Removing the alpha channel from all the jpg images in a folder
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
add a comment |
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
add a comment |
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
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
command-line imagemagick image-processing png mogrify
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
add a comment |
add a comment |
1 Answer
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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 "{}" ;
add a comment |
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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 "{}" ;
add a comment |
find . -name "*.jpeg" -exec convert "{}" -alpha off "{}" ;
find . -name "*.png" -exec convert "{}" -alpha off "{}" ;
find . -name "*.jpg" -exec convert "{}" -alpha off "{}" ;
add a comment |
find . -name "*.jpeg" -exec convert "{}" -alpha off "{}" ;
find . -name "*.png" -exec convert "{}" -alpha off "{}" ;
find . -name "*.jpg" -exec convert "{}" -alpha off "{}" ;
find . -name "*.jpeg" -exec convert "{}" -alpha off "{}" ;
find . -name "*.png" -exec convert "{}" -alpha off "{}" ;
find . -name "*.jpg" -exec convert "{}" -alpha off "{}" ;
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
add a comment |
add a comment |
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