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Steps for Training

Dataset

Before training, download the videos files and the .csv annotations of WebVid10M to the local mechine. Note that our examplar training script requires all the videos to be saved in a single folder. You may change this by modifying animatediff/data/dataset.py.

Configuration

After dataset preparations, update the below data paths in the config .yaml files in configs/training/ folder:

train_data:
  csv_path: [Replace with .csv Annotation File Path]
  video_folder: [Replace with Video Folder Path]
  sample_size: 256

Other training parameters (lr, epochs, validation settings, etc.) are also included in the config files.

Training

To finetune the unet's image layers

torchrun --nnodes=1 --nproc_per_node=1 train.py --config configs/training/v1/image_finetune.yaml

To train motion modules

torchrun --nnodes=1 --nproc_per_node=1 train.py --config configs/training/v1/training.yaml