Make sure to clone the repository with the submodules by using: git clone --recursive [email protected]:TritiumR/mega-sam.git

The following codebase was successfully run with Python 3.10, CUDA11.8, and Pytorch2.0.1. We suggest installing the library in a virtual environment such as Anaconda.

1. To install main libraries, run:
   conda env create -f environment.yml

2. To install xformers for UniDepth model, follow the instructions from https://github.com/facebookresearch/xformers. If you encounter any installation issue, we suggest installing it from a prebuilt file. For example, for Python 3.10+Cuda11.8+Pytorch2.0.1, run:
   wget https://anaconda.org/xformers/xformers/0.0.22.post7/download/linux-64/xformers-0.0.22.post7-py310_cu11.8.0_pyt2.0.1.tar.bz2

   conda install xformers-0.0.22.post7-py310_cu11.8.0_pyt2.0.1.tar.bz2

3. Compile the extensions for the camera tracking module:
   cd base; python setup.py install

1. Download DepthAnything checkpoint to mega-sam/Depth-Anything/checkpoints/depth_anything_vitl14.pth

2. Download and include RAFT checkpoint at mega-sam/cvd_opt/raft-things.pth

1. Put your video in data/$NAME

2. Run the following script: ./run.sh $NAME