airctic/icevision
airctic/icevision has 866 GitHub stars and 145 forks. GitHot measured 0 stars in 24 hours, 0 in 7 days, and -1 in 15 days. Last checked 2026-11-10 00:28 UTC. Last push 2024-11-26.
An Agnostic Computer Vision Framework - Pluggable to any Training Library: Fastai, Pytorch-Lightning with more to come
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README.md
Original
An Agnostic Computer Vision Framework
IceVision is the first agnostic computer vision framework to offer a curated collection with hundreds of high-quality pre-trained models from Torchvision, Open MMLab's MMDetection, Ultralytic's YOLOv5, Ross Wightman's EfficientDet and soon PyTorch Image Models. It orchestrates the end-to-end deep learning workflow allowing to train networks with easy-to-use robust high-performance libraries such as PyTorch-Lightning and Fastai.
IceVision Unique Features:
Data curation/cleaning with auto-fix
Access to an exploratory data analysis dashboard
Pluggable transforms for better model generalization
Access to hundreds of neural net models
Access to multiple training loop libraries
Multi-task training to efficiently combine object detection, segmentation, and classification models
Installation
pip install icevision[all]
For more installation options, check our docs.
Important: We currently only support Linux/MacOS.
Quick Example: How to train the Fridge Objects Dataset

Happy Learning!
If you need any assistance, feel free to:
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