Removing the alpha channel from all the jpg images in a folder












0















How can I remove the alpha channel from jpg images automatically?



I am using a deep learning code based on PyTorch that requires 3 channels but my images have 4 channels. I saw this answer but I do not know how to convert all the images in a folder to a counterpart image that does not have an alpha channel.



Here is the error I receive:



[jalal@goku example]$ python img_to_vec_nearest_neighbors.py 
/scratch/sjn-p3/anaconda/anaconda3/lib/python3.6/importlib/_bootstrap.py:219: RuntimeWarning: numpy.dtype size changed, may indicate binary incompatibility. Expected 96, got 88
return f(*args, **kwds)
/scratch/sjn-p3/anaconda/anaconda3/lib/python3.6/importlib/_bootstrap.py:219: RuntimeWarning: numpy.dtype size changed, may indicate binary incompatibility. Expected 96, got 88
return f(*args, **kwds)
/scratch/sjn-p3/anaconda/anaconda3/lib/python3.6/importlib/_bootstrap.py:219: RuntimeWarning: numpy.dtype size changed, may indicate binary incompatibility. Expected 96, got 88
return f(*args, **kwds)
/scratch/sjn-p3/anaconda/anaconda3/lib/python3.6/importlib/_bootstrap.py:219: RuntimeWarning: numpy.dtype size changed, may indicate binary incompatibility. Expected 96, got 88
return f(*args, **kwds)
/scratch/sjn-p3/anaconda/anaconda3/lib/python3.6/site-packages/torchvision-0.2.1-py3.6.egg/torchvision/transforms/transforms.py:188: UserWarning: The use of the transforms.Scale transform is deprecated, please use transforms.Resize instead.
Traceback (most recent call last):
File "img_to_vec_nearest_neighbors.py", line 18, in <module>
vec = img2vec.get_vec(img)
File "../img_to_vec.py", line 43, in get_vec
h_x = self.model(image)
File "/scratch/sjn-p3/anaconda/anaconda3/lib/python3.6/site-packages/torch/nn/modules/module.py", line 477, in __call__
result = self.forward(*input, **kwargs)
File "/scratch/sjn-p3/anaconda/anaconda3/lib/python3.6/site-packages/torchvision-0.2.1-py3.6.egg/torchvision/models/resnet.py", line 139, in forward
File "/scratch/sjn-p3/anaconda/anaconda3/lib/python3.6/site-packages/torch/nn/modules/module.py", line 477, in __call__
result = self.forward(*input, **kwargs)
File "/scratch/sjn-p3/anaconda/anaconda3/lib/python3.6/site-packages/torch/nn/modules/conv.py", line 301, in forward
self.padding, self.dilation, self.groups)
RuntimeError: Given groups=1, weight of size [64, 3, 7, 7], expected input[1, 4, 224, 224] to have 3 channels, but got 4 channels instead


For example, how can I perform the following command for all the images I have in one folder? My images have the extensions jpg, jpeg, and png, but I don't mind if they all become jpg.



convert cat.png -background white -alpha remove cat.jpg









share|improve this question





























    0















    How can I remove the alpha channel from jpg images automatically?



    I am using a deep learning code based on PyTorch that requires 3 channels but my images have 4 channels. I saw this answer but I do not know how to convert all the images in a folder to a counterpart image that does not have an alpha channel.



    Here is the error I receive:



    [jalal@goku example]$ python img_to_vec_nearest_neighbors.py 
    /scratch/sjn-p3/anaconda/anaconda3/lib/python3.6/importlib/_bootstrap.py:219: RuntimeWarning: numpy.dtype size changed, may indicate binary incompatibility. Expected 96, got 88
    return f(*args, **kwds)
    /scratch/sjn-p3/anaconda/anaconda3/lib/python3.6/importlib/_bootstrap.py:219: RuntimeWarning: numpy.dtype size changed, may indicate binary incompatibility. Expected 96, got 88
    return f(*args, **kwds)
    /scratch/sjn-p3/anaconda/anaconda3/lib/python3.6/importlib/_bootstrap.py:219: RuntimeWarning: numpy.dtype size changed, may indicate binary incompatibility. Expected 96, got 88
    return f(*args, **kwds)
    /scratch/sjn-p3/anaconda/anaconda3/lib/python3.6/importlib/_bootstrap.py:219: RuntimeWarning: numpy.dtype size changed, may indicate binary incompatibility. Expected 96, got 88
    return f(*args, **kwds)
    /scratch/sjn-p3/anaconda/anaconda3/lib/python3.6/site-packages/torchvision-0.2.1-py3.6.egg/torchvision/transforms/transforms.py:188: UserWarning: The use of the transforms.Scale transform is deprecated, please use transforms.Resize instead.
    Traceback (most recent call last):
    File "img_to_vec_nearest_neighbors.py", line 18, in <module>
    vec = img2vec.get_vec(img)
    File "../img_to_vec.py", line 43, in get_vec
    h_x = self.model(image)
    File "/scratch/sjn-p3/anaconda/anaconda3/lib/python3.6/site-packages/torch/nn/modules/module.py", line 477, in __call__
    result = self.forward(*input, **kwargs)
    File "/scratch/sjn-p3/anaconda/anaconda3/lib/python3.6/site-packages/torchvision-0.2.1-py3.6.egg/torchvision/models/resnet.py", line 139, in forward
    File "/scratch/sjn-p3/anaconda/anaconda3/lib/python3.6/site-packages/torch/nn/modules/module.py", line 477, in __call__
    result = self.forward(*input, **kwargs)
    File "/scratch/sjn-p3/anaconda/anaconda3/lib/python3.6/site-packages/torch/nn/modules/conv.py", line 301, in forward
    self.padding, self.dilation, self.groups)
    RuntimeError: Given groups=1, weight of size [64, 3, 7, 7], expected input[1, 4, 224, 224] to have 3 channels, but got 4 channels instead


