AI Choreographer 多模式内容创建模型训练基础设施

conda create -n mint python=3.7
conda activate mint
conda install protobuf numpy
pip install tensorflow absl-py tensorflow-datasets librosa

sudo apt-get install libopenexr-dev
pip install --upgrade OpenEXR
pip install tensorflow-graphics tensorflow-graphics-gpu

git clone https://github.com/arogozhnikov/einops /tmp/einops
cd /tmp/einops/ && pip install . -U

git clone https://github.com/google/aistplusplus_api /tmp/aistplusplus_api
cd /tmp/aistplusplus_api && pip install -r requirements.txt && pip install . -U

注意如果遇到 numpy 的环境冲突，可以试试 pip install numpy==1.20

获取数据

数据在该网站。

运行代码

• 编译协议

protoc ./mint/protos/*.proto

• 将数据集预处理为 tfrecord 

python tools/preprocessing.py \\
    --anno_dir=\"/mnt/data/aist_plusplus_final/\" \\
    --audio_dir=\"/mnt/data/AIST/music/\" \\
    --split=train
python tools/preprocessing.py \\
    --anno_dir=\"/mnt/data/aist_plusplus_final/\" \\
    --audio_dir=\"/mnt/data/AIST/music/\" \\
    --split=testval

• 训练

python trainer.py --config_path ./configs/fact_v5_deeper_t10_cm12.config --model_dir ./checkpoints

• 运行测试和评估 

# caching the generated motions (seed included) to `./outputs`
python evaluator.py --config_path ./configs/fact_v5_deeper_t10_cm12.config --model_dir ./checkpoints
# calculate FIDs
python tools/calculate_scores.py