ALAE
torch-metrics
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ALAE | torch-metrics | |
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1 | 2 | |
3,492 | 109 | |
- | - | |
0.0 | 1.8 | |
about 3 years ago | about 3 years ago | |
Python | Python | |
- | MIT License |
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ALAE
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[D] How do I make a model which takes a bedroom image as input give an output of different design of bedroom related to input image?
source link: https://github.com/podgorskiy/ALAE
torch-metrics
- Torch Metrics Library
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[P] Contributions needed for PyTorch metrics library
Hi all I've created a metrics library for PyTorch here but will need lots of contributions to make it as user friendly as possible. Feature requests/ contributions are welcome :) Feel free to use it in your projects if you find it useful. Thanks.
What are some alternatives?
jukebox - Code for the paper "Jukebox: A Generative Model for Music"
ignite - High-level library to help with training and evaluating neural networks in PyTorch flexibly and transparently.
simsiam-cifar10 - Code to train the SimSiam model on cifar10 using PyTorch
Robo-Semantic-Segmentation - Just a simple semantic segmentation library that I developed to speed up the image segmentation pipeline
dnn_from_scratch - A high level deep learning library for Convolutional Neural Networks,GANs and more, made from scratch(numpy/cupy implementation).
PyTorch-VAE - A Collection of Variational Autoencoders (VAE) in PyTorch.
generative-inpainting-pytorch - A PyTorch reimplementation for paper Generative Image Inpainting with Contextual Attention (https://arxiv.org/abs/1801.07892)
onemetric - One Metrics Library to Rule Them All!
lightweight-gan - Implementation of 'lightweight' GAN, proposed in ICLR 2021, in Pytorch. High resolution image generations that can be trained within a day or two
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.
denoising-diffusion-pytorch - Implementation of Denoising Diffusion Probabilistic Model in Pytorch
datasets - 🤗 The largest hub of ready-to-use datasets for ML models with fast, easy-to-use and efficient data manipulation tools