Video Prediction by GAN
This project aims to adopt the GAN-based architectures, which original proposed by Project Page(https://alexlee-gk.github.io/video_prediction/) Paper(https://arxiv.org/abs/1804.01523), to predict temperature based on ERA5 data
Getting Started
Prerequisites
- Linux or macOS
- Python 3
- CPU or NVIDIA GPU + CUDA CuDNN
Installation
- Clone this repo:
git clone -b master https://gitlab.version.fz-juelich.de/gong1/video_prediction_savp.git
cd Video_Prediction_SAVP- Install TensorFlow >= 1.9 and dependencies from http://tensorflow.org/
- Install other dependencies
pip install -r requirements.txtMiscellaneous installation considerations
- In python >= 3.6, make sure to add the root directory to thePYTHONPATH
, e.g.export PYTHONPATH=path/to/video_prediction_savp`. - For the best speed and experimental results, we recommend using cudnn version 7.3.0.29 and any tensorflow version >= 1.9 and <= 1.12. The final training loss is worse when using cudnn versions 7.3.1.20 or 7.4.1.5, compared to when using versions 7.3.0.29 and below.
- Add the directories lpips-tensorflow and hickle (get from Workflow project to the
PATHONPATH, e.g export PYTHONPATH=path/to/lpips-tensorflow
Download data
- Download the ERA5 data (.hkl) from the output of DataPreprocess in the Workflow project
bash data/download_and_preprocess_dataset_era5.sh --data era5 --input_dir /splits --output_dir data/era5 Model Training
python scripts/train.py --input_dir data/era5 --dataset era5 --model savp --model_hparams_dict hparams/kth/ours_savp/model_hparams.json --output_dir logs/era5/ours_savp