专属
文档
插件
助手
邀请
顶部
快速返回页面顶部
收起
收起工具栏
轩辕镜像 官方专业版
轩辕镜像
专业版
轩辕镜像 官方专业版
轩辕镜像
专业版
首页个人中心搜索镜像

交易
充值流量我的订单

文档

工具

功能
提交工单页面收录

帮助
轩辕镜像免费版

其他
关于我们网站地图
热门搜索:
matlab-deep-learning

mathworks/matlab-deep-learning

mathworks

包含深度学习工具箱、预训练模型及其他工具箱的MATLAB Docker容器,用于支持深度学习等任务。

14 次收藏下载次数: 0状态:社区镜像维护者:mathworks仓库类型:镜像最近更新:7 天前
让 AI 帮你使用轩辕镜像? · 展开查看说明

如果你使用 DeepSeek、元宝 AI、Copilot、ChatGPT 等 AI 工具,协助配置轩辕镜像、编写 docker pull 命令、修改 Docker Compose 镜像地址、配置镜像加速、排查镜像拉取失败、分析报错日志等问题,请先让 AI 阅读并遵守轩辕镜像的规则文档。

只需在 AI 对话中先发送下面这句话即可:

请先完整阅读并严格遵守以下文档中的全部规则与要求:

https://xuanyuan.cloud/agents.md

在未充分阅读并理解该文档前,不要生成任何命令、配置、修改建议、故障排查方案或技术回答。后续所有输出都必须严格以该文档中的规范为最高优先级执行。

查看 agents.md 用法指南与完整示范。国内用户首推 元宝 AI、DeepSeek 的深度思考模式,不推荐豆包 AI;Cursor 等编辑器可在对话 @ 该链接,或加入 User Rules。 若 AI 无法访问外链,可 打开说明文档 复制全文粘贴。文档会随站点更新,复制内容可能过期,建议定期检查。

轩辕镜像,加速的不只是镜像。点击查看
DockerHub 官方简介
轩辕镜像中文简介
标签列表
镜像标签列表与下载命令
轩辕镜像,加速的不只是镜像。点击查看

MATLAB Deep Learning Docker Container

Speed up your deep learning applications by training neural networks in the MATLAB® Deep Learning Container. This container is designed to take full advantage of high-performance NVIDIA® GPUs. It provides a simple and flexible solution to use MATLAB for deep learning workflows in cloud environments such as AWS® or Microsoft® Azure®.

Supported tags

TagsMATLAB VersionOperating SystemBase Image
latest, R2026a, r2026aR2026aUbuntu® 24.04ubuntu:24.04
R2025b, r2025bR2025bUbuntu 24.04ubuntu:24.04
R2025a, r2025aR2025aUbuntu 24.04ubuntu:24.04
R2024b, r2024bR2024bUbuntu 24.04ubuntu:24.04
R2024a, r2024aR2024aUbuntu 24.04ubuntu:24.04
R2023b, r2023bR2023bUbuntu 24.04ubuntu:24.04
R2023a, r2023aR2023aUbuntu 24.04ubuntu:24.04
R2022b, r2022bR2022bUbuntu 20.04ubuntu:20.04
R2022a, r2022aR2022aUbuntu 20.04ubuntu:20.04
R2021b, r2021bR2021bUbuntu 20.04ubuntu:20.04

Quick Launch Instructions

This section describes an example workflow to pull the R2026a MATLAB Deep Learning image and launch an interactive MATLAB session from the image.

To pull the R2026a MATLAB image to your machine, execute:

console
docker pull mathworks/matlab-deep-learning:r2026a

To launch the container with the -browser option, execute:

console
docker run -it --rm -p 8888:8888 --shm-size=512M mathworks/matlab-deep-learning:r2026a -browser

Executing this command will display a URL on which you can access MATLAB, for example:

console
http://localhost:8888/index.html

For more information on running the container, see the section on How to use this image.

What is MATLAB?

MATLAB is a programming platform designed for engineers and scientists. It combines a desktop environment tuned for iterative analysis and design processes with a programming language that expresses matrix and array mathematics directly. For more information, click this link to access our website.

