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How to save grayscale image in Pytorch?


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0















I want to save grayscale image in Pytorch, each image has four gray values, 0, 60, 120 and 180. I try the following way to save images, but the saved image is not I expected.



for i, (inputs) in enumerate(test_generator):
pred = modelPl(inputs.float()).detach()
fig,ax = plt.subplots(1,1,figsize = (5,5))
ax.imshow(pred[0,:,:], cmap = "gray")
print(pred.shape)
torchvision.utils.save_image(pred, saveTestPath + 'img_0.png'.format(i))


Output:
torch.Size([400, 400])



Expected image:



enter image description here



However, the saved picture is not correct as follows:



enter image description here










share|improve this question
































    0















    I want to save grayscale image in Pytorch, each image has four gray values, 0, 60, 120 and 180. I try the following way to save images, but the saved image is not I expected.



    for i, (inputs) in enumerate(test_generator):
    pred = modelPl(inputs.float()).detach()
    fig,ax = plt.subplots(1,1,figsize = (5,5))
    ax.imshow(pred[0,:,:], cmap = "gray")
    print(pred.shape)
    torchvision.utils.save_image(pred, saveTestPath + 'img_0.png'.format(i))


    Output:
    torch.Size([400, 400])



    Expected image:



    enter image description here



    However, the saved picture is not correct as follows:



    enter image description here










    share|improve this question




























      0












      0








      0








      I want to save grayscale image in Pytorch, each image has four gray values, 0, 60, 120 and 180. I try the following way to save images, but the saved image is not I expected.



      for i, (inputs) in enumerate(test_generator):
      pred = modelPl(inputs.float()).detach()
      fig,ax = plt.subplots(1,1,figsize = (5,5))
      ax.imshow(pred[0,:,:], cmap = "gray")
      print(pred.shape)
      torchvision.utils.save_image(pred, saveTestPath + 'img_0.png'.format(i))


      Output:
      torch.Size([400, 400])



      Expected image:



      enter image description here



      However, the saved picture is not correct as follows:



      enter image description here










      share|improve this question
















      I want to save grayscale image in Pytorch, each image has four gray values, 0, 60, 120 and 180. I try the following way to save images, but the saved image is not I expected.



      for i, (inputs) in enumerate(test_generator):
      pred = modelPl(inputs.float()).detach()
      fig,ax = plt.subplots(1,1,figsize = (5,5))
      ax.imshow(pred[0,:,:], cmap = "gray")
      print(pred.shape)
      torchvision.utils.save_image(pred, saveTestPath + 'img_0.png'.format(i))


      Output:
      torch.Size([400, 400])



      Expected image:



      enter image description here



      However, the saved picture is not correct as follows:



      enter image description here







      python image computer-vision pytorch






      share|improve this question















      share|improve this question













      share|improve this question




      share|improve this question








      edited Mar 27 at 1:31







      rosefun

















      asked Mar 27 at 1:26









      rosefunrosefun

      4752 silver badges13 bronze badges




      4752 silver badges13 bronze badges

























          1 Answer
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          It might be that torchvision.utils.save_image requires values to be in range 0 to 1. Your images have values which are greater than 1 and hence the problem.



          You can check this by dividing the tensor by 255 (or some appropriate number). You can also try to set normalize=True and see if it can automatically normalize the data for you.






          share|improve this answer




















          • 1





            Thanks, I solve the problem by dividing the tensor by 255.

            – rosefun
            Mar 27 at 1:41










          Your Answer






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          1 Answer
          1






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          active

          oldest

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          active

          oldest

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          2














          It might be that torchvision.utils.save_image requires values to be in range 0 to 1. Your images have values which are greater than 1 and hence the problem.



          You can check this by dividing the tensor by 255 (or some appropriate number). You can also try to set normalize=True and see if it can automatically normalize the data for you.






          share|improve this answer




















          • 1





            Thanks, I solve the problem by dividing the tensor by 255.

            – rosefun
            Mar 27 at 1:41















          2














          It might be that torchvision.utils.save_image requires values to be in range 0 to 1. Your images have values which are greater than 1 and hence the problem.



          You can check this by dividing the tensor by 255 (or some appropriate number). You can also try to set normalize=True and see if it can automatically normalize the data for you.






          share|improve this answer




















          • 1





            Thanks, I solve the problem by dividing the tensor by 255.

            – rosefun
            Mar 27 at 1:41













          2












          2








          2







          It might be that torchvision.utils.save_image requires values to be in range 0 to 1. Your images have values which are greater than 1 and hence the problem.



          You can check this by dividing the tensor by 255 (or some appropriate number). You can also try to set normalize=True and see if it can automatically normalize the data for you.






          share|improve this answer













          It might be that torchvision.utils.save_image requires values to be in range 0 to 1. Your images have values which are greater than 1 and hence the problem.



          You can check this by dividing the tensor by 255 (or some appropriate number). You can also try to set normalize=True and see if it can automatically normalize the data for you.







          share|improve this answer












          share|improve this answer



          share|improve this answer










          answered Mar 27 at 1:37









          Umang GuptaUmang Gupta

          4,4721 gold badge21 silver badges42 bronze badges




          4,4721 gold badge21 silver badges42 bronze badges










          • 1





            Thanks, I solve the problem by dividing the tensor by 255.

            – rosefun
            Mar 27 at 1:41












          • 1





            Thanks, I solve the problem by dividing the tensor by 255.

            – rosefun
            Mar 27 at 1:41







          1




          1





          Thanks, I solve the problem by dividing the tensor by 255.

          – rosefun
          Mar 27 at 1:41





          Thanks, I solve the problem by dividing the tensor by 255.

          – rosefun
          Mar 27 at 1:41






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