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Browse files- Dockerfile +6 -6
Dockerfile
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# Use the pre-built PyTorch Docker image with CUDA
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FROM pytorch/pytorch:2.1.2-cuda11.8-cudnn8-devel
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# Set up environment variables
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# ENV CONDA_DIR=/opt/conda
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# ENV PATH=$CONDA_DIR/bin:$PATH
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# Install build deps
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RUN apt-get update -y && apt-get install -y wget git vim \
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&& apt-get clean && rm -f /var/lib/apt/lists/*_*
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@@ -19,9 +15,13 @@ RUN git clone --recursive https://github.com/NVlabs/InstantSplat.git && \
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# wget https://download.europe.naverlabs.com/ComputerVision/DUSt3R/DUSt3R_ViTLarge_BaseDecoder_512_dpt.pth -P checkpoints/ && \
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# cd ../../
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# Create the conda environment and install dependencies
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RUN conda create -n instantsplat python=3.11 cmake=3.14.0
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conda install pytorch torchvision pytorch-cuda=12.1 -c pytorch -c nvidia -y && \
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cd InstantSplat && \
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pip install -r requirements.txt && \
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# Use the pre-built PyTorch Docker image with CUDA
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FROM pytorch/pytorch:2.1.2-cuda11.8-cudnn8-devel
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# Install build deps
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RUN apt-get update -y && apt-get install -y wget git vim \
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&& apt-get clean && rm -f /var/lib/apt/lists/*_*
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# wget https://download.europe.naverlabs.com/ComputerVision/DUSt3R/DUSt3R_ViTLarge_BaseDecoder_512_dpt.pth -P checkpoints/ && \
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# cd ../../
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# Set up environment variables
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ENV CONDA_DIR=/opt/conda
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ENV PATH=$CONDA_DIR/bin:$PATH
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# Create the conda environment and install dependencies
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RUN conda create -n instantsplat python=3.11 cmake=3.14.0
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RUN conda activate instantsplat && \
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conda install pytorch torchvision pytorch-cuda=12.1 -c pytorch -c nvidia -y && \
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cd InstantSplat && \
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pip install -r requirements.txt && \
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