docker.io/roboflow/roboflow-inference-server-gpu:0.62.4 linux/amd64

docker.io/roboflow/roboflow-inference-server-gpu:0.62.4 - 国内下载镜像源浏览次数:13

源镜像	docker.io/roboflow/roboflow-inference-server-gpu:0.62.4
国内镜像	swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/roboflow/roboflow-inference-server-gpu:0.62.4
镜像ID	sha256:fb7663b0759faa39ff8f00ffd0f77e67d69b09d1b9f470c8f068b221926042b6
镜像TAG	0.62.4
大小	15.00GB
镜像源	docker.io
项目信息	Docker-Hub主页 🚀项目TAG 🚀
CMD
启动入口	/bin/sh -c uvicorn gpu_http:app --workers $NUM_WORKERS --host $HOST --port $PORT
工作目录	/app/
OS/平台	linux/amd64
浏览量	13 次
贡献者	18********6@163.com
镜像创建	2025-12-09T22:16:08.646199305Z
同步时间	2025-12-11 00:40
更新时间	2025-12-11 16:25

环境变量

PATH=/usr/local/nvidia/bin:/usr/local/cuda/bin:/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin NVARCH=x86_64 NVIDIA_REQUIRE_CUDA=cuda>=12.4 brand=tesla,driver>=470,driver<471 brand=unknown,driver>=470,driver<471 brand=nvidia,driver>=470,driver<471 brand=nvidiartx,driver>=470,driver<471 brand=geforce,driver>=470,driver<471 brand=geforcertx,driver>=470,driver<471 brand=quadro,driver>=470,driver<471 brand=quadrortx,driver>=470,driver<471 brand=titan,driver>=470,driver<471 brand=titanrtx,driver>=470,driver<471 brand=tesla,driver>=525,driver<526 brand=unknown,driver>=525,driver<526 brand=nvidia,driver>=525,driver<526 brand=nvidiartx,driver>=525,driver<526 brand=geforce,driver>=525,driver<526 brand=geforcertx,driver>=525,driver<526 brand=quadro,driver>=525,driver<526 brand=quadrortx,driver>=525,driver<526 brand=titan,driver>=525,driver<526 brand=titanrtx,driver>=525,driver<526 brand=tesla,driver>=535,driver<536 brand=unknown,driver>=535,driver<536 brand=nvidia,driver>=535,driver<536 brand=nvidiartx,driver>=535,driver<536 brand=geforce,driver>=535,driver<536 brand=geforcertx,driver>=535,driver<536 brand=quadro,driver>=535,driver<536 brand=quadrortx,driver>=535,driver<536 brand=titan,driver>=535,driver<536 brand=titanrtx,driver>=535,driver<536 NV_CUDA_CUDART_VERSION=12.4.127-1 NV_CUDA_COMPAT_PACKAGE=cuda-compat-12-4 CUDA_VERSION=12.4.1 LD_LIBRARY_PATH=/usr/local/nvidia/lib:/usr/local/nvidia/lib64 NVIDIA_VISIBLE_DEVICES=all NVIDIA_DRIVER_CAPABILITIES=compute,utility NV_CUDA_LIB_VERSION=12.4.1-1 NV_NVTX_VERSION=12.4.127-1 NV_LIBNPP_VERSION=12.2.5.30-1 NV_LIBNPP_PACKAGE=libnpp-12-4=12.2.5.30-1 NV_LIBCUSPARSE_VERSION=12.3.1.170-1 NV_LIBCUBLAS_PACKAGE_NAME=libcublas-12-4 NV_LIBCUBLAS_VERSION=12.4.5.8-1 NV_LIBCUBLAS_PACKAGE=libcublas-12-4=12.4.5.8-1 NV_LIBNCCL_PACKAGE_NAME=libnccl2 NV_LIBNCCL_PACKAGE_VERSION=2.21.5-1 NCCL_VERSION=2.21.5-1 NV_LIBNCCL_PACKAGE=libnccl2=2.21.5-1+cuda12.4 NVIDIA_PRODUCT_NAME=CUDA NV_CUDNN_VERSION=9.1.0.70-1 NV_CUDNN_PACKAGE_NAME=libcudnn9-cuda-12 NV_CUDNN_PACKAGE=libcudnn9-cuda-12=9.1.0.70-1 VERSION_CHECK_MODE=continuous PROJECT=roboflow-platform NUM_WORKERS=1 HOST=0.0.0.0 PORT=9001 WORKFLOWS_STEP_EXECUTION_MODE=local WORKFLOWS_MAX_CONCURRENT_STEPS=4 API_LOGGING_ENABLED=True LMM_ENABLED=True CORE_MODEL_SAM2_ENABLED=True CORE_MODEL_SAM3_ENABLED=True CORE_MODEL_OWLV2_ENABLED=True ENABLE_STREAM_API=True ENABLE_PROMETHEUS=True STREAM_API_PRELOADED_PROCESSES=2

