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v0.2.0: Improved models, a demo app and a vision API

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@frgfm frgfm released this 20 Jul 00:42
6d88202

This release brings a big performance leap to classification models while providing easier contribution and deployment tools.

Note: pyrovision 0.2.0 requires PyTorch 1.11 and torchvision 0.12 or newer.

Highlights

🎁 Gradio Demo

gradio_demo

In order to showcase pyrovision added value, a short Gradio demo app was added to the repo!
You can try it out live on HF Spaces over 👉 here

💻 API boilerplate

Thanks to the great FastAPI by Sebastián Ramírez (@tiangolo), we have added a small template to deploy your own vision API 😁

Check out in the folder ./api how to get yours running!

🤗 HF Hub integration

Contributions are important in open source projects and we're happy to announce that our model checkpoints are now available on HF Hub. See it as a github for data files (checkpoints for instance) 👍

You can load a model from the hub with two lines:

from pyrovision.models.utils import model_from_hf_hub
model = model_from_hf_hub("pyronear/rexnet1_0x")

If you upload your model as well, you can load it from the hub by changing "pyronear/rexnet1_0x" into "hf_user/model_repo"

🔥 OpenFire reloaded

You might have noticed that our first version of OpenFire started to have a lot of URLs failing. We've scaled up our queries to retrieve public images and checked them manually to produce a new updated version of ~7000 train images and ~800 validation images. The dataset was used to train the new model checkpoints!

The dataset is also available on HF datasets: https://huggingface.co/datasets/pyronear/openfire

Breaking changes

✝️ Deprecated modules

The following modules and features were deprecated:

  • pyrovision.nn
  • pyrovision.datasets.wildfire & pyrovision.datasets.video_utils
  • pyrovision.models.densenet & pyrovision.models.ssresnet

Full changelog

Breaking Changes 🛠

New Features 🚀

  • chore: add workflow to publish docker image by @MateoLostanlen in #120
  • feat: Added codecarbon integration by @frgfm in #140
  • feat: Added new classification checkpoints by @frgfm in #150
  • feat: Added a Gradio demo by @frgfm in #151
  • feat: Added minimal API template by @frgfm in #152
  • feat: Updated OpenFire extract by @frgfm in #153
  • feat: Added image prefetching option to Openfire by @frgfm in #158
  • feat: Improved all model checkpoints and added HF hub loading function by @frgfm in #159
  • ci: Added release note template file by @frgfm in #160

Bug Fixes 🐛

Improvements

  • docs: add inference exemple in readme by @MateoLostanlen in #116
  • docs: remove email adress by @MateoLostanlen in #122
  • chore: Updated CI jobs by @frgfm in #128
  • docs: Updated README & CONTRIBUTING by @frgfm in #127
  • refactor: Refactored setup.py by @frgfm in #133
  • chore: Updated license from AGPLv3 to Apache 2 by @frgfm in #132
  • ci: Updated python version for builds by @MateoLostanlen in #135
  • ci: Updated funding from OpenCollective to Github by @frgfm in #142
  • style: Improved code style and documentation by @frgfm in #143
  • chore: Updates version specifiers & conda recipe by @frgfm in #145
  • docs: Updates documentation and README by @frgfm in #146
  • ci: Updated header verification, env collection and docker job by @frgfm in #147
  • feat: Updated augmentations for training and disabled codecarbon logger by @frgfm in #149
  • feat: Speeds up OpenFire image verification & improves READMEs by @frgfm in #155

New Contributors

  • @fe51 made their first contribution in #134

Full Changelog: v0.1.2...v0.2.0