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
#Demo
-
git clone
$ git clone https://github.com/quadjr/PredNet.git
$ cd PredNet -
Prepare Dataset
This command will download The KITTI Dataset(about 47GB), unzip, and make image lists.
$ ./scripts/prepare_kitti.sh
You can intterupt and resume downloading. -
Train
On a CPU
$ python main.py -i dataset/train_list.txt
On a GPU
$ python main.py -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).
- Test
$ python main.py -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.