镜像标签

9.1.0.70-1: com.nvidia.cudnn.version NVIDIA CORPORATION <cudatools@nvidia.com>: maintainer ubuntu: org.opencontainers.image.ref.name 22.04: org.opencontainers.image.version

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无权限下载?点我修复生成Docker Run命令生成Kubernetes YAML资源

Docker拉取命令

docker pull swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/roboflow/roboflow-inference-server-gpu:0.62.4
docker tag  swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/roboflow/roboflow-inference-server-gpu:0.62.4  docker.io/roboflow/roboflow-inference-server-gpu:0.62.4

Containerd拉取命令

ctr images pull swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/roboflow/roboflow-inference-server-gpu:0.62.4
ctr images tag  swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/roboflow/roboflow-inference-server-gpu:0.62.4  docker.io/roboflow/roboflow-inference-server-gpu:0.62.4

Shell快速替换命令

sed -i 's#roboflow/roboflow-inference-server-gpu:0.62.4#swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/roboflow/roboflow-inference-server-gpu:0.62.4#' 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/roboflow/roboflow-inference-server-gpu:0.62.4 && docker tag  swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/roboflow/roboflow-inference-server-gpu:0.62.4  docker.io/roboflow/roboflow-inference-server-gpu:0.62.4'

Ansible快速分发-Containerd

#ansible k8s -m shell -a 'ctr images pull swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/roboflow/roboflow-inference-server-gpu:0.62.4 && ctr images tag  swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/roboflow/roboflow-inference-server-gpu:0.62.4  docker.io/roboflow/roboflow-inference-server-gpu:0.62.4'

镜像构建历史


# 2025-12-10 06:16:08  0.00B 配置容器启动时运行的命令
ENTRYPOINT ["/bin/sh" "-c" "uvicorn gpu_http:app --workers $NUM_WORKERS --host $HOST --port $PORT"]
                        
