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- Ubuntu 22.04 base with Python 3.11 - Intel Media Driver and VAAPI for QuickSync hardware acceleration - NVIDIA CUDA support via container toolkit - FFmpeg with hardware codec support - OpenCV, PyTorch, and common ML/CV packages - Non-root user setup for security - Provides comprehensive base for ML/CV applications with hardware acceleration
56 lines
1.7 KiB
Markdown
56 lines
1.7 KiB
Markdown
# Generic Docker Images
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This repository contains reusable Docker base images for various purposes.
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## Available Images
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### debian-curl
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Debian with curl installed.
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### accelerated_base
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A comprehensive base image with hardware acceleration support for ML/CV applications.
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**Features:**
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- Ubuntu 22.04 LTS base
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- Python 3.11 with pip
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- Intel QuickSync / VAAPI support for hardware video acceleration
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- NVIDIA CUDA support (when NVIDIA Container Toolkit is available)
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- FFmpeg with hardware acceleration codecs
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- OpenCV with Python bindings
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- PyTorch (CPU by default, GPU when NVIDIA runtime is available)
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- Common ML/CV Python packages (numpy, scipy, pandas, matplotlib, etc.)
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- Video and image codec libraries
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- Non-root user setup for security
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**Usage:**
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```dockerfile
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FROM gitea.jde.nz/public/accelerated_base:latest
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# Your application-specific setup
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COPY your_app.py /app/
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CMD ["python", "/app/your_app.py"]
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```
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**Hardware Acceleration:**
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- Intel QuickSync: Automatically available when `/dev/dri` is mounted
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- NVIDIA GPU: Automatically available when using `--runtime=nvidia` or `--gpus all`
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**Environment Variables:**
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- `LIBVA_DRIVER_NAME=iHD` - Intel Media Driver for VAAPI
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- `FFMPEG_HWACCEL_PRIORITY="vaapi,cuda,auto"` - Hardware acceleration preference
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- `NVIDIA_VISIBLE_DEVICES=all` - NVIDIA GPU visibility
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- `NVIDIA_DRIVER_CAPABILITIES=compute,utility,video` - NVIDIA capabilities
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**Size:** ~2.5GB (includes Python, ML libraries, and video codecs)
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## Building
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Images are automatically built and published when pushed to this repository.
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## Registry
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Images are available at:
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- `gitea.jde.nz/public/<image_name>:latest`
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- `gitea.jde.nz/public/<image_name>:latest-<arch>` (architecture-specific) |