This is an PyTorch implementation of PredNet paper.
The thing that differs from the previous implementation is the use of a Conv-GRU instead of a Conv-LSTM.
Also, I have optimized the way in which the parameters are updated during training, increased training speed with long sequences.
However, the PredNet model is too complex for a realtime application !!
The code is just an example, to extend it at the application level you should create your own training file following the test function created inside of PredNetModel.py
python PredNetModel.pyA NVIDIA GPU of at least 4 GB of global memory and linux/windows/mac os.
Download Python 3.6 Anaconda
bash Anaconda-3.x.x-Linux-x86[_64].sh
After accepting the license terms specify the install location (which defaults to ~/anaconda).
Then, you should install PyTorch and OpenCV:
conda install pytorch torchvision -c pytorch
conda install -c conda-forge opencv - Nicolo Savioli - Initial work
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