# 2025-12-10 06:16:08  0.00B 设置环境变量 STREAM_API_PRELOADED_PROCESSES
ENV STREAM_API_PRELOADED_PROCESSES=2
                        
# 2025-12-10 06:16:08  0.00B 设置环境变量 ENABLE_PROMETHEUS
ENV ENABLE_PROMETHEUS=True
                        
# 2025-12-10 06:16:08  0.00B 设置环境变量 ENABLE_STREAM_API
ENV ENABLE_STREAM_API=True
                        
# 2025-12-10 06:16:08  0.00B 设置环境变量 CORE_MODEL_OWLV2_ENABLED
ENV CORE_MODEL_OWLV2_ENABLED=True
                        
# 2025-12-10 06:16:08  0.00B 设置环境变量 CORE_MODEL_SAM3_ENABLED
ENV CORE_MODEL_SAM3_ENABLED=True
                        
# 2025-12-10 06:16:08  0.00B 设置环境变量 CORE_MODEL_SAM2_ENABLED
ENV CORE_MODEL_SAM2_ENABLED=True
                        
# 2025-12-10 06:16:08  0.00B 设置环境变量 LMM_ENABLED
ENV LMM_ENABLED=True
                        
# 2025-12-10 06:16:08  0.00B 设置环境变量 API_LOGGING_ENABLED
ENV API_LOGGING_ENABLED=True
                        
# 2025-12-10 06:16:08  0.00B 设置环境变量 WORKFLOWS_MAX_CONCURRENT_STEPS
ENV WORKFLOWS_MAX_CONCURRENT_STEPS=4
                        
# 2025-12-10 06:16:08  0.00B 设置环境变量 WORKFLOWS_STEP_EXECUTION_MODE
ENV WORKFLOWS_STEP_EXECUTION_MODE=local
                        
# 2025-12-10 06:16:08  0.00B 设置环境变量 PORT
ENV PORT=9001
                        
# 2025-12-10 06:16:08  0.00B 设置环境变量 HOST
ENV HOST=0.0.0.0
                        
# 2025-12-10 06:16:08  0.00B 设置环境变量 NUM_WORKERS
ENV NUM_WORKERS=1
                        
# 2025-12-10 06:16:08  0.00B 设置环境变量 PROJECT
ENV PROJECT=roboflow-platform
                        
# 2025-12-10 06:16:08  0.00B 设置环境变量 VERSION_CHECK_MODE
ENV VERSION_CHECK_MODE=continuous
                        
# 2025-12-10 06:16:08  1.68KB 复制新文件或目录到容器中
COPY docker/config/gpu_http.py gpu_http.py # buildkit
                        
# 2025-12-10 06:16:08  7.91MB 复制新文件或目录到容器中
COPY inference inference # buildkit
                        
# 2025-12-10 06:16:08  0.00B 设置工作目录为/app/
WORKDIR /app/
                        
# 2025-12-10 06:16:08  12.03MB 复制新文件或目录到容器中
COPY examples/notebooks . # buildkit
                        
# 2025-12-10 06:16:08  0.00B 设置工作目录为/notebooks
WORKDIR /notebooks
                        
# 2025-12-10 06:16:07  18.47MB 执行命令并创建新的镜像层
RUN /bin/sh -c pip3 install --no-cache-dir dist/inference_cli*.whl dist/inference_core*.whl dist/inference_gpu*.whl dist/inference_sdk*.whl "setuptools<=75.5.0" # buildkit
                        
# 2025-12-10 06:16:01  28.80MB 执行命令并创建新的镜像层
RUN /bin/sh -c /bin/make create_wheels_for_gpu_notebook # buildkit
                        
# 2025-12-10 06:15:52  16.00B 执行命令并创建新的镜像层
RUN /bin/sh -c ln -s /usr/bin/python3 /usr/bin/python # buildkit
                        
# 2025-12-10 06:15:51  135.94MB 复制新文件或目录到容器中
COPY . . # buildkit
                        
# 2025-12-09 16:53:48  0.00B 设置工作目录为/build
WORKDIR /build
                        
# 2025-12-09 16:53:48  2.46GB 执行命令并创建新的镜像层
RUN /bin/sh -c set -eux;     rm -rf /var/lib/apt/lists/*; apt-get clean;     dpkg -i /tmp/cuda-keyring.deb || true;     rm -f /tmp/cuda-keyring.deb;     apt-get update -y;     DEBIAN_FRONTEND=noninteractive apt-get install -y         libxext6         libopencv-dev         uvicorn         python3-pip         git         libgdal-dev         libvips-dev         wget         rustc         cargo;     rm -rf /var/lib/apt/lists/* # buildkit
                        
# 2025-12-09 16:52:00  4.33KB 复制文件或目录到容器中
ADD https://developer.download.nvidia.com/compute/cuda/repos/ubuntu2204/x86_64/cuda-keyring_1.1-1_all.deb /tmp/cuda-keyring.deb # buildkit
                        
# 2025-12-09 16:52:00  55.52MB 复制新文件或目录到容器中
COPY /usr/local/bin /usr/local/bin # buildkit
                        
# 2025-12-09 16:51:59  8.96GB 复制新文件或目录到容器中
COPY /usr/local/lib/python3.10 /usr/local/lib/python3.10 # buildkit
                        
# 2025-11-24 19:22:54  0.00B 设置工作目录为/app
WORKDIR /app
                        
# 2024-04-23 08:07:03  1.02GB 执行命令并创建新的镜像层
RUN |1 TARGETARCH=amd64 /bin/sh -c apt-get update && apt-get install -y --no-install-recommends     ${NV_CUDNN_PACKAGE}     && apt-mark hold ${NV_CUDNN_PACKAGE_NAME}     && rm -rf /var/lib/apt/lists/* # buildkit
                        
