &#39;PIL.PngImagePlugin.PngImageFile&#39;>, 0, 255)    # 注意，PIL是有自己的数据结构的，但是可以转换成numpy数组
(<type &#39;numpy.ndarray&#39;>, dtype(&#39;uint8&#39;), 0, 255)    # 和用matplotlib读取不同，PIL和matlab相同，读进来图片和其存储在硬盘的样子是一样的，uint8，0-255

3 cv2.imread

import cv2
import numpy as np
img = cv2.imread('examples.png')    # 默认是读入为彩色图，即使原图是灰度图也会复制成三个相同的通道变成彩色图
img_gray = cv2.imread('examples.png', 0)    # 第二个参数为0的时候读入为灰度图，即使原图是彩色图也会转成灰度图
print(type(img), img.dtype, np.min(img), np.max(img))
print(img.shape)
print(img_gray.shape)
[out]
(<type &#39;numpy.ndarray&#39;>, dtype(&#39;uint8&#39;), 0, 255)    # opencv读进来的是numpy数组，类型是uint8，0-255
(824, 987, 3)    # 彩色图3通道
(824, 987)    # 灰度图单通道

import cv2
import pylab as plt
from PIL import Image
import numpy as np
img_plt = plt.imread('examples.png')
img_pil = Image.open('examples.png')
img_cv = cv2.imread('examples.png')
print(img_plt[125, 555, :])
print(np.array(img_pil)[125, 555, :] / 255.0)
print(img_cv[125, 555, :] / 255.0)
[out]
[ 0.61176473  0.3764706   0.29019609]
[ 0.61176471  0.37647059  0.29019608]
[ 0.29019608  0.37647059  0.61176471]    # opencv的是BGR顺序

2. Display pictures

1, matplotlib.pylab - plt.imshow , this function actually displays an RGB image in numpy array format

import pylab as plt
import numpy as np
img = plt.imread('examples.png')
plt.imshow(img) 
plt.show()

import pylab as plt
from PIL import Image
import numpy as np
img = Image.open('examples.png')
img_gray = img.convert('L')    #转换成灰度图像
img = np.array(img)
img_gray = np.array(img_gray)
plt.imshow(img)    # or plt.imshow(img / 255.0)，matplotlib和matlab一样，如果是float类型的图像，范围是0-1才能正常imshow，如果是uint8图像，范围则需要是0-255
plt.show()
plt.imshow(img_gray, cmap=plt.gray())    # 显示灰度图要设置cmap参数
plt.show()
plt.imshow(Image.open('examples.png'))    # 实际上plt.imshow可以直接显示PIL格式图像
plt.show()

import pylab as plt
import cv2
import numpy as np
img = cv2.imread('examples.png')
plt.imshow(img[..., -1::-1])    # 因为opencv读取进来的是bgr顺序呢的，而imshow需要的是rgb顺序，因此需要先反过来
plt.show()

2 cv2 display image

import cv2
image2=cv2.imread(r"test/aaa/0002/0002_0_1.jpg")
cv2.imshow("1",image2)
cv2.waitKey(0)

3. Grayscale image-RGB image conversion

1 PIL.Image

from PIL import Image
img = Image.open('examples.png')
img_gray = img.convert('L')    # RGB转换成灰度图像
img_rgb = img_gray.convert('RGB') # 灰度转RGB
print(img)
print(img_gray)
print(img_rgb)
[out]
<PIL.PngImagePlugin.PngImageFile image mode=RGB size=987x824 at 0x7FC2CCAE04D0>
<PIL.Image.Image image mode=L size=987x824 at 0x7FC2CCAE0990>
<PIL.Image.Image image mode=RGB size=987x824 at 0x7FC2CCAE0250>

2 cv2 (note that opencv can convert color channels through parameters when reading images, the following is implemented in other ways)

import cv2
import pylab as plt
img = cv2.imread('examples.png')
img_gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)    # BGR转灰度
img_bgr = cv2.cvtColor(img_gray, cv2.COLOR_GRAY2BGR)    # 灰度转BRG
img_rgb = cv2.cvtColor(img_gray, cv2.COLOR_GRAY2RGB)    # 也可以灰度转RGB

4. Save pictures

1 PIL.image - Save pictures in PIL format

from PIL import Image
img = Image.open('examples.png')
img.save('examples2.png')
img_gray = img.convert('L')
img_gray.save('examples_gray.png')    # 不管是灰度还是彩色，直接用save函数保存就可以，但注意，只有PIL格式的图片能够用save函数

2 cv2.imwrite - Save pictures in numpy format

import cv2
img = cv2.imread('examples.png')    # 这是BGR图片
cv2.imwrite('examples2.png', img)    # 这里也应该用BGR图片保存，这里要非常注意，因为用pylab或PIL读入的图片都是RGB的，如果要用opencv存图片就必须做一个转换
img_gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
cv2.imwrite('examples_gray.png', img_gray)

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