The UAV (Project) 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.
Install modelscope-cv:
pip install "modelscope[cv]" -f https://modelscope.oss-cn-beijing.aliyuncs.com/releases/repo.html
Run the download code:
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)))
Install modelscope-cv:
pip install "modelscope[cv]" -f https://modelscope.oss-cn-beijing.aliyuncs.com/releases/repo.html
Run the download code:
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/.
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
cd CVPR_Anti_UAV
python tests/pipelines/test_uav_detection.py
The model and code come from the open source community([Project).Please comply with relevant permits。