# 2024-04-23 08:07:03  0.00B 添加元数据标签
LABEL com.nvidia.cudnn.version=9.1.0.70-1
                        
# 2024-04-23 08:07:03  0.00B 添加元数据标签
LABEL maintainer=NVIDIA CORPORATION <cudatools@nvidia.com>
                        
# 2024-04-23 08:07:03  0.00B 定义构建参数
ARG TARGETARCH
                        
# 2024-04-23 08:07:03  0.00B 设置环境变量 NV_CUDNN_PACKAGE
ENV NV_CUDNN_PACKAGE=libcudnn9-cuda-12=9.1.0.70-1
                        
# 2024-04-23 08:07:03  0.00B 设置环境变量 NV_CUDNN_PACKAGE_NAME
ENV NV_CUDNN_PACKAGE_NAME=libcudnn9-cuda-12
                        
# 2024-04-23 08:07:03  0.00B 设置环境变量 NV_CUDNN_VERSION
ENV NV_CUDNN_VERSION=9.1.0.70-1
                        
# 2024-04-23 07:46:26  0.00B 配置容器启动时运行的命令
ENTRYPOINT ["/opt/nvidia/nvidia_entrypoint.sh"]
                        
# 2024-04-23 07:46:26  0.00B 设置环境变量 NVIDIA_PRODUCT_NAME
ENV NVIDIA_PRODUCT_NAME=CUDA
                        
# 2024-04-23 07:46:26  2.53KB 复制新文件或目录到容器中
COPY nvidia_entrypoint.sh /opt/nvidia/ # buildkit
                        
# 2024-04-23 07:46:26  3.06KB 复制新文件或目录到容器中
COPY entrypoint.d/ /opt/nvidia/entrypoint.d/ # buildkit
                        
# 2024-04-23 07:46:26  263.02KB 执行命令并创建新的镜像层
RUN |1 TARGETARCH=amd64 /bin/sh -c apt-mark hold ${NV_LIBCUBLAS_PACKAGE_NAME} ${NV_LIBNCCL_PACKAGE_NAME} # buildkit
                        
# 2024-04-23 07:46:26  2.05GB 执行命令并创建新的镜像层
RUN |1 TARGETARCH=amd64 /bin/sh -c apt-get update && apt-get install -y --no-install-recommends     cuda-libraries-12-4=${NV_CUDA_LIB_VERSION}     ${NV_LIBNPP_PACKAGE}     cuda-nvtx-12-4=${NV_NVTX_VERSION}     libcusparse-12-4=${NV_LIBCUSPARSE_VERSION}     ${NV_LIBCUBLAS_PACKAGE}     ${NV_LIBNCCL_PACKAGE}     && rm -rf /var/lib/apt/lists/* # buildkit
                        
