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This is a implimentation of PredNet on chainer.

#Testd on *Ubuntu 14.04
*Python 2.7.6
*chainer 1.9.1
*CUDA Toolkit 7.5
*cuDNN v5


  1. git clone
    $ git clone
    $ cd PredNet

  2. Prepare Dataset
    This command will download The KITTI Dataset(about 47GB), unzip, and make image lists.
    $ ./scripts/
    You can intterupt and resume downloading.

  3. Train
    On a CPU
    $ python -i dataset/train_list.txt
    On a GPU
    $ python -i dataset/train_list.txt -g 0

Model files and some images will be generated in models/ and images/ directory.
Image suffix means x (input), y (predicted), z (correct).

  1. Test
    $ python -i dataset/test_list.txt --test --initmodel models/???.model
    Plase specify the model file with option --initialmodel.
    Test result will be generated in images/ directory.
    Image suffix means x (input), y (predicted).

#TODO *Confirm the learning strategy.