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Eloi Moliner Juanpere 2022-01-24 10:06:15 +02:00 committed by GitHub
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Listen to our [audio samples](http://research.spa.aalto.fi/publications/papers/icassp22-denoising/) Listen to our [audio samples](http://research.spa.aalto.fi/publications/papers/icassp22-denoising/)
[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/eloimoliner/denoising-historical-recordings/blob/colab/colab/demo.ipynb) [![Open In Colab](https://colab.research.google.com/github/eloimoliner/denoising-historical-recordings/blob/master/colab/demo.ipynb)
## Requirements ## Requirements
You will need at least python 3.7 and CUDA 10.1 if you want to use GPU. See `requirements.txt` for the required package versions. You will need at least python 3.7 and CUDA 10.1 if you want to use GPU. See `requirements.txt` for the required package versions.
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## Denoising Recordings ## Denoising Recordings
You can denoise your recordings in the cloud using the Colab notebook. [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/eloimoliner/denoising-historical-recordings/blob/colab/colab/demo.ipynb) You can denoise your recordings in the cloud using the Colab notebook. [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/eloimoliner/denoising-historical-recordings/blob/master/colab/demo.ipynb)
Otherwise, run the following commands to clone the repository and install the pretrained weights of the two-stage U-Net model: Otherwise, run the following commands to clone the repository and install the pretrained weights of the two-stage U-Net model: