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Gentle guide on how YOLO Object Localization works with Keras

Complementary source code for the post. Keras+TensorFlow YOLO object Localization implementation guided walk through.

How to Run

Require Python 3.5+ and Jupyter notebook installed

Clone or download this repo

git clone https://github.com/Tony607/YOLO_Object_Localization

Install required libraries

pip3 install -r requirements.txt

Download the Pre-trained YOLO model

Download the trained model weight from the releases, yolo.h5. Put it to model_data folder in the project directory.

Start the notebook

In the project directory start a command line, then run

jupyter notebook

In the opened browser window open

Gentle guide on how YOLO Object Localization works with Keras.ipynb

Side note, if the model doesn't load correctly try to follow the instruction on YAD2K

• Clone/Download YAD2K.
• Download Darknet model cfg and weights from the official YOLO website.
• Convert the Darknet YOLO_v2 model to a Keras model.
• Test the converted model on the small test set in images/.

git clone https://github.com/allanzelener/YAD2K
wget http://pjreddie.com/media/files/yolo.weights
wget https://raw.githubusercontent.com/pjreddie/darknet/master/cfg/yolo.cfg
./yad2k.py yolo.cfg yolo.weights model_data/yolo.h5
./test_yolo.py model_data/yolo.h5  # output in images/out/

See ./yad2k.py --help and ./test_yolo.py --help for more options.

Happy coding! Leave a comment if you have any question.