Create Dockerfile

Dockerfile

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+
+
+FROM nvidia/cuda:11.8.0-devel-ubuntu22.04
+
+# Use NVIDIA CUDA 11.8 base image
+# FROM nvidia/cuda:11.8.0-devel-ubuntu22.04
+
+# # Set environment variables
+# ENV DEBIAN_FRONTEND=noninteractive
+# ENV PYTHONUNBUFFERED=1
+# ENV LD_LIBRARY_PATH=/usr/local/cuda/lib64:$LD_LIBRARY_PATH
+
+# # Install system dependencies
+RUN apt-get update && apt-get install -y \
+    wget \
+    git \
+    python3.10 \
+    python3-pip \
+    python3.10-venv \
+    libgl1 \
+    libglib2.0-0 \
+    && rm -rf /var/lib/apt/lists/*
+
+# Clone the WildGS-SLAM repository with submodules
+RUN git clone --recursive https://github.com/GradientSpaces/WildGS-SLAM.git /app
+
+
+RUN python3 --version 
+# Create and activate Python 3.10 virtual environment
+RUN python3.10 -m venv /venv
+ENV PATH="/venv/bin:$PATH"
+
+WORKDIR /app
+
+# Install Python dependencies
+# COPY requirements.txt /tmp/requirements.txt
+RUN pip install --upgrade pip && \
+    pip install numpy==1.26.3 && \
+    pip install torch==2.1.0 torchvision==0.16.0 torchaudio==2.1.0 --index-url https://download.pytorch.org/whl/cu118 && \
+    pip install torch-scatter -f https://data.pyg.org/whl/torch-2.1.0+cu118.html && \
+    pip install xformers==0.0.22.post7 --index-url https://download.pytorch.org/whl/cu118 && \
+    pip install -r requirements.txt && \
+    pip install mmcv-full -f https://download.openmmlab.com/mmcv/dist/cu118/torch2.1.0/index.html && \
+    pip install gdown
+
+
+#check pytorch install ? 
+
+# 4. Verify PyTorch installation before proceeding
+# 4. Verify PyTorch installation
+RUN python -c "import torch; print(f'PyTorch {torch.__version__}, CUDA {torch.version.cuda}')" && \
+    python -m pip list | grep torch
+
+# 4. Install build dependencies
+RUN apt-get update && apt-get install -y \
+    build-essential \
+    ninja-build
+
+RUN pip install --upgrade pip wheel setuptools
+
+#nvcc ? need devel base image
+RUN ls -la /usr/local/cuda/bin/nvcc 
+
+# 5. Install with explicit CUDA flags
+RUN cd thirdparty/lietorch && \
+    export TORCH_CUDA_ARCH_LIST="8.6" && \ 
+    export FORCE_CUDA=1 && \
+    pip install --no-build-isolation -v -e . && \
+    grep "Successfully installed" install.log && \
+    cd /app
+
+
+RUN pip install -v --no-cache-dir --no-build-isolation -e thirdparty/lietorch/
+
+# Install custom packages from the cloned repository
+RUN python -m pip install -e thirdparty/lietorch/ && \
+    python -m pip install -e thirdparty/diff-gaussian-rasterization-w-pose/ && \
+    python -m pip install -e thirdparty/simple-knn/
+
+# Install the main package
+RUN python -m pip install -e .
+
+# Create pretrained directory and download model
+RUN mkdir -p /app/pretrained && \
+    gdown https://drive.google.com/uc?id=1PpqVt1H4maBa_GbPJp4NwxRsd9jk-elh -O /app/pretrained/droid.pth
+
+# Verify installation
+RUN python -c "import torch; import lietorch; import simple_knn; import diff_gaussian_rasterization; print(torch.cuda.is_available())"
+
+# Set default command
+CMD ["bash"]
+
+
+#build lighter runtime image ? 
+#FROM nvidia/cuda:11.8.0-base-ubuntu22.04