# 2024-04-23 07:46:26  0.00B 添加元数据标签
LABEL maintainer=NVIDIA CORPORATION <cudatools@nvidia.com>
                        
# 2024-04-23 07:46:26  0.00B 定义构建参数
ARG TARGETARCH
                        
# 2024-04-23 07:46:26  0.00B 设置环境变量 NV_LIBNCCL_PACKAGE
ENV NV_LIBNCCL_PACKAGE=libnccl2=2.21.5-1+cuda12.4
                        
# 2024-04-23 07:46:26  0.00B 设置环境变量 NCCL_VERSION
ENV NCCL_VERSION=2.21.5-1
                        
# 2024-04-23 07:46:26  0.00B 设置环境变量 NV_LIBNCCL_PACKAGE_VERSION
ENV NV_LIBNCCL_PACKAGE_VERSION=2.21.5-1
                        
# 2024-04-23 07:46:26  0.00B 设置环境变量 NV_LIBNCCL_PACKAGE_NAME
ENV NV_LIBNCCL_PACKAGE_NAME=libnccl2
                        
# 2024-04-23 07:46:26  0.00B 设置环境变量 NV_LIBCUBLAS_PACKAGE
ENV NV_LIBCUBLAS_PACKAGE=libcublas-12-4=12.4.5.8-1
                        
# 2024-04-23 07:46:26  0.00B 设置环境变量 NV_LIBCUBLAS_VERSION
ENV NV_LIBCUBLAS_VERSION=12.4.5.8-1
                        
# 2024-04-23 07:46:26  0.00B 设置环境变量 NV_LIBCUBLAS_PACKAGE_NAME
ENV NV_LIBCUBLAS_PACKAGE_NAME=libcublas-12-4
                        
# 2024-04-23 07:46:26  0.00B 设置环境变量 NV_LIBCUSPARSE_VERSION
ENV NV_LIBCUSPARSE_VERSION=12.3.1.170-1
                        
# 2024-04-23 07:46:26  0.00B 设置环境变量 NV_LIBNPP_PACKAGE
ENV NV_LIBNPP_PACKAGE=libnpp-12-4=12.2.5.30-1
                        
# 2024-04-23 07:46:26  0.00B 设置环境变量 NV_LIBNPP_VERSION
ENV NV_LIBNPP_VERSION=12.2.5.30-1
                        
# 2024-04-23 07:46:26  0.00B 设置环境变量 NV_NVTX_VERSION
ENV NV_NVTX_VERSION=12.4.127-1
                        
# 2024-04-23 07:46:26  0.00B 设置环境变量 NV_CUDA_LIB_VERSION
ENV NV_CUDA_LIB_VERSION=12.4.1-1
                        
# 2024-04-23 07:42:28  0.00B 设置环境变量 NVIDIA_DRIVER_CAPABILITIES
ENV NVIDIA_DRIVER_CAPABILITIES=compute,utility
                        
# 2024-04-23 07:42:28  0.00B 设置环境变量 NVIDIA_VISIBLE_DEVICES
ENV NVIDIA_VISIBLE_DEVICES=all
                        
# 2024-04-23 07:42:28  17.29KB 复制新文件或目录到容器中
COPY NGC-DL-CONTAINER-LICENSE / # buildkit
                        
# 2024-04-23 07:42:28  0.00B 设置环境变量 LD_LIBRARY_PATH
ENV LD_LIBRARY_PATH=/usr/local/nvidia/lib:/usr/local/nvidia/lib64
                        
# 2024-04-23 07:42:28  0.00B 设置环境变量 PATH
ENV PATH=/usr/local/nvidia/bin:/usr/local/cuda/bin:/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin
                        
# 2024-04-23 07:42:28  46.00B 执行命令并创建新的镜像层
RUN |1 TARGETARCH=amd64 /bin/sh -c echo "/usr/local/nvidia/lib" >> /etc/ld.so.conf.d/nvidia.conf     && echo "/usr/local/nvidia/lib64" >> /etc/ld.so.conf.d/nvidia.conf # buildkit
                        
# 2024-04-23 07:42:28  155.93MB 执行命令并创建新的镜像层
RUN |1 TARGETARCH=amd64 /bin/sh -c apt-get update && apt-get install -y --no-install-recommends     cuda-cudart-12-4=${NV_CUDA_CUDART_VERSION}     ${NV_CUDA_COMPAT_PACKAGE}     && rm -rf /var/lib/apt/lists/* # buildkit
                        
# 2024-04-23 07:42:16  0.00B 设置环境变量 CUDA_VERSION
ENV CUDA_VERSION=12.4.1
                        
# 2024-04-23 07:42:16  10.57MB 执行命令并创建新的镜像层
RUN |1 TARGETARCH=amd64 /bin/sh -c apt-get update && apt-get install -y --no-install-recommends     gnupg2 curl ca-certificates &&     curl -fsSLO https://developer.download.nvidia.com/compute/cuda/repos/ubuntu2204/${NVARCH}/cuda-keyring_1.1-1_all.deb &&     dpkg -i cuda-keyring_1.1-1_all.deb &&     apt-get purge --autoremove -y curl     && rm -rf /var/lib/apt/lists/* # buildkit
                        
