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如何仅使用 Python PIL 检查 jpeg 图像是彩色还是灰度? (不使用 OpenCV)

[英]How to check whether a jpeg image is color or grayscale using only Python PIL? (not using OpenCV)

I found this method really helpful and it's actually working quite accurately.我发现这个方法真的很有帮助,而且它实际上工作得非常准确。 BUT this uses OpenCV.. and I want to use the same method using PIL.但是这使用 OpenCV .. 我想使用 PIL 使用相同的方法。

code using PIL instead of OpenCV:使用 PIL 而不是 OpenCV 的代码:

from PIL import Image
import numpy as np

###test image
img=Image.open('')
img=img.load()

### splitting b,g,r channels
r,g,b=img.split()

### getting differences between (b,g), (r,g), (b,r) channel pixels
r_g=np.count_nonzero(abs(r-g))
r_b=np.count_nonzero(abs(r-b))
g_b=np.count_nonzero(abs(g-b))

### sum of differences
diff_sum=float(r_g+r_b+g_b)

### finding ratio of diff_sum with respect to size of image
ratio=diff_sum/img.size

if ratio>0.005:
    print("image is color")
else:
    print("image is greyscale")

I changed cv2.imread('') to Image.open('') and added img=img.load() .我将cv2.imread('')更改为Image.open('')并添加了img=img.load() and I changed b,g,r=cv2.split(img) to r,g,b=img.split()我把b,g,r=cv2.split(img)改为r,g,b=img.split()

I know that split() method exists in PIL.我知道 PIL 中存在split()方法。 but I'm having this error.但我有这个错误。

AttributeError: 'PixelAccess' object has no attribute 'split'

How can I solve this?我该如何解决这个问题? Thank you in advance!!先感谢您!!

You are mixing data types like you are mixing Red Bull and Vodka .您正在混合data types就像混合 Red Bull 和 Vodka 一样 The load method is producing the error because it converts the PIL image into a PixelAccess object, an you need a PIL image for split() . load方法产生错误,因为它将PIL图像转换为PixelAccess对象,您需要一个用于split()PIL图像。 Also, count_nonzero() does not work because it operates on NumPy arrays, and you are attempting to call that method on a PIL image.此外, count_nonzero()不起作用,因为它在NumPy数组上运行,而您正试图在PIL图像上调用该方法。 Lastly, size returns a tuple ( width and height ) of the image, so you need to modify your code accordingly:最后, size返回图像的元组widthheight ),因此您需要相应地修改代码:

from PIL import Image
import numpy as np

###test image
img=Image.open("D://opencvImages//lena512.png")

### splitting b,g,r channels
r,g,b=img.split()

### PIL to numpy conversion:
r = np.array(r)
g = np.array(g)
b = np.array(b)

### getting differences between (b,g), (r,g), (b,r) channel pixels
r_g=np.count_nonzero(abs(r-g))
r_b=np.count_nonzero(abs(r-b))
g_b=np.count_nonzero(abs(g-b))

### sum of differences
diff_sum=float(r_g+r_b+g_b)

### get image size:
width, height = img.size

### get total pixels on image:
totalPixels = width * height

### finding ratio of diff_sum with respect to size of image
ratio = diff_sum/totalPixels

print("Ratio is: "+ratio)

if ratio>0.005:
    print("image is color")
else:
    print("image is greyscale")

Let's check out the Lena image in color and grayscale:让我们以彩色和灰度查看Lena图像:

Color Lena returns this:颜色莉娜返回这个:

Ratio is: 2.981109619140625
image is color

And Grayscale Lena returns this:灰度莉娜返回这个:

Ratio is: 0.0
image is greyscale

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