python - image.show 中的图像未显示任何内容（Python 3 笔记本）

Question

我的输出没有显示任何内容，老实说我不知道​​为什么

这是完整的代码，但我认为问题是当我将参数传递给aRed, aGreen, aBlue, originalImage = openImage(response.content) 当我在 collab python notebook 中运行该代码时，我的图像由于某种原因没有显示出来！也许这是我在上面的行中将 URL 作为参数传递的方式？

import numpy
from PIL import Image
import requests
from io import BytesIO

# FUNCTION DEFINTIONS:

# open the image and return 3 matrices, each corresponding to one channel (R, G and B channels)
def openImage(imagePath):
    imOrig = Image.open(BytesIO(imagePath))
    im = numpy.array(imOrig)

    aRed = im[:, :, 0]
    aGreen = im[:, :, 1]
    aBlue = im[:, :, 2]

    return [aRed, aGreen, aBlue, imOrig]

# compress the matrix of a single channel
def compressSingleChannel(channelDataMatrix, singularValuesLimit):
    uChannel, sChannel, vhChannel = numpy.linalg.svd(channelDataMatrix)
    aChannelCompressed = numpy.zeros((channelDataMatrix.shape[0], channelDataMatrix.shape[1]))
    k = singularValuesLimit

    leftSide = numpy.matmul(uChannel[:, 0:k], numpy.diag(sChannel)[0:k, 0:k])
    aChannelCompressedInner = numpy.matmul(leftSide, vhChannel[0:k, :])
    aChannelCompressed = aChannelCompressedInner.astype('uint8')
    return aChannelCompressed


# MAIN PROGRAM:
response = requests.get('https://i.imgur.com/BIOFZNo.png')
print ('*** Image Compression using SVD - a demo')
aRed, aGreen, aBlue, originalImage = openImage(response.content)
# image width and height:
imageWidth = 1000
imageHeight = 1000

#number of singular values to use for reconstructing the compressed image
singularValuesLimit = 160

aRedCompressed = compressSingleChannel(aRed, singularValuesLimit)
aGreenCompressed = compressSingleChannel(aGreen, singularValuesLimit)
aBlueCompressed = compressSingleChannel(aBlue, singularValuesLimit)

imr=Image.fromarray(aRedCompressed,mode=None)
img=Image.fromarray(aGreenCompressed,mode=None)
imb=Image.fromarray(aBlueCompressed,mode=None)

newImage = Image.merge("RGB", (imr,img,imb))

originalImage.show()
newImage.show()

编译程序没有错误，只是没有显示任何内容。谢谢你们！这是我的文件的链接：https ://colab.research.google.com/drive/12K0nWKRdOpZ3gSfTn0wuP8Y0_UUeUxEE

标签： pythonimagenumpyurlpython-imaging-library

Answer 1

您无需.show()在交互模式下指定。只需删除该部分，它就会正常工作。

import numpy
from PIL import Image
import requests
from io import BytesIO

# FUNCTION DEFINTIONS:

# open the image and return 3 matrices, each corresponding to one channel (R, G and B channels)
def openImage(imagePath):
    imOrig = Image.open(BytesIO(imagePath))
    im = numpy.array(imOrig)

    aRed = im[:, :, 0]
    aGreen = im[:, :, 1]
    aBlue = im[:, :, 2]

    return [aRed, aGreen, aBlue, imOrig]

# compress the matrix of a single channel
def compressSingleChannel(channelDataMatrix, singularValuesLimit):
    uChannel, sChannel, vhChannel = numpy.linalg.svd(channelDataMatrix)
    aChannelCompressed = numpy.zeros((channelDataMatrix.shape[0], channelDataMatrix.shape[1]))
    k = singularValuesLimit

    leftSide = numpy.matmul(uChannel[:, 0:k], numpy.diag(sChannel)[0:k, 0:k])
    aChannelCompressedInner = numpy.matmul(leftSide, vhChannel[0:k, :])
    aChannelCompressed = aChannelCompressedInner.astype('uint8')
    return aChannelCompressed


# MAIN PROGRAM:
response = requests.get('https://i.imgur.com/BIOFZNo.png')
print ('*** Image Compression using SVD - a demo')
aRed, aGreen, aBlue, originalImage = openImage(response.content)
# image width and height:
imageWidth = 1000
imageHeight = 1000

#number of singular values to use for reconstructing the compressed image
singularValuesLimit = 160

aRedCompressed = compressSingleChannel(aRed, singularValuesLimit)
aGreenCompressed = compressSingleChannel(aGreen, singularValuesLimit)
aBlueCompressed = compressSingleChannel(aBlue, singularValuesLimit)

imr=Image.fromarray(aRedCompressed,mode=None)
img=Image.fromarray(aGreenCompressed,mode=None)
imb=Image.fromarray(aBlueCompressed,mode=None)

newImage = Image.merge("RGB", (imr,img,imb))

originalImage

将显示原始图像。对于新图像，在下一个代码单元中：

newImage