---
title: cv_manual_uav-detection_uav
canonical_url: "https://www.modelscope.cn/models/damo/cv_manual_uav-detection_uav"
md_url: "https://www.modelscope.cn/models/damo/cv_manual_uav-detection_uav.md"
repository: damo/cv_manual_uav-detection_uav
last_updated: 2023-03-01
license: "MIT License"
library_name:
  - pytorch
frameworks:
  - pytorch
domain:
  - cv
downloads: 917
stars: 1
tags:
  - "CVPR2023 Workshop"
  - "UAV Detection"
  - "Base Model"
---

# cv_manual_uav-detection_uav

> cv_manual_uav-detection_uav - damo 在 ModelScope 开源的模型。The UAV is a baseline model for CVPR23 Anti_UAV workshop, which encourages participants to develop automated methods that can detect and track UAVs in thermal infrared videos with high accuracy.

damo/cv_manual_uav-detection_uav 是 ModelScope 魔搭社区上的机器学习模型，采用 MIT License 许可。

- **Repository**: damo/cv_manual_uav-detection_uav
- **License**: MIT License
- **Tags**: CVPR2023 Workshop, UAV Detection, Base Model
- **Downloads**: 917
- **Stars**: 1
- **Last updated**: 2023-03-01

Source: https://www.modelscope.cn/models/damo/cv_manual_uav-detection_uav

---

# UAV Model and Dataset

The UAV ([Project](https://github.com/Anti-UAV/baseline)) is a baseline model for CVPR23 Anti_UAV workshop.We encourage participants to develop automated methods that can detect and track UAVs in thermal infrared videos with UAV model and dataset.

# Download Dataset

Install modelscope-cv:
```
pip install "modelscope[cv]" -f https://modelscope.oss-cn-beijing.aliyuncs.com/releases/repo.html
```

Run the download code:
```python
from modelscope.msdatasets import MsDataset
from modelscope.utils.constant import DownloadMode

## Download train set
UAV_train = MsDataset.load('Anti_UAV', namespace='damo', split='train', download_mode=DownloadMode.FORCE_REDOWNLOAD)
print(next(iter(UAV_train)))

## Download validation set
UAV_validation = MsDataset.load('Anti_UAV', namespace='damo', split='validation', download_mode=DownloadMode.FORCE_REDOWNLOAD)
print(next(iter(UAV_validation)))

```

# Download Baseline Model

Install modelscope-cv:
```
pip install "modelscope[cv]" -f https://modelscope.oss-cn-beijing.aliyuncs.com/releases/repo.html
```

Run the download code:
```python
from modelscope.pipelines import pipeline
from modelscope.utils.constant import Tasks
pipeline(Tasks.face_detection, 'damo/cv_manual_uav-detection_uav')
```
**Note**: You can find model architecture, weiths, test code in /root/.cache/modelscope/hub/damo/cv_manual_uav-detection_uav/.


# Evaluation Code

Install CVPR_Anti_UAV
```
git clone https://github.com/ly19965/CVPR_Anti_UAV
pip install -r requirements/tests.txt -f https://modelscope.oss-cn-beijing.aliyuncs.com/releases/repo.html
pip install -r requirements/runtime.txt -f https://modelscope.oss-cn-beijing.aliyuncs.com/releases/repo.html
pip install -r requirements/cv.txt -f https://modelscope.oss-cn-beijing.aliyuncs.com/releases/repo.html
```

Evaluation model accuracy
```python
cd CVPR_Anti_UAV
python tests/pipelines/test_uav_detection.py
```

## Source Description

The model and code come from the open source community([[Project](https://github.com/Anti-UAV/baseline)).Please comply with relevant permits。