Skip to content

Latest commit

 

History

History
47 lines (38 loc) · 1.42 KB

README.md

File metadata and controls

47 lines (38 loc) · 1.42 KB
Raw

42028-YOLOX-Colaboratory-Training

This is a colab tutorial to train YOLOX on Google Colaboratory
It includes the following contents.

  • Sample Aquarium Data set (Annotation not implemented)
  • Sample Aquarium Data set (Annotated)
  • Colaboratory notebook (environment setting, model training)

Requirements

  • Pytorch 1.9.0 or later
  • apex 0.1 or later
  • pycocotools 2.0 or later
  • OpenCV 3.4.2 or later
  • onnxruntime 1.5.2 or later ※Only when performing inference samples

About annotation

It is assumed that annotation data is in Pascal VOC format.
However, it is further converted to MS COCO format in the notebook.

You may modify the code to use your dataset in COCO format if required.

The notebook sample assumes the following directory structure.
However, since "pascal_label_map.pbtxt" is not used in this sample,
There is no problem even if you do not store it.

02.annotation_data
│  000001.jpg
│  000001.xml
│  000002.jpg
│  000002.xml
│   :
│  000049.jpg
│  000049.xml
│  000050.xml
└─ pascal_label_map.pbtxt

Usage

Use Colab
Training will be performed on Google Colaboratory.

Author

Gitarth Vaishnav

License

42028_YOLOX is under Apache-2.0 License.