Clone this Repo
git clone {https://github.com/tannd-ds/this_repo.git} {REPO_HOME}
Setup Environment, please replace {ENV_NAME} with name of your choice.
conda create -n {ENV_NAME} python=3.10
conda activate {ENV_NAME}
pip install -r requirements.txt
To run the demo of YOLO on VisDrone dataset (test set)
python {REPO_HOME}/run.py \
--MODEL yolo \
--WEIGHTS_PATH {path_to_yolo_weights} \
--SEQUENCES_DIR {path_to_visdrone_dataset_test/test} \
--TRACKER botsort \
--SAVE_RESULTS \
--SHOW
Note: YOLOv10 is not officially part of Ultralytics, we need to set up it differently.
Clone YOLOv10 Repo
git clone https://github.com/NhiNguyen34/yolov10.git {YOLOv10_HOME}
cp {REPO_HOME}/my_utils/run_yolov10_on_visdrone.py {YOLOv10_HOME}
Note: You need to copy the
{REPO_HOME}/my_utils/run_yolov10_on_visdrone.py
to{YOLOv10_HOME}
since it need to use the ultralytics of YOLOv10 instead of the official one.
Setup Environment, please replace {ENV_NAME} with name of your choice.
cd {YOLOv10_HOME}
conda create -n {ENV_NAME} python=3.10
conda activate {ENV_NAME}
pip install -r requirements.txt
To run the demo of YOLO on VisDrone dataset (test set)
cd {YOLOv10_HOME}
python run_yolov10_on_visdrone.py \
--WEIGHTS_PATH {path_to_yolov10_weights} \
--SEQUENCES_DIR {path_to_visdrone_dataset_test/test} \
--TRACKER botsort \
--SAVE_RESULTS \
--SHOW
We use TrackEval for evaluation. To run the evaluation:
cd {REPO_HOME}
python TrackEval/scripts/run_visdrone.py \
--BENCHMARK VisDrone2019-MOT_coco \
--DO_PREPROC False \
--SPLIT_TO_EVAL [train/test] \
--TRACKERS_TO_EVAL {TRACKERS_NAME} \
--USE_PARALLEL True
- After you run above code (the
run.py
, in previous section), by default, your results will be save toTrackEval/data/trackers/mot-challenge/VisDrone2019-MOT_coco/{SPLIT}/{TRACKERS_NAME}
.SPLIT
will betrain
ortest
based on your previous run on VisDrone train or test set respectively.
Some parts of our code are borrowed from the following works: