Pytorch-UNet
Wave-U-Net-for-Speech-Enhancement
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| Pytorch-UNet | Wave-U-Net-for-Speech-Enhancement | |
|---|---|---|
| 2 | 1 | |
| 8,358 | 302 | |
| - | - | |
| 3.9 | 0.0 | |
| 3 months ago | over 1 year ago | |
| Python | Python | |
| GNU General Public License v3.0 only | MIT License |
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Pytorch-UNet
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Trying to find resources for "Image Segmentation using RL"
Probably mean something like unet: https://github.com/milesial/Pytorch-UNet
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How to add a pyramid pooling in UNet++?
Hi! I will give you some resources that might help you understand(I didnt implement a network but I can answer more questions about how you can train it). 1 This link gives you a broad explanation about UNet. 2 This is a link to a UNet used for binary segmentation. 3 This is a step by step guide. The UNet++ that I posted is good for multiclass segmentation. If you need more advice feel free to reply. Good luck!
Wave-U-Net-for-Speech-Enhancement
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[P] Malaya-Speech, Speech-Toolkit library for Malay language, powered by Deep Learning Tensorflow
Speech Enhancement UNET, https://github.com/haoxiangsnr/Wave-U-Net-for-Speech-Enhancement
What are some alternatives?
mmsegmentation - OpenMMLab Semantic Segmentation Toolbox and Benchmark.
malaya-speech - Speech Toolkit for Malaysian language, https://malaya-speech.readthedocs.io/
face-parsing.PyTorch - Using modified BiSeNet for face parsing in PyTorch
asteroid - The PyTorch-based audio source separation toolkit for researchers
lightning-hydra-template - Deep Learning project template best practices with Pytorch Lightning, Hydra, Tensorboard.
unet-nested-multiple-classification - This repository contains code for a multiple classification image segmentation model based on UNet and UNet++
pyannote-audio - Neural building blocks for speaker diarization: speech activity detection, speaker change detection, overlapped speech detection, speaker embedding
efficientdet-pytorch - A PyTorch impl of EfficientDet faithful to the original Google impl w/ ported weights
espnet - End-to-End Speech Processing Toolkit
d2l-en - Interactive deep learning book with multi-framework code, math, and discussions. Adopted at 500 universities from 70 countries including Stanford, MIT, Harvard, and Cambridge.
segmentation_models.pytorch - Segmentation models with pretrained backbones. PyTorch.