# Base image with complete ML and hardware acceleration stack FROM pytorch/pytorch:2.8.0-cuda12.6-cudnn9-runtime # Install build dependencies and system libraries RUN apt-get update && apt-get install -y \ # Build tools build-essential \ cmake \ git \ pkg-config \ wget \ unzip \ yasm \ nasm \ # System libraries libgl1 \ libglib2.0-0 \ libgtk-3-0 \ libgomp1 \ # Media libraries for FFmpeg build libjpeg-dev \ libpng-dev \ libtiff-dev \ libx264-dev \ libx265-dev \ libvpx-dev \ libfdk-aac-dev \ libmp3lame-dev \ libopus-dev \ libv4l-dev \ libxvidcore-dev \ libdc1394-22-dev \ # TurboJPEG for fast JPEG encoding libturbojpeg0-dev \ # GStreamer complete stack libgstreamer1.0-dev \ libgstreamer-plugins-base1.0-dev \ libgstreamer-plugins-bad1.0-dev \ gstreamer1.0-tools \ gstreamer1.0-plugins-base \ gstreamer1.0-plugins-good \ gstreamer1.0-plugins-bad \ gstreamer1.0-plugins-ugly \ gstreamer1.0-libav \ gstreamer1.0-vaapi \ python3-gst-1.0 \ # Python development python3-dev \ python3-numpy \ # NVIDIA driver components libnvidia-encode-535 \ libnvidia-decode-535 \ && rm -rf /var/lib/apt/lists/* # Install NVIDIA Video Codec SDK headers RUN cd /tmp && \ wget https://github.com/FFmpeg/nv-codec-headers/archive/refs/tags/n12.1.14.0.zip && \ unzip n12.1.14.0.zip && \ cd nv-codec-headers-n12.1.14.0 && \ make install && \ rm -rf /tmp/* # Build FFmpeg from source with full NVIDIA hardware acceleration ENV FFMPEG_VERSION=6.0 RUN cd /tmp && \ wget https://ffmpeg.org/releases/ffmpeg-${FFMPEG_VERSION}.tar.xz && \ tar xf ffmpeg-${FFMPEG_VERSION}.tar.xz && \ cd ffmpeg-${FFMPEG_VERSION} && \ ./configure \ --enable-gpl \ --enable-nonfree \ --enable-libx264 \ --enable-libx265 \ --enable-libvpx \ --enable-libfdk-aac \ --enable-libmp3lame \ --enable-libopus \ --enable-cuda-nvcc \ --enable-cuvid \ --enable-nvenc \ --enable-nvdec \ --enable-cuda-llvm \ --enable-libnpp \ --extra-cflags=-I/usr/local/cuda/include \ --extra-ldflags=-L/usr/local/cuda/lib64 \ --nvccflags="-gencode arch=compute_50,code=sm_50 -gencode arch=compute_52,code=sm_52 -gencode arch=compute_60,code=sm_60 -gencode arch=compute_61,code=sm_61 -gencode arch=compute_70,code=sm_70 -gencode arch=compute_75,code=sm_75 -gencode arch=compute_80,code=sm_80 -gencode arch=compute_86,code=sm_86 -gencode arch=compute_89,code=sm_89 -gencode arch=compute_90,code=sm_90" && \ make -j$(nproc) && \ make install && \ ldconfig && \ cd / && rm -rf /tmp/* # Build OpenCV from source with custom FFmpeg and full CUDA support ENV OPENCV_VERSION=4.8.1 RUN cd /tmp && \ wget -O opencv.zip https://github.com/opencv/opencv/archive/${OPENCV_VERSION}.zip && \ wget -O opencv_contrib.zip https://github.com/opencv/opencv_contrib/archive/${OPENCV_VERSION}.zip && \ unzip opencv.zip && \ unzip opencv_contrib.zip && \ cd opencv-${OPENCV_VERSION} && \ mkdir build && cd build && \ PKG_CONFIG_PATH=/usr/local/lib/pkgconfig:$PKG_CONFIG_PATH \ cmake -D CMAKE_BUILD_TYPE=RELEASE \ -D CMAKE_INSTALL_PREFIX=/usr/local \ -D WITH_CUDA=ON \ -D WITH_CUDNN=ON \ -D OPENCV_DNN_CUDA=ON \ -D ENABLE_FAST_MATH=ON \ -D CUDA_FAST_MATH=ON \ -D