Python scripts performing class agnostic object localization using the Object Localization Network model in ONNX.
Original image: https://en.wikipedia.org/wiki/File:Interior_design_865875.jpg
- I added a bit of logic to the box color selection to make it look nicer. Since it performs K-Means for each box, it might be slow. If you only care about speed, you can either set all the boxes to the same color or use random colors.
- Check the requirements.txt file.
- For ONNX, if you have a NVIDIA GPU, then install the onnxruntime-gpu, otherwise use the onnxruntime library.
- Additionally, pafy and youtube-dl are required for youtube video inference.
git clone https://github.com/ibaiGorordo/ONNX-Object-Localization-Network.git
cd ONNX-Object-Localization-Network
pip install -r requirements.txt
For Nvidia GPU computers:
pip install onnxruntime-gpu
Otherwise:
pip install onnxruntime
pip install youtube_dl
pip install git+https://github.com/zizo-pro/pafy@b8976f22c19e4ab5515cacbfae0a3970370c102b
The original model was converted to ONNX by PINTO0309, download the models from the download script in his repository and save them into the models folder.
- The License of the models is Apache-2.0 License: https://github.com/mcahny/object_localization_network/blob/main/LICENSE
The original Pytorch model can be found in this repository: https://github.com/mcahny/object_localization_network
- Image inference:
python image_object_localization.py
- Webcam inference:
python webcam_object_localization.py
- Video inference: https://youtu.be/n9qhQJXYUWo
python video_object_localization.py
Original video: https://youtu.be/vgJUXvkdS78
- Object-Localization-Network model: https://github.com/mcahny/object_localization_network
- PINTO0309's model zoo: https://github.com/PINTO0309/PINTO_model_zoo
- Original paper: https://arxiv.org/abs/2108.06753