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Hi,
I was curious, how do you deal when one data set has 3 channels (imagenet) but others have 1 (omniglot)?
I've seen others do:
transform = transforms.Compose([ lambda x: x.convert("RGB"), transforms.Resize(224), transforms.ToTensor(), ])
in pytorch. Is that what you do?
The text was updated successfully, but these errors were encountered:
We use tf.image.decode_image passing explicitly channels=3, see here.
tf.image.decode_image
channels=3
Then we resize with tf.image.resize_images, and map values to [-1, 1].
tf.image.resize_images
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Hi,
I was curious, how do you deal when one data set has 3 channels (imagenet) but others have 1 (omniglot)?
I've seen others do:
in pytorch. Is that what you do?
The text was updated successfully, but these errors were encountered: