An anchor-free version of YOLO with a simpler design but better performance

YOLOX

YOLOX is an anchor-free version of YOLO, with a simpler design but better performance! It aims to bridge the gap between research and industrial communities. For more details, please refer to our report on Arxiv.

git_fig

demo--1-

Comming soon

[ ] YOLOX-P6 and larger model.
[ ] Objects365 pretrain.
[ ] Transformer modules.
[ ] More features in need.

Benchmark

Standard Models.

Light Models.

Quick Start

Installation

Step1. Install YOLOX.

git clone [email protected]:Megvii-BaseDetection/YOLOX.git
cd YOLOX
pip3 install -U pip && pip3 install -r requirements.txt
pip3 install -v -e .  # or  python3 setup.py develop

Step2. Install apex.

git clone https://github.com/NVIDIA/apex
cd apex
pip3 install -v --disable-pip-version-check --no-cache-dir --global-option="--cpp_ext" --global-option="--cuda_ext" ./

To finish reading, please visit source site