The MATLAB Deep Learning Container provides algorithms, pretrained models, and apps to create, train, visualize, and optimize deep neural networks. You can also access tools for image and signal processing, text analytics, and automatically generating C and CUDA® code for deployment on NVIDIA® GPUs in data centers and embedded systems. Specifically, this container provides an Ubuntu-based image with an installation of MATLAB and the following toolboxes:

  • Computer Vision Toolbox™
  • Deep Learning Toolbox™
  • GPU Coder™
  • Image Processing Toolbox™
  • MATLAB Coder™
  • Parallel Computing Toolbox™
  • Signal Processing Toolbox™
  • Statistics and Machine Learning Toolbox™
  • Text Analytics Toolbox™

and the following Support Packages:

  • Deep Learning Toolbox Converter for TensorFlow Models
  • Deep Learning Toolbox Converter for ONXX Models Format
  • Deep Learning Toolbox Importer for Caffe Models
  • Deep Learning Toolbox Model for AlexNet Network
  • Deep Learning Toolbox Model for GoogLeNet Network
  • Deep Learning Toolbox Model for Inception-v3 Network
  • Deep Learning Toolbox Model for Inception-ResNet-v2 Network
  • Deep Learning Toolbox Model for ResNet-18 Network
  • Deep Learning Toolbox Model for ResNet-50 Network
  • Deep Learning Toolbox Model for ResNet-101 Network
  • GPU Coder Interface for Deep Learning Libraries
  • MATLAB Coder Interface for Deep Learning Libraries
  • (since R2023a) Deep Learning Toolbox Verification Library

Configure your license

To use the MATLAB Deep Learning Container, you need a license for the MathWorks® products in the container.

To train deep learning models, you need a license for MATLAB, Deep Learning and Parallel Computing toolboxes. If you are licensed to use the additional products in the container, its functionality is extended.

On public cloud instances like Amazon EC2®, you can use a license that is enabled for cloud use. For on-premise DGX use, you can use a concurrent license by specifying the location of the network license manager when you run the container. Individual and Campus-Wide licenses are already configured for cloud use. For other license types, contact your license administrator. You can identify your license type and administrator by viewing your MathWorks Account. Administrators can consult Administer Network Licenses.

How to use this image

This section describes the different options you can use to run the container, depending on your use case. Some options allow you to interact with MATLAB via the command line interface while others let you interact with the MATLAB desktop.

Run MATLAB with GPUs on your host machine

Before you start the container, check that your graphics driver is up to date. See MATLAB GPU Computing Requirements for details.

To start the container and run MATLAB with GPUs on your host machine, execute:

console
$ docker run --gpus all -it --rm --shm-size=512M mathworks/matlab-deep-learning:r2026a

By default, a container does not have access to hardware resources of its host. To enable the container to access the GPUs of the host system, use the --gpus flag when you execute the docker run command. Set this flag to all if you want the container to have access to all the GPUs of the host machine.

For more information, see Access an NVIDIA GPU.

Run MATLAB in an interactive command prompt

To start the container and run MATLAB in an interactive command prompt, execute:

console
$ docker run -it --rm mathworks/matlab-deep-learning:r2026a

Run MATLAB non-interactively in batch mode

To start the container and run the MATLAB command RAND, execute:

console
$ docker run --rm -e MLM_LICENSE_FILE=27000@MyLicenseServer mathworks/matlab-deep-learning:r2026a -batch rand

where you must replace 27000@MyLicenseServer with the correct port number and DNS address for your network license manager.

Alternatively, if your system administrator provides you with a license file, you can mount the license file to the container and point MLM_LICENSE_FILE to the license file path in the container. For example, to start the container and run the MATLAB command RAND with a license file, execute:

console
$ docker run --rm -v /path/to/local/license/file:/licenses/license.lic -e MLM_LICENSE_FILE=/licenses/license.lic mathworks/matlab-deep-learning:r2026a -batch rand

If a valid license file is provided, the container runs the command RAND in MATLAB and exits. For more information on using the network license manager, see https://github.com/mathworks-ref-arch/matlab-dockerfile#use-the-network-license-manager.

