https://github.com/zeqiang-lai/torchlight
Torchlight is a light-weight PyTorch wrapper with many useful util functions for fast prototyping of computer vision models.
https://github.com/zeqiang-lai/torchlight
deep-learning pytorch
Last synced: about 1 year ago
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Torchlight is a light-weight PyTorch wrapper with many useful util functions for fast prototyping of computer vision models.
- Host: GitHub
- URL: https://github.com/zeqiang-lai/torchlight
- Owner: Zeqiang-Lai
- Created: 2021-07-10T11:09:01.000Z (about 5 years ago)
- Default Branch: main
- Last Pushed: 2024-03-28T11:52:37.000Z (over 2 years ago)
- Last Synced: 2025-04-16T00:58:15.705Z (about 1 year ago)
- Topics: deep-learning, pytorch
- Language: Python
- Homepage: https://torchlight.readthedocs.io
- Size: 1.67 MB
- Stars: 14
- Watchers: 3
- Forks: 1
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
# Torchlight
[](https://torchlight.readthedocs.io/en/latest/?badge=latest)
[](https://pypi.org/project/torchlights/)
Torchlight provides an light-weight PyTorch trainer, as well as many useful utils, including network components, transforms, metrics, etal. for fast prototyping of computer vision models.
**:sparkles: All top level packages are self-contained and independent. Feel free to steal any part into your own project.**
[](https://asciinema.org/a/441271)
## Installation
- Install via [PyPI](https://pypi.org/project/torchlights/).
```shell
pip install torchlights
```
- Install the latest version from source.
```shell
git clone https://github.com/Zeqiang-Lai/torchlight.git
cd torchlight
pip install .
pip install -e . # editable installation
# or simply if you don't need editable installation
pip install git+https://github.com/Zeqiang-Lai/torchlight.git
```
## Features
- Most modules are self-contained.
- Debug Mode.
- User friendly progress bar .
- Save latest checkpoint if interrupted by Ctrl-C.
- Override any option in configuration file with cmd args.
## Useful Tools
- [kornia](https://github.com/kornia/kornia): Open Source Differentiable Computer Vision Library.
- [huggingface/datasets](https://github.com/huggingface/datasets/): original design for NLP, but also include some vision datasets.
- [huggingface/accelerate](https://github.com/huggingface/accelerate/): A simple way to train and use PyTorch models with multi-GPU, TPU, mixed-precision.
- [einops](https://github.com/arogozhnikov/einops): Flexible and powerful tensor operations for readable and reliable code.
- [torch-fidelity](https://github.com/toshas/torch-fidelity): High-fidelity performance metrics for generative models in PyTorch.
- [piq](https://github.com/photosynthesis-team/piq): Measures and metrics for image2image tasks. PyTorch.
- [image-similarity-measures](https://github.com/up42/image-similarity-measures): Numpy implementation of eight evaluation metrics to access the similarity between two images. The eight metrics are as follows: RMSE, PSNR, SSIM, ISSM, FSIM, SRE, SAM, and UIQ.
- [ResizeRight](https://github.com/assafshocher/ResizeRight): The correct way to resize images or tensors. For Numpy or Pytorch (differentiable).
- [omegaconf](https://github.com/omry/omegaconf): Flexible Python configuration system. The last one you will ever need.