git clone https://github.com/Inception3D/TTT3R.git
cd TTT3R

conda create -n ttt3r python=3.11 cmake=3.14.0
conda activate ttt3r
conda install pytorch torchvision pytorch-cuda=12.1 -c pytorch -c nvidia  # use the correct version of cuda for your system
pip install -r requirements.txt
# issues with pytorch dataloader, see https://github.com/pytorch/pytorch/issues/99625
conda install 'llvm-openmp<16'
# for evaluation
pip install evo
pip install open3d

cd src/croco/models/curope/
python setup.py build_ext --inplace
cd ../../../../

cd src
gdown --fuzzy https://drive.google.com/file/d/1Asz-ZB3FfpzZYwunhQvNPZEUA8XUNAYD/view?usp=drive_link
cd ..

# input can be a folder or a video
# the following script will run inference with TTT3R and visualize the output with viser on port 8080
CUDA_VISIBLE_DEVICES=6 python demo.py --model_path MODEL_PATH --size 512 \
    --seq_path SEQ_PATH --output_dir OUT_DIR --port 8080 \
    --model_update_type ttt3r --frame_interval 1 --reset_interval 100 \
    --downsample_factor 1000 --vis_threshold 5.0
# Example:
CUDA_VISIBLE_DEVICES=6 python demo.py --model_path src/cut3r_512_dpt_4_64.pth --size 512 \
    --seq_path examples/westlake.mp4 --output_dir tmp/taylor --port 8080 \
    --model_update_type ttt3r --frame_interval 1 --reset_interval 100 \
    --downsample_factor 100 --vis_threshold 6.0
CUDA_VISIBLE_DEVICES=6 python demo.py --model_path src/cut3r_512_dpt_4_64.pth --size 512 \
    --seq_path examples/taylor.mp4 --output_dir tmp/taylor --port 8080 \
    --model_update_type ttt3r --frame_interval 1 --reset_interval 50 \
    --downsample_factor 100 --vis_threshold 10.0