943172e8e0
- Remove existing manifests before creating new ones - Add architecture annotations for proper platform detection - Ensures Docker pulls correct architecture automatically
Generic Docker Images
This repository contains reusable Docker base images for various purposes.
Available Images
debian-curl
Debian with curl installed.
accelerated_base
A comprehensive base image with hardware acceleration support for ML/CV applications.
Features:
- Ubuntu 22.04 LTS base
- Python 3.11 with pip
- Intel QuickSync / VAAPI support for hardware video acceleration
- NVIDIA CUDA support (when NVIDIA Container Toolkit is available)
- FFmpeg with hardware acceleration codecs
- OpenCV with Python bindings
- PyTorch (CPU by default, GPU when NVIDIA runtime is available)
- Common ML/CV Python packages (numpy, scipy, pandas, matplotlib, etc.)
- Video and image codec libraries
- Non-root user setup for security
Usage:
FROM gitea.jde.nz/public/accelerated_base:latest
# Your application-specific setup
COPY your_app.py /app/
CMD ["python", "/app/your_app.py"]
Hardware Acceleration:
- Intel QuickSync: Automatically available when
/dev/driis mounted - NVIDIA GPU: Automatically available when using
--runtime=nvidiaor--gpus all
Environment Variables:
LIBVA_DRIVER_NAME=iHD- Intel Media Driver for VAAPIFFMPEG_HWACCEL_PRIORITY="vaapi,cuda,auto"- Hardware acceleration preferenceNVIDIA_VISIBLE_DEVICES=all- NVIDIA GPU visibilityNVIDIA_DRIVER_CAPABILITIES=compute,utility,video- NVIDIA capabilities
Size: ~2.5GB (includes Python, ML libraries, and video codecs)
Building
Images are automatically built and published when pushed to this repository.
Registry
Images are available at:
gitea.jde.nz/public/<image_name>:latestgitea.jde.nz/public/<image_name>:latest-<arch>(architecture-specific)