WITH_CUBLAS=ON \ -D WITH_NVCUVID=ON \ -D WITH_CUVID=ON \ -D BUILD_opencv_cudacodec=ON \ -D WITH_FFMPEG=ON \ -D WITH_GSTREAMER=ON \ -D WITH_LIBV4L=ON \ -D BUILD_opencv_python3=ON \ -D OPENCV_GENERATE_PKGCONFIG=ON \ -D OPENCV_ENABLE_NONFREE=ON \ -D OPENCV_EXTRA_MODULES_PATH=/tmp/opencv_contrib-${OPENCV_VERSION}/modules \ -D PYTHON3_EXECUTABLE=$(which python3) \ -D PYTHON_INCLUDE_DIR=$(python3 -c "from distutils.sysconfig import get_python_inc; print(get_python_inc())") \ -D PYTHON_LIBRARY=$(python3 -c "import distutils.sysconfig as sysconfig; print(sysconfig.get_config_var('LIBDIR'))") \ -D BUILD_EXAMPLES=OFF \ -D BUILD_TESTS=OFF \ -D BUILD_PERF_TESTS=OFF \ .. && \ make -j$(nproc) && \ make install && \ ldconfig && \ cd / && rm -rf /tmp/* # Set environment variables for maximum hardware acceleration ENV LD_LIBRARY_PATH="/usr/local/cuda/lib64:/usr/local/lib:${LD_LIBRARY_PATH}" ENV PKG_CONFIG_PATH="/usr/local/lib/pkgconfig:${PKG_CONFIG_PATH}" ENV PYTHONPATH="/usr/local/lib/python3.10/dist-packages:${PYTHONPATH}" ENV GST_PLUGIN_PATH="/usr/lib/x86_64-linux-gnu/gstreamer-1.0" # Optimized environment variables for hardware acceleration ENV OPENCV_FFMPEG_CAPTURE_OPTIONS="rtsp_transport;tcp|hwaccel;cuda|hwaccel_device;0|video_codec;h264_cuvid|hwaccel_output_format;cuda" ENV OPENCV_FFMPEG_WRITER_OPTIONS="video_codec;h264_nvenc|preset;fast|tune;zerolatency|gpu;0" ENV CUDA_VISIBLE_DEVICES=0 ENV NVIDIA_VISIBLE_DEVICES=all ENV NVIDIA_DRIVER_CAPABILITIES=compute,video,utility # Copy and install base requirements (exclude opencv-python since we built from source) COPY requirements.base.txt . RUN grep -v opencv-python requirements.base.txt > requirements.tmp && \ mv requirements.tmp requirements.base.txt && \ pip install --no-cache-dir -r requirements.base.txt # Verify complete hardware acceleration setup RUN echo "=== Hardware Acceleration Verification ===" && \ echo "FFmpeg Hardware Accelerators:" && \ ffmpeg -hide_banner -hwaccels 2>/dev/null | head -10 && \ echo "FFmpeg NVIDIA Decoders:" && \ ffmpeg -hide_banner -decoders 2>/dev/null | grep -E "(cuvid|nvdec)" | head -5 && \ echo "FFmpeg NVIDIA Encoders:" && \ ffmpeg -hide_banner -encoders 2>/dev/null | grep nvenc | head -5 && \ echo "OpenCV Configuration:" && \ python3 -c "import cv2; print('OpenCV version:', cv2.__version__); print('CUDA devices:', cv2.cuda.getCudaEnabledDeviceCount()); build_info = cv2.getBuildInformation(); print('CUDA support:', 'CUDA' in build_info); print('CUVID support:', 'CUVID' in build_info); print('FFmpeg support:', 'FFMPEG' in build_info); print('GStreamer support:', 'GStreamer' in build_info)" && \ echo "GStreamer NVIDIA Plugins:" && \ gst-inspect-1.0 2>/dev/null | grep -E "(nvv4l2|nvvideo)" | head -5 || echo "GStreamer NVIDIA plugins not detected" && \ echo "=== Verification Complete ===" # Set working directory WORKDIR /app # Create images directory for bind mount RUN mkdir -p /app/images && \ chmod 755 /app/images # This base image will be reused for all worker builds CMD ["python3", "-m", "fastapi", "run", "--host", "0.0.0.0", "--port", "8000"]