Roboflow Object Tracking Example

Object tracking using Roboflow Inference API and zeroshot CLIP Deep SORT. More on CLIP

Example object tracking courtesy of the Roboflow Universe public playing cards model and dataset. You can adapt this to your own dataset on Roboflow.

Getting Started

Training your model

Upload, annotate, and train your model on Roboflow with Roboflow Train. Your model will be hosted on an inference URL.

Performing Object Tracking

Clone repositories

git clone https://github.com/roboflow-ai/roboflow-object-tracking
cd roboflow-object-tracking
git clone https://github.com/openai/CLIP.git CLIP-repo
cp -r ./CLIP-repo/clip ./clip

Install requirements (python 3.7+)

pip install --upgrade pip
pip install -r requirements.txt

Install requirements (anaconda python 3.8)

conda install pytorch torchvision torchaudio -c pytorch
conda install ftfy regex
pip install opencv pycocotools tensorflow

Run

python clip_object_tracker.py --source data/video/cards.mp4 --url https://detect.roboflow.com/playing-cards-ow27d/1 --api_key ROBOFLO_API_KEY

(by default, output will be in runs/detect/exp[num])

Help

python clip_object_tracker.py -h

Acknowledgements

Huge thanks to:

• yolov4-deepsort by theAIGuysCode
• yolov5 by ultralytics
• Deep SORT Repository by nwojke
• OpenAI for being awesome