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ValueError: Dimension 2 in both shapes must be equal, but are 1024 and 1280. #23
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Have you solved this problem? I just get the same error. |
In the end this worked in Colab for me on 1024x1024 so I guess connected to the min-h and min-w needing to correspond to your images. Hope this helps. !python run_training.py --num-gpus=1 --data-dir=/yourdatadir --config=config-e --dataset=yourdataset --min-h=8 --min-w=8 --res-log2=7 --mirror-augment=true --metric=none --total-kimg=20000 --result-dir=./results |
Thank you SO MUCH! It works! c: |
I am learning stylegan. |
The formula is given in description of this repository: “Create training image set. Instead of image size of 2^n * 2^n, now you can process your image size as of (min_h x 2^n) X (min_w * 2^n) natually. For example, 640x384, min_h = 5, min_w =3, n=7. Please make sure all your raw images are preprocessed to the exact same size. To reduce the training set size, JPEG format is preferred.” |
Maybe I have the same problem as you? Can you give me some advice? Traceback (most recent call last): |
I don't know why [3,3840,2699]. this shape appears |
Hi,
I get this message when I try to run training on my custom dataset.
ValueError: Dimension 2 in both shapes must be equal, but are 1024 and 1280.
I know all my images are 1024x1024 but the error message seems to suggest otherwise. And the same images work fine on the original stylegan2, so not sure where this is going wrong.
Thanks
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