Dockerfile

FROM pytorch/pytorch:2.0.1-cuda11.7-cudnn8-runtime

ENV DEBIAN_FRONTEND=noninteractive
ENV MKL_THREADING_LAYER=GNU

# Install dependencies
RUN apt-get update && apt-get install -y \
    git wget libgl1-mesa-glx libglib2.0-0 ffmpeg libx264-dev pkg-config \
    build-essential cmake g++ python3-dev software-properties-common \
    wget gnupg2 libopenblas-dev && \
    rm -rf /var/lib/apt/lists/*

# Add NVIDIA package repositories
RUN wget https://developer.download.nvidia.com/compute/cuda/repos/ubuntu2004/x86_64/cuda-keyring_1.0-1_all.deb && \
    dpkg -i cuda-keyring_1.0-1_all.deb && \
    apt-get update

# Install CUDA Toolkit and cuDNN
RUN apt-get install -y cuda-toolkit-11-7 libcudnn8 libcudnn8-dev

# Create a user
RUN useradd -m -u 1000 user
USER user

# Set CUDA paths
ENV HOME=/home/user \
    PATH=/home/user/.local/bin:/usr/local/cuda/bin:$PATH \
    PYTHONPATH=$HOME/app \
    PYTHONUNBUFFERED=1 \
    GRADIO_ALLOW_FLAGGING=never \
    GRADIO_NUM_PORTS=1 \
    GRADIO_SERVER_NAME=0.0.0.0 \
    GRADIO_THEME=huggingface \
    GRADIO_SHARE=False \
    SYSTEM=spaces \
    CUDA_TOOLKIT_ROOT_DIR=/usr/local/cuda \
    CUDA_HOME=/usr/local/cuda \
    LD_LIBRARY_PATH=/usr/local/cuda/lib64:$LD_LIBRARY_PATH \
    TORCH_CUDA_ARCH_LIST="8.6"

# Set CUDA & cuDNN paths
ENV CMAKE_PREFIX_PATH="/usr/local/cuda:/usr/lib/x86_64-linux-gnu/"

# Set working directory
WORKDIR $HOME/app

# Clone the repository
RUN git clone -b dev https://github.com/fffiloni/dreamtalk $HOME/app 

# Download model checkpoints
RUN wget https://huggingface.co/camenduru/dreamtalk/resolve/main/damo/dreamtalk/checkpoints/denoising_network.pth -O $HOME/app/checkpoints/denoising_network.pth
RUN wget https://huggingface.co/camenduru/dreamtalk/resolve/main/damo/dreamtalk/checkpoints/renderer.pt -O $HOME/app/checkpoints/renderer.pt

# Upgrade pip & install dependencies
RUN pip install --upgrade pip setuptools wheel
RUN pip install --no-cache-dir urllib3 transformers yacs scipy scikit-image scikit-learn PyYAML Pillow "numpy<2" opencv-python imageio ffmpeg-python av "moviepy<2" gradio

# Install CMake first
RUN pip install cmake

# Install dlib with CUDA support (force source compilation)
RUN pip install --no-cache-dir dlib -vvv --no-binary dlib

# Copy application file
COPY app.py .

# Set CUDA environment variables
ENV CUDA_DEVICE_ORDER=PCI_BUS_ID
ENV CUDA_VISIBLE_DEVICES=0

# Run the application
CMD ["python", "app.py"]