docker.io/heartexlabs/label-studio-ml-backend:yolo-master linux/amd64

Docker拉取命令

docker pull swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/heartexlabs/label-studio-ml-backend:yolo-master
docker tag  swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/heartexlabs/label-studio-ml-backend:yolo-master  docker.io/heartexlabs/label-studio-ml-backend:yolo-master

Containerd拉取命令

ctr images pull swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/heartexlabs/label-studio-ml-backend:yolo-master
ctr images tag  swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/heartexlabs/label-studio-ml-backend:yolo-master  docker.io/heartexlabs/label-studio-ml-backend:yolo-master

Shell快速替换命令

sed -i 's#heartexlabs/label-studio-ml-backend:yolo-master#swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/heartexlabs/label-studio-ml-backend:yolo-master#' deployment.yaml

Ansible快速分发-Docker

#ansible k8s -m shell -a 'docker pull swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/heartexlabs/label-studio-ml-backend:yolo-master && docker tag  swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/heartexlabs/label-studio-ml-backend:yolo-master  docker.io/heartexlabs/label-studio-ml-backend:yolo-master'

Ansible快速分发-Containerd

#ansible k8s -m shell -a 'ctr images pull swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/heartexlabs/label-studio-ml-backend:yolo-master && ctr images tag  swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/heartexlabs/label-studio-ml-backend:yolo-master  docker.io/heartexlabs/label-studio-ml-backend:yolo-master'

镜像构建历史

# 2025-09-08 19:27:20  0.00B 设置默认要执行的命令
CMD ["/app/start.sh"]
                        
# 2025-09-08 19:27:20  0.00B 设置环境变量 PYTHONPATH
ENV PYTHONPATH=/app
                        
# 2025-09-08 19:27:20  72.78MB 执行命令并创建新的镜像层
RUN |2 DEBIAN_FRONTEND=noninteractive TEST_ENV= /bin/sh -c /bin/sh -c 'if [ ! -f /app/models/yolov8m.pt ]; then     yolo predict model=/app/models/yolov8m.pt source=/app/tests/car.jpg     && yolo predict model=/app/models/yolov8n.pt source=/app/tests/car.jpg     && yolo predict model=/app/models/yolov8n-cls.pt source=/app/tests/car.jpg     && yolo predict model=/app/models/yolov8n-seg.pt source=/app/tests/car.jpg;     fi' # buildkit
                        
# 2025-09-08 19:27:11  1.02MB 复制新文件或目录到容器中
COPY . ./ # buildkit
                        
# 2025-09-08 19:27:11  0.00B 设置工作目录为/app
WORKDIR /app
                        
# 2025-09-08 19:27:11  0.00B 执行命令并创建新的镜像层
RUN |2 DEBIAN_FRONTEND=noninteractive TEST_ENV= /bin/sh -c if [ "$TEST_ENV" = "true" ]; then       pip3 install -r requirements-test.txt;     fi # buildkit
                        
# 2025-09-08 19:27:11  29.00B 复制新文件或目录到容器中
COPY requirements-test.txt . # buildkit
                        
# 2025-09-08 19:27:10  590.58MB 执行命令并创建新的镜像层
RUN |2 DEBIAN_FRONTEND=noninteractive TEST_ENV= /bin/sh -c pip3 install -r requirements.txt # buildkit
                        
# 2025-09-08 19:26:55  66.00B 复制新文件或目录到容器中
COPY requirements.txt . # buildkit
                        
# 2025-09-08 19:26:54  382.65MB 执行命令并创建新的镜像层
RUN |2 DEBIAN_FRONTEND=noninteractive TEST_ENV= /bin/sh -c pip install -r requirements-base.txt # buildkit
                        
# 2025-09-08 19:26:32  180.00B 复制新文件或目录到容器中
COPY requirements-base.txt . # buildkit
                        
# 2025-09-08 19:26:32  0.00B 设置环境变量 CUDA_HOME TORCH_CUDA_ARCH_LIST
ENV CUDA_HOME=/opt/conda TORCH_CUDA_ARCH_LIST=6.0;6.1;7.0;7.5;8.0;8.6+PTX;8.9;9.0
                        
# 2025-09-08 19:26:32  0.00B 设置环境变量 PYTHONUNBUFFERED PYTHONDONTWRITEBYTECODE PIP_CACHE_DIR PORT WORKERS THREADS CUDA_HOME
ENV PYTHONUNBUFFERED=1 PYTHONDONTWRITEBYTECODE=1 PIP_CACHE_DIR=/.cache PORT=9090 WORKERS=2 THREADS=4 CUDA_HOME=/usr/local/cuda
                        
# 2025-09-08 19:26:32  760.57MB 执行命令并创建新的镜像层
RUN |2 DEBIAN_FRONTEND=noninteractive TEST_ENV= /bin/sh -c apt-get -y update     && apt-get install -y git     && apt-get install -y wget     && apt-get install -y curl     && apt-get install -y g++ freeglut3-dev build-essential libx11-dev     libxmu-dev libxi-dev libglu1-mesa libglu1-mesa-dev libfreeimage-dev     && apt-get -y install ffmpeg libsm6 libxext6 libffi-dev python3-dev python3-pip gcc # buildkit
                        
