| dataset=$1 | |
| workspace=$2 | |
| gpu_id=$3 | |
| audio_extractor='deepspeech' # deepspeech, esperanto, hubert | |
| export CUDA_VISIBLE_DEVICES=$gpu_id | |
| python train_mouth.py -s $dataset -m $workspace --audio_extractor $audio_extractor | |
| python train_face.py -s $dataset -m $workspace --init_num 2000 --densify_grad_threshold 0.0005 --audio_extractor $audio_extractor | |
| python train_fuse.py -s $dataset -m $workspace --opacity_lr 0.001 --audio_extractor $audio_extractor | |
| # # Parallel. Ensure that you have aleast 2 GPUs, and over N x 64GB memory for about N x 5k frames (IMPORTANT! Otherwise the computer will crash). | |
| # CUDA_VISIBLE_DEVICES=$gpu_id python train_mouth.py -s $dataset -m $workspace --audio_extractor $audio_extractor & | |
| # CUDA_VISIBLE_DEVICES=$((gpu_id+1)) python train_face.py -s $dataset -m $workspace --init_num 2000 --densify_grad_threshold 0.0005 --audio_extractor $audio_extractor | |
| # CUDA_VISIBLE_DEVICES=$gpu_id python train_fuse.py -s $dataset -m $workspace --opacity_lr 0.001 --audio_extractor $audio_extractor | |
| python synthesize_fuse.py -s $dataset -m $workspace --eval --audio_extractor $audio_extractor | |
| python metrics.py $workspace/test/ours_None/renders/out.mp4 $workspace/test/ours_None/gt/out.mp4 |