    For example, how can I perform the following command for all the images I have in one folder? My images have the extensions jpg, jpeg, and png, but I don't mind if they all become jpg.



    convert cat.png -background white -alpha remove cat.jpg









    share|improve this question



























      0












      0








      0








      How can I remove the alpha channel from jpg images automatically?



      I am using a deep learning code based on PyTorch that requires 3 channels but my images have 4 channels. I saw this answer but I do not know how to convert all the images in a folder to a counterpart image that does not have an alpha channel.



      Here is the error I receive:



      [jalal@goku example]$ python img_to_vec_nearest_neighbors.py 
      /scratch/sjn-p3/anaconda/anaconda3/lib/python3.6/importlib/_bootstrap.py:219: RuntimeWarning: numpy.dtype size changed, may indicate binary incompatibility. Expected 96, got 88
      return f(*args, **kwds)
      /scratch/sjn-p3/anaconda/anaconda3/lib/python3.6/importlib/_bootstrap.py:219: RuntimeWarning: numpy.dtype size changed, may indicate binary incompatibility. Expected 96, got 88
      return f(*args, **kwds)
      /scratch/sjn-p3/anaconda/anaconda3/lib/python3.6/importlib/_bootstrap.py:219: RuntimeWarning: numpy.dtype size changed, may indicate binary incompatibility. Expected 96, got 88
      return f(*args, **kwds)
      /scratch/sjn-p3/anaconda/anaconda3/lib/python3.6/importlib/_bootstrap.py:219: RuntimeWarning: numpy.dtype size changed, may indicate binary incompatibility. Expected 96, got 88
      return f(*args, **kwds)
      /scratch/sjn-p3/anaconda/anaconda3/lib/python3.6/site-packages/torchvision-0.2.1-py3.6.egg/torchvision/transforms/transforms.py:188: UserWarning: The use of the transforms.Scale transform is deprecated, please use transforms.Resize instead.
      Traceback (most recent call last):
      File "img_to_vec_nearest_neighbors.py", line 18, in <module>
      vec = img2vec.get_vec(img)
      File "../img_to_vec.py", line 43, in get_vec
      h_x = self.model(image)
      File "/scratch/sjn-p3/anaconda/anaconda3/lib/python3.6/site-packages/torch/nn/modules/module.py", line 477, in __call__
      result = self.forward(*input, **kwargs)
      File "/scratch/sjn-p3/anaconda/anaconda3/lib/python3.6/site-packages/torchvision-0.2.1-py3.6.egg/torchvision/models/resnet.py", line 139, in forward
      File "/scratch/sjn-p3/anaconda/anaconda3/lib/python3.6/site-packages/torch/nn/modules/module.py", line 477, in __call__
      result = self.forward(*input, **kwargs)
      File "/scratch/sjn-p3/anaconda/anaconda3/lib/python3.6/site-packages/torch/nn/modules/conv.py", line 301, in forward
      self.padding, self.dilation, self.groups)
      RuntimeError: Given groups=1, weight of size [64, 3, 7, 7], expected input[1, 4, 224, 224] to have 3 channels, but got 4 channels instead


      For example, how can I perform the following command for all the images I have in one folder? My images have the extensions jpg, jpeg, and png, but I don't mind if they all become jpg.



      convert cat.png -background white -alpha remove cat.jpg









      share|improve this question
















      How can I remove the alpha channel from jpg images automatically?



      I am using a deep learning code based on PyTorch that requires 3 channels but my images have 4 channels. I saw this answer but I do not know how to convert all the images in a folder to a counterpart image that does not have an alpha channel.



