- 2018-08-04 - Option to select the preferred GPU -
- 2018-04-23 - PyPI Release of RC12
- Python 3.5
pip3 install numpy
pip3 install cython
- Optionally, OpenCV 3.x with Python bindings. (Tested on OpenCV 3.4.0)
- You can use this script to automate Open CV 3.4 installation (Tested on Ubuntu 16.04).
- Performance of this approach is better than not using OpenCV.
- Installations from PyPI distributions does not use OpenCV.
NOTE: OpenCV 3.4.1 has a bug which causes Darknet to fail. Therefore this wrapper would not work with OpenCV 3.4.1. More details are available at https://github.com/pjreddie/darknet/issues/502
Installation from PyPI distribution (as described below) is the most convenient approach if you intend to use yolo34py for your projects.
Installation of CPU Only Version
pip3 install yolo34py
Installation of GPU Accelerated Version
pip3 install yolo34py-gpu
NOTE: PyPI Deployments does not use OpenCV due to complexity involved in installation. To get best performance, it is recommended to install from source with OpenCV enabled.
NOTE: Make sure CUDA_HOME environment variable is set.
How to run demos in local machine?
- If you have not installed already, run
python3 setup.py build_ext --inplaceto install library locally.
- Download "yolov3" model file and config files using
How to run demo using docker?
- Navigate to docker directory.
- Copy sample images into the
inputdirectory. Or else run input/download_sample_images.sh
- Observe the outputs generated in
Installation from Source
- Set environment variables
- To enable GPU acceleration,
- To enable OpenCV,
- Navigate to source root and run
pip3 install .to install library.
Using a custom version of Darknet
- Set environment variable DARKNET_HOME to download location of darknet.
- Add DARKNET_HOME to LD_LIBRARY_PATH.
- Continue instructions for installation from source.
Kindly raise your issues in the issues section of GitHub repository.
Like to contribute?
Feel free to send PRs or discuss on possible future improvements in issues section. Your contributions are most welcome!