icevision 0.1.0rc1

An Agnostic Computer Vision Framework.

An Agnostic Object Detection Framework

---

Note: "We Need Your Help" If you find this work useful, please let other people know by starring it, and sharing it. Thank you!

---

Contributors

Installation

First follow the instructions for installing PyTorch here.

Then:

pip install git+git://github.com/airctic/icevision.git#egg=icevision[all]

For more installation options, check our docs.

Important: We currently only support Linux/MacOS.

Quick Example: How to train the PETS Dataset

Source Code

The Problem We Are Solving

• Object dectection datasets come in different sizes and most impotantly have different annotations formats ranging from the stanndard formarts such COCO and VOC to more self-tailored formats
• When new object detection models are released with some source code, the latter is very often written in non-portable way: The source code is difficult to use for other datasets because of some hard-coded parts coupled with self developed tweaks
• Both researchers and DL coders have to deploy a lot of effort to use many SOTA models for their own use-cases and/or to craft an enhanced model based on those already published

Our Solution

IceVision library provides some elegant solutions in those 2 fundamental components:

1- A Unified Data API

Out of the box, we offer several annotation parsers that translates different annotation formats into a very flexibe parser:

• By default, we offer differents standard format parsers such as COCO and VOC.
• We host a community curated parsers where community contributors publish their own parsers to be shared, and therefore save time and energy in creating similar parsers over and over.
• We provide some intuitive tutorials that walk you through the steps of creating your own parser. Please, consider sharing it with the whole community.

2- A Universal Adapter to different DL Libraries

• IceVision provides a universal adapter that allows you to hook up your dataset to the DL library of your choice (fastai, Pytorch Lightning and Pytorch), and train your model using a familiar API.
• Our library allows you to choose one of the public implementations of a given model, plug it in icevision model adapter, and seamlessly train your model.
• As a bonus, our library even allows to experiment with another DL library. Our tutorials have several examples showing you how to train a given model using both fastai and Pytorch Lightning libraries side by side.

Happy Learning!

If you need any assistance, feel free to:

Join our Users Forum

Join our Devs Forum