Dockerfile.ultralytics

# Image is CUDA-optimized for YOLOv8 single/multi-GPU training and inference

# Start FROM PyTorch image https://hub.docker.com/r/pytorch/pytorch or nvcr.io/nvidia/pytorch:23.03-py3
FROM pytorch/pytorch:2.2.2-cuda12.1-cudnn8-runtime
RUN pip install --no-cache nvidia-tensorrt --index-url https://pypi.ngc.nvidia.com

# ENV DEBIAN_FRONTEND=noninteractive

# Downloads to user config dir
ADD assets/Arial.ttf assets/Arial.Unicode.ttf /root/.config/Ultralytics/

RUN /bin/bash -c 'conda init bash'

# 将原镜像地址替换为腾讯云镜像地址
RUN sed -i 's/archive.ubuntu.com/mirrors.cloud.tencent.com/g' /etc/apt/sources.list
RUN sed -i 's/security.ubuntu.com/mirrors.cloud.tencent.com/g' /etc/apt/sources.list
RUN apt update && \
    apt install --no-install-recommends -y build-essential \
    gcc git zip curl htop libgl1 libglib2.0-0 libpython3-dev gnupg g++ \
    libusb-1.0-0 && apt clean && \
    apt autoremove && \
    rm -rf /var/lib/apt/lists/*

RUN apt upgrade --no-install-recommends -y openssl tar

# RUN mkdir -p /home/user/ultralytics
WORKDIR /home/user/ultralytics

ADD requirements.txt /home/user/ultralytics

# 换源并更新pip
RUN pip config set global.index-url https://pypi.mirrors.ustc.edu.cn/simple/
RUN pip install --upgrade pip
# RUN pip install --no-cache -e ".[export]" albumentations comet pycocotools
RUN pip install --no-cache -r requirements.txt


# Usage Examples -------------------------------------------------------------------------------------------------------

# build
# docker build --pull --rm -f "Dockerfile.ultralytics" -t ultralytics:2.2.2-cuda12.1-cudnn8-runtime "."

# run
# docker run --rm --gpus all -it -v E:\Projects\weights\yolo\v8\detect\coco:/home/user/ultralytics -p : --name yolo ultralytics:2.2.2-cuda12.1-cudnn8-runtime