Installation. Step1. Install YOLOX from source. git clone git@github.com:Megvii-BaseDetection/YOLOX.git cd YOLOX pip3 install -v -e . # or python3 setup.py ...

Step1. Download a pretrained model from the benchmark table. Step2. Use either -n or -f to specify your detector's config.

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.

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.

14 мая 2023 г. · I found the error. It was because of the Python version. On Python3.10 this package is not working correctly.

31 окт. 2022 г. · Hi There are many guides on how to train and test YOLOX in colab, but are there a guide for how to get i installed on in a local environmnet ...

19 июл. 2023 г. · This topic presents an example about how to deploy a YOLOX model on a RISC-V development board for object detection.

It is a demo application of the YOLOX model. Project description Yolox-Pip: This is a packaged version of the YOLOX for easy installation and use.

21 мар. 2022 г. · Step1. Install YOLOX. git clone git@github.com:Megvii-BaseDetection/YOLOX.git cd YOLOX.

The YOLOX object detection model is a single-stage, anchor-free technique, which significantly reduces the model size and improves computation speed.