mirror of
https://github.com/ultralytics/ultralytics
synced 2026-04-21 14:07:18 +00:00
1ce3b0c4e6
Signed-off-by: Glenn Jocher <glenn.jocher@ultralytics.com> Co-authored-by: UltralyticsAssistant <web@ultralytics.com> Co-authored-by: Claude Sonnet 4.6 <noreply@anthropic.com>
60 lines
2.9 KiB
Docker
60 lines
2.9 KiB
Docker
# Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
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# Builds ultralytics/ultralytics:latest image on DockerHub https://hub.docker.com/r/ultralytics/ultralytics
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# Image is CUDA-optimized for YOLO single/multi-GPU training and inference
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# Start FROM PyTorch image https://hub.docker.com/r/pytorch/pytorch or nvcr.io/nvidia/pytorch:25.02-py3
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FROM pytorch/pytorch:2.10.0-cuda12.8-cudnn9-runtime
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# Set environment variables
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# Avoid DDP error "MKL_THREADING_LAYER=INTEL is incompatible with libgomp.so.1 library"
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# Suppress TensorFlow cuDNN, cuBLAS, and cuFFT Registration Warnings and PyTorch NNPACK warnings
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ENV PYTHONUNBUFFERED=1 \
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PYTHONDONTWRITEBYTECODE=1 \
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PIP_NO_CACHE_DIR=1 \
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PIP_BREAK_SYSTEM_PACKAGES=1 \
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UV_BREAK_SYSTEM_PACKAGES=1 \
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MKL_THREADING_LAYER=GNU \
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OMP_NUM_THREADS=1 \
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TF_CPP_MIN_LOG_LEVEL=3 \
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TORCH_CPP_LOG_LEVEL=ERROR
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# Downloads to user config dir
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ADD https://github.com/ultralytics/assets/releases/download/v0.0.0/Arial.ttf \
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https://github.com/ultralytics/assets/releases/download/v0.0.0/Arial.Unicode.ttf \
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/root/.config/Ultralytics/
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# Install linux packages
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# gnupg required for Edge TPU install
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# libsm6 required by libqxcb to create QT-based windows for visualization; set 'QT_DEBUG_PLUGINS=1' to test in docker
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RUN apt-get update && \
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apt-get install -y --no-install-recommends \
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gcc git zip unzip wget curl htop libgl1 libglib2.0-0 gnupg libsm6 && \
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apt-get clean && \
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rm -rf /var/lib/apt/lists/*
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# Create working directory
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WORKDIR /ultralytics
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# Copy contents and configure git
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COPY . .
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RUN sed -i '/^\[http "https:\/\/github\.com\/"\]/,+1d' .git/config && \
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sed -i'' -e 's/"opencv-python/"opencv-python-headless/' pyproject.toml
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ADD https://github.com/ultralytics/assets/releases/download/v8.4.0/yolo26n.pt .
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# Install pip packages (uv already installed in base image)
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RUN uv pip install --system -e "." albumentations faster-coco-eval nvidia-ml-py && \
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# Remove extra build files \
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rm -rf tmp /root/.config/Ultralytics/persistent_cache.json
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# Usage --------------------------------------------------------------------------------------------------------------
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# Production builds: https://github.com/ultralytics/ultralytics/blob/main/.github/workflows/docker.yml
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# Example (build): t=ultralytics/ultralytics:latest && docker build -f docker/Dockerfile -t $t .
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# Example (push): docker push $t
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# Example (pull): t=ultralytics/ultralytics:latest && docker pull $t
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# Example (run-gpu): docker run -it --ipc=host --runtime=nvidia --gpus all $t
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# Example (run-gpu-subset): docker run -it --ipc=host --runtime=nvidia --gpus "device=2,3" $t
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# Note: device=2,3 maps to CUDA 0,1 inside the container.
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# Example (run-with-volume): docker run -it --ipc=host --runtime=nvidia --gpus all -v "$PWD/shared/datasets:/datasets" $t
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# Example (tag-release): t=ultralytics/ultralytics:latest tnew=ultralytics/ultralytics:vX.Y && docker tag $t $tnew && docker push $tnew
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