[AAAI2025] Mamba YOLO: A Simple Baseline for Object Detection with State Space Model
Zeyu Wang, Chen Li, Huiying Xu, Xinzhong Zhu, Hongbo Li
Model Zoo
We've pre-trained Mamba YOLO-T/B/L from scratch and evaluate on the MSCOCO2017 val.
Inference on MSCOCO2017 dataset
| model | Params | FLOPs | ${AP}^{val}$ | ${AP}_{{50}}^{val}$ | ${AP}_{{75}}^{val}$ | ${AP}_{{S}}^{val}$ | ${AP}_{{M}}^{val}$ | ${AP}_{{L}}^{val}$ |
|---|---|---|---|---|---|---|---|---|
| Mamba YOLO-T | 5.8M | 13.2G | 44.5 | 61.2 | 48.2 | 24.7 | 48.8 | 62.0 |
| Mamba YOLO-B | 19.1M | 45.4G | 49.1 | 66.5 | 53.5 | 30.6 | 54.0 | 66.4 |
| Mamba YOLO-L | 57.6M | 156.2G | 52.1 | 69.8 | 56.5 | 34.1 | 57.3 | 68.1 |
Getting started
1. Installation
Mamba YOLO is developed based on torch==2.3.0 pytorch-cuda==12.1 and CUDA Version==12.6.
2.Clone Project
git clone https://github.com/HZAI-ZJNU/Mamba-YOLO.git
3.Create and activate a conda environment.
conda create -n mambayolo -y python=3.11
conda activate mambayolo
4. Install torch
pip3 install torch===2.3.0 torchvision torchaudio
5. Install Dependencies
pip install seaborn thop timm einops
cd selective_scan && pip install . && cd ..
pip install -v -e .
6. Prepare MSCOCO2017 Dataset
Make sure your dataset structure as follows:
├── coco
│ ├── annotations
│ │ ├── instances_train2017.json
│ │ └── instances_val2017.json
│ ├── images
│ │ ├── train2017
│ │ └── val2017
│ ├── labels
│ │ ├── train2017
│ │ ├── val2017
7. Training Mamba-YOLO-T
python mbyolo_train.py --task train --data ultralytics/cfg/datasets/coco.yaml \
--config ultralytics/cfg/models/mamba-yolo/Mamba-YOLO-T.yaml \
--amp --project ./output_dir/mscoco --name mambayolo_n
Acknowledgement
This repo is modified from open source real-time object detection codebase Ultralytics. The selective-scan from VMamba.
Citations
If you find Mamba-YOLO is useful in your research or applications, please consider giving us a star 🌟 and citing it.
@inproceedings{wang2025mamba,
title={Mamba yolo: A simple baseline for object detection with state space model},
author={Wang, Zeyu and Li, Chen and Xu, Huiying and Zhu, Xinzhong and Li, Hongbo},
booktitle={Proceedings of the AAAI conference on artificial intelligence},
volume={39},
number={8},
pages={8205--8213},
year={2025}
}