# 2024-04-23 07:42:16  0.00B 添加元数据标签
LABEL maintainer=NVIDIA CORPORATION <cudatools@nvidia.com>
                        
# 2024-04-23 07:42:16  0.00B 定义构建参数
ARG TARGETARCH
                        
# 2024-04-23 07:42:16  0.00B 设置环境变量 NV_CUDA_COMPAT_PACKAGE
ENV NV_CUDA_COMPAT_PACKAGE=cuda-compat-12-4
                        
# 2024-04-23 07:42:16  0.00B 设置环境变量 NV_CUDA_CUDART_VERSION
ENV NV_CUDA_CUDART_VERSION=12.4.127-1
                        
# 2024-04-23 07:42:16  0.00B 设置环境变量 NVIDIA_REQUIRE_CUDA brand brand brand brand brand brand brand brand brand brand brand brand brand brand brand brand brand brand brand brand brand brand brand brand brand brand brand brand brand brand
ENV NVIDIA_REQUIRE_CUDA=cuda>=12.4 brand=tesla,driver>=470,driver<471 brand=unknown,driver>=470,driver<471 brand=nvidia,driver>=470,driver<471 brand=nvidiartx,driver>=470,driver<471 brand=geforce,driver>=470,driver<471 brand=geforcertx,driver>=470,driver<471 brand=quadro,driver>=470,driver<471 brand=quadrortx,driver>=470,driver<471 brand=titan,driver>=470,driver<471 brand=titanrtx,driver>=470,driver<471 brand=tesla,driver>=525,driver<526 brand=unknown,driver>=525,driver<526 brand=nvidia,driver>=525,driver<526 brand=nvidiartx,driver>=525,driver<526 brand=geforce,driver>=525,driver<526 brand=geforcertx,driver>=525,driver<526 brand=quadro,driver>=525,driver<526 brand=quadrortx,driver>=525,driver<526 brand=titan,driver>=525,driver<526 brand=titanrtx,driver>=525,driver<526 brand=tesla,driver>=535,driver<536 brand=unknown,driver>=535,driver<536 brand=nvidia,driver>=535,driver<536 brand=nvidiartx,driver>=535,driver<536 brand=geforce,driver>=535,driver<536 brand=geforcertx,driver>=535,driver<536 brand=quadro,driver>=535,driver<536 brand=quadrortx,driver>=535,driver<536 brand=titan,driver>=535,driver<536 brand=titanrtx,driver>=535,driver<536
                        
# 2024-04-23 07:42:16  0.00B 设置环境变量 NVARCH
ENV NVARCH=x86_64
                        
# 2024-04-11 02:52:04  0.00B 
/bin/sh -c #(nop)  CMD ["/bin/bash"]
                        
# 2024-04-11 02:52:04  77.86MB 
/bin/sh -c #(nop) ADD file:3bd10da0673e2e72cb06a1f64a9df49a36341df39b0f762e3d1b38ee4de296fa in / 
                        
# 2024-04-11 02:52:02  0.00B 
/bin/sh -c #(nop)  LABEL org.opencontainers.image.version=22.04
                        
# 2024-04-11 02:52:02  0.00B 
/bin/sh -c #(nop)  LABEL org.opencontainers.image.ref.name=ubuntu
                        
# 2024-04-11 02:52:02  0.00B 
/bin/sh -c #(nop)  ARG LAUNCHPAD_BUILD_ARCH
                        
# 2024-04-11 02:52:02  0.00B 
/bin/sh -c #(nop)  ARG RELEASE

镜像信息

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    "Id": "sha256:fb7663b0759faa39ff8f00ffd0f77e67d69b09d1b9f470c8f068b221926042b6",
    "RepoTags": [
        "roboflow/roboflow-inference-server-gpu:0.62.4",
        "swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/roboflow/roboflow-inference-server-gpu:0.62.4"
    ],
    "RepoDigests": [
        "roboflow/roboflow-inference-server-gpu@sha256:c45b47d75768b8c40a9cfe0171d08b94a24e0f00db53a141b4daffe859657724",
        "swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/roboflow/roboflow-inference-server-gpu@sha256:faf0d8a213bdd0114988de3df86e25b9d923f55ab29b1a5a7f288841a35dcfbf"
    ],
    "Parent": "",
    "Comment": "buildkit.dockerfile.v0",
    "Created": "2025-12-09T22:16:08.646199305Z",
    "Container": "",
    "ContainerConfig": null,
    "DockerVersion": "",
    "Author": "",
    "Config": {
        "Hostname": "",
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}

更多版本

docker.io/roboflow/roboflow-inference-server-gpu:0.62.4

linux/amd64 docker.io15.00GB2025-12-11 00:40