# 2025-09-08 19:25:45  1.41GB 执行命令并创建新的镜像层
RUN |2 DEBIAN_FRONTEND=noninteractive TEST_ENV= /bin/sh -c conda update conda -y # buildkit
                        
# 2025-09-08 19:22:39  0.00B 设置工作目录为/app
WORKDIR /app
                        
# 2025-09-08 19:22:39  0.00B 定义构建参数
ARG TEST_ENV
                        
# 2025-09-08 19:22:39  0.00B 定义构建参数
ARG DEBIAN_FRONTEND=noninteractive
                        
# 2023-12-15 06:53:46  0.00B 设置工作目录为/workspace
WORKDIR /workspace
                        
# 2023-12-15 06:53:46  0.00B 设置环境变量 PYTORCH_VERSION
ENV PYTORCH_VERSION=2.1.2
                        
# 2023-12-15 06:53:46  0.00B 设置环境变量 LD_LIBRARY_PATH
ENV LD_LIBRARY_PATH=/usr/local/nvidia/lib:/usr/local/nvidia/lib64
                        
# 2023-12-15 06:53:46  0.00B 设置环境变量 NVIDIA_DRIVER_CAPABILITIES
ENV NVIDIA_DRIVER_CAPABILITIES=compute,utility
                        
# 2023-12-15 06:53:46  0.00B 设置环境变量 NVIDIA_VISIBLE_DEVICES
ENV NVIDIA_VISIBLE_DEVICES=all
                        
# 2023-12-15 06:53:46  0.00B 设置环境变量 PATH
ENV PATH=/opt/conda/bin:/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin
                        
# 2023-12-15 06:53:46  0.00B 执行命令并创建新的镜像层
RUN |4 PYTORCH_VERSION=2.1.2 TRITON_VERSION=2.1.0+e6216047b8 TARGETPLATFORM=linux/amd64 CUDA_VERSION=12.1.1 /bin/sh -c if test -n "${TRITON_VERSION}" -a "${TARGETPLATFORM}" != "linux/arm64"; then         DEBIAN_FRONTEND=noninteractive apt install -y --no-install-recommends gcc;         rm -rf /var/lib/apt/lists/*;     fi # buildkit
                        
# 2023-12-15 06:53:44  7.10GB 复制新文件或目录到容器中
COPY /opt/conda /opt/conda # buildkit
                        
# 2023-12-15 06:46:03  46.87MB 执行命令并创建新的镜像层
RUN |4 PYTORCH_VERSION=2.1.2 TRITON_VERSION=2.1.0+e6216047b8 TARGETPLATFORM=linux/amd64 CUDA_VERSION=12.1.1 /bin/sh -c apt-get update && DEBIAN_FRONTEND=noninteractive apt-get install -y --no-install-recommends         ca-certificates         libjpeg-dev         libpng-dev         && rm -rf /var/lib/apt/lists/* # buildkit
                        
# 2023-12-15 06:46:03  0.00B 添加元数据标签
LABEL com.nvidia.volumes.needed=nvidia_driver
                        
# 2023-12-15 06:46:03  0.00B 定义构建参数
ARG CUDA_VERSION
                        
# 2023-12-15 06:46:03  0.00B 定义构建参数
ARG TARGETPLATFORM
                        
# 2023-12-15 06:46:03  0.00B 定义构建参数
ARG TRITON_VERSION
                        
# 2023-12-15 06:46:03  0.00B 定义构建参数
ARG PYTORCH_VERSION
                        
# 2023-11-28 13:17:41  0.00B 
/bin/sh -c #(nop)  CMD ["/bin/bash"]
                        
# 2023-11-28 13:17:41  72.81MB 
/bin/sh -c #(nop) ADD file:9169bb1d6ef21313aed17e924538fee03d858460ae6b05e01968457dfc043bd7 in / 
                        
# 2023-11-28 13:17:39  0.00B 
/bin/sh -c #(nop)  LABEL org.opencontainers.image.version=20.04
                        
# 2023-11-28 13:17:39  0.00B 
/bin/sh -c #(nop)  LABEL org.opencontainers.image.ref.name=ubuntu
                        
# 2023-11-28 13:17:39  0.00B 
/bin/sh -c #(nop)  ARG LAUNCHPAD_BUILD_ARCH
                        
# 2023-11-28 13:17:39  0.00B 
/bin/sh -c #(nop)  ARG RELEASE
                        
                    

镜像信息

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    "DockerVersion": "",
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        "Hostname": "",
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        "AttachStdin": false,
        "AttachStdout": false,
        "AttachStderr": false,
        "Tty": false,
        "OpenStdin": false,
        "StdinOnce": false,
        "Env": [
            "PATH=/opt/conda/bin:/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin",
            "NVIDIA_VISIBLE_DEVICES=all",
            "NVIDIA_DRIVER_CAPABILITIES=compute,utility",
            "LD_LIBRARY_PATH=/usr/local/nvidia/lib:/usr/local/nvidia/lib64",
            "PYTORCH_VERSION=2.1.2",
            "PYTHONUNBUFFERED=1",
            "PYTHONDONTWRITEBYTECODE=1",
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