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In this PR, I'm adding an example for detecting license plates with YOLOv3. The model has obviously been trained with this Keras implementation. This also includes the configuration file in
zoo/
.Apart from this change, I've also added some lines to limit the GPU usage down to a given percentage so as to not get the infamous
CUDA_OUT_OF_MEMORY
. Also, I've setallow_growth = True
to not allow the GPU to preallocate memory and to let it use just as much as it needs. See https://stackoverflow.com/a/39467358/2096747.I've added a
debug = False
variable intrain.py
to prevent getting too many debug messages while training - this has the benefit of being able to witness the model's progress (on the loss) as it trains.Added
create_validation_script.sh
script to divide the dataset into training and validation sets (for VOC format).Added requirements file for the project to work. Without it, time is wasted finding out the right dependencies, especially with TensorFlow and Keras.