YOLO_Object_Localization_Keras
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Gentle guide on how YOLO Object Localization works with Keras (Part 2)
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.