# 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:**
```dockerfile
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/dri` is mounted
- NVIDIA GPU: Automatically available when using `--runtime=nvidia` or `--gpus all`

**Environment Variables:**
- `LIBVA_DRIVER_NAME=iHD` - Intel Media Driver for VAAPI
- `FFMPEG_HWACCEL_PRIORITY="vaapi,cuda,auto"` - Hardware acceleration preference
- `NVIDIA_VISIBLE_DEVICES=all` - NVIDIA GPU visibility
- `NVIDIA_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>:latest`
- `gitea.jde.nz/public/<image_name>:latest-<arch>` (architecture-specific)