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A PyTorch library and evaluation platform for end-to-end compression research

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Hello, I would like to ask you a question about the installation of compressai “Successfully installed compressai-1.2.4.dev0” . I successfully installed cmpressai, but I got the following error when importing:...

## Documentation There are no `parameters` or `source` in documentation(https://interdigitalinc.github.io/CompressAI/ans.html) Where I can find that, 3Q.

Hi, I'm using your colab tutorial to compress some random size images. And I found that when image size=(672, 512), they cannot be processed. Could you fix this bug?

As stated, how can we use CompressAI to compress [y] instead of [y-mean]. Furthermore, how can we understand the advantages of compressing [y-mean]? Thank you very much for your answer!!!

As stated, in the evaluation phase, when calling the forward function, the neural network gives you an estimated bit per pixel (bpp) value. I wish to know if this value...

I'm using the EntropyBottleneck module in a factorized prior network. While training, the aux_loss and bpp_loss are decreasing but when I use the trained network to compress and save the...

I want to use entropybottleneck to calculate pmf of weights of a trained model. the range of weights value are mostly between (-1, 1), and the number of parameters is...

Hi, Is there a way to compute per-pixel bitrate info in RGB space of the latent variable y or z during evaluation? Regards

Hello, I have a question regarding the implementation of JointAutoRegressiveHierarchicalPriors. I noticed there is something off in the forward() function. ```python y_hat = self.gaussian_conditional.quantize( # Why do you use this...

Hello, in the CompressAI documentation, it is mentioned that "MS-SSIM optimized networks were fine-tuned from pre-trained MSE networks (with a learning rate of 1e-5 for both optimizers)." I want to...