      Here is the error I receive:



      [jalal@goku example]$ python img_to_vec_nearest_neighbors.py 
      /scratch/sjn-p3/anaconda/anaconda3/lib/python3.6/importlib/_bootstrap.py:219: RuntimeWarning: numpy.dtype size changed, may indicate binary incompatibility. Expected 96, got 88
      return f(*args, **kwds)
      /scratch/sjn-p3/anaconda/anaconda3/lib/python3.6/importlib/_bootstrap.py:219: RuntimeWarning: numpy.dtype size changed, may indicate binary incompatibility. Expected 96, got 88
      return f(*args, **kwds)
      /scratch/sjn-p3/anaconda/anaconda3/lib/python3.6/importlib/_bootstrap.py:219: RuntimeWarning: numpy.dtype size changed, may indicate binary incompatibility. Expected 96, got 88
      return f(*args, **kwds)
      /scratch/sjn-p3/anaconda/anaconda3/lib/python3.6/importlib/_bootstrap.py:219: RuntimeWarning: numpy.dtype size changed, may indicate binary incompatibility. Expected 96, got 88
      return f(*args, **kwds)
      /scratch/sjn-p3/anaconda/anaconda3/lib/python3.6/site-packages/torchvision-0.2.1-py3.6.egg/torchvision/transforms/transforms.py:188: UserWarning: The use of the transforms.Scale transform is deprecated, please use transforms.Resize instead.
      Traceback (most recent call last):
      File "img_to_vec_nearest_neighbors.py", line 18, in <module>
      vec = img2vec.get_vec(img)
      File "../img_to_vec.py", line 43, in get_vec
      h_x = self.model(image)
      File "/scratch/sjn-p3/anaconda/anaconda3/lib/python3.6/site-packages/torch/nn/modules/module.py", line 477, in __call__
      result = self.forward(*input, **kwargs)
      File "/scratch/sjn-p3/anaconda/anaconda3/lib/python3.6/site-packages/torchvision-0.2.1-py3.6.egg/torchvision/models/resnet.py", line 139, in forward
      File "/scratch/sjn-p3/anaconda/anaconda3/lib/python3.6/site-packages/torch/nn/modules/module.py", line 477, in __call__
      result = self.forward(*input, **kwargs)
      File "/scratch/sjn-p3/anaconda/anaconda3/lib/python3.6/site-packages/torch/nn/modules/conv.py", line 301, in forward
      self.padding, self.dilation, self.groups)
      RuntimeError: Given groups=1, weight of size [64, 3, 7, 7], expected input[1, 4, 224, 224] to have 3 channels, but got 4 channels instead


      For example, how can I perform the following command for all the images I have in one folder? My images have the extensions jpg, jpeg, and png, but I don't mind if they all become jpg.



      convert cat.png -background white -alpha remove cat.jpg






      command-line imagemagick image-processing png mogrify






      share|improve this question















      share|improve this question













      share|improve this question




      share|improve this question








      edited Jan 7 at 16:09









      Zanna

      50.6k13134241




      50.6k13134241










      asked Oct 19 '18 at 2:15









      Mona JalalMona Jalal

      1,19052441




      1,19052441






















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          find . -name "*.jpeg" -exec convert "{}" -alpha off "{}" ;
          find . -name "*.png" -exec convert "{}" -alpha off "{}" ;
          find . -name "*.jpg" -exec convert "{}" -alpha off "{}" ;





          share|improve this answer

























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            1 Answer
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            1 Answer
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            active

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            active

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            find . -name "*.jpeg" -exec convert "{}" -alpha off "{}" ;
            find . -name "*.png" -exec convert "{}" -alpha off "{}" ;
            find . -name "*.jpg" -exec convert "{}" -alpha off "{}" ;





            share|improve this answer






























              2














              find . -name "*.jpeg" -exec convert "{}" -alpha off "{}" ;
              find . -name "*.png" -exec convert "{}" -alpha off "{}" ;
              find . -name "*.jpg" -exec convert "{}" -alpha off "{}" ;





              share|improve this answer




























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                2








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                find . -name "*.jpeg" -exec convert "{}" -alpha off "{}" ;
                find . -name "*.png" -exec convert "{}" -alpha off "{}" ;
                find . -name "*.jpg" -exec convert "{}" -alpha off "{}" ;





                share|improve this answer















                find . -name "*.jpeg" -exec convert "{}" -alpha off "{}" ;
                find . -name "*.png" -exec convert "{}" -alpha off "{}" ;
                find . -name "*.jpg" -exec convert "{}" -alpha off "{}" ;






                share|improve this answer














                share|improve this answer



                share|improve this answer








                edited Jan 7 at 16:09









                Zanna

                50.6k13134241




                50.6k13134241










                answered Oct 19 '18 at 3:07









                Mona JalalMona Jalal

                1,19052441




                1,19052441






























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