Agnostic Computer Vision Framework
Project description
An Agnostic Object Detection Framework
IceVision is the first agnostic computer vision framework to offer a curated collection with hundreds of high-quality pre-trained models from torchvision, MMLabs, 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:
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
Built Distribution
Hashes for icevision-0.12.0-py3-none-any.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | 2d3dc9baea271f23490cce6aa48b682cb381b6dccdcbef7bfffa8f682ac63fb7 |
|
MD5 | c7d8a5e6e3830f6b8db8c5242e6ba5b9 |
|
BLAKE2b-256 | 6595a6c10800730777974336f75ccdf6efc19bc858de9959743684d280403d2a |