Run MATLAB and interact with it via a web browser

To start the container, execute:

console
$ docker run -it --rm -p 8888:8888 --shm-size=512M mathworks/matlab:r2026a -browser

Running the above command prints text to your terminal containing the URL to access MATLAB. For example:

console
MATLAB can be accessed at:
http://localhost:8888/index.html

Enter the provided URL into a web browser. If prompted to do so, enter credentials for a MathWorks account associated with a MATLAB license. If you are using a network license manager, change to the Network License Manager tab and enter the license server address instead. After you provide your license information, a MATLAB session will start in the browser (this may take several minutes).

To modify the behavior of MATLAB when launched with -browser flag, pass environment variables to the docker run command. For more information, see https://github.com/mathworks/matlab-proxy/blob/main/Advanced-Usage.md.

Some browsers may not support this workflow. For more information, see Cloud Solutions Browser Requirements.

NOTE: The -browser flag is supported by Docker® images starting from MATLAB R2022a. To access MATLAB in a web browser in custom Docker images with MATLAB or older MATLAB Docker images, for example R2021b, see https://github.com/mathworks/matlab-proxy/blob/main/examples/Dockerfile.

Run MATLAB in desktop mode and interact with it via VNC

To start the MATLAB desktop, execute:

console
$ docker run -it --rm -p 5901:5901 -p 6080:6080 --shm-size=512M mathworks/matlab-deep-learning:r2026a -vnc

To connect to the MATLAB desktop, either:

  1. Point a browser to port 6080 of the Docker host machine running this container (http://hostname:6080)
  2. Use a VNC client to connect to display 1 of the Docker host machine (hostname:1)

The VNC password is matlab by default. Use the PASSWORD environment variable to change it. If you are using a cloud service provider or your host or client machines are protected by a firewall, you must set up SSH tunnels between your client machine and the Docker host to access the container desktop. For instructions, see the Create Encrypted Connection to Remote Applications and Containers.

Run MATLAB desktop using X11

To start the container and run MATLAB desktop using X11, execute:

console
$ xhost +
$ docker run -it --rm -e DISPLAY=$DISPLAY -v /tmp/.X11-unix:/tmp/.X11-unix:ro --shm-size=512M mathworks/matlab-deep-learning:r2026a

The MATLAB desktop window will open on your machine. Note that the command above works only on a Linux operating system with X11 and its dependencies installed.

Run MATLAB with startup options

To override the default behavior of the container and run MATLAB with any set of arguments, such as -logfile, execute:

console
$ docker run -it --rm mathworks/matlab-deep-learning:r2026a -logfile "logfilename.log"

Environment variables

When executing the command docker run you can specify environment variables using the option -e. This section describes all the environment variables that you can specify.

MLM_LICENSE_FILE

Use this environment variable when you want to use either a license file or a network license manager to license MATLAB.

Example:

docker run -it --rm -e MLM_LICENSE_FILE=27000@MyLicenseServer mathworks/matlab-deep-learning:r2026a

docker run -it --rm -e MLM_LICENSE_FILE=/license.dat mathworks/matlab-deep-learning:r2026a

PROXY_SETTINGS

Use this environment variable when you want to use a proxy server to connect to the MathWorks licensing servers.

Example:

docker run -it --rm -e PROXY_SETTINGS=<proxy-server-address> mathworks/matlab-deep-learning:r2026a

You can specify the proxy server address using any of the following forms:

  • hostname:12345
  • shorthostname:12345
  • http://hostname:12345
  • http://username:password@hostname:12345
  • IPaddress:12345

where hostname is the fully qualified domain name, shorthostname is the relative domain name, and *** is the port number.

PASSWORD

Use this environment variable when you want to change the password used to access the VNC server.

Example:

docker run -it --rm -e PASSWORD=ILoveMATLAB -p 5901:5901 -p 6080:6080 --shm-size=512M mathworks/matlab-deep-learning:r2026a -vnc

Install updates, toolboxes, add-ons in the container and save changes

You can install the latest MATLAB updates or install additional toolboxes and add-ons in this container. For more information, see Install Updates, Toolboxes, Support Packages, and Add-Ons in Containers.

Security reporting

Follow these instructions to https://github.com/mathworks-ref-arch/container-images/blob/master/SECURITY.md.

Additional information

This container includes commercial software products of The MathWorks, Inc. ("MathWorks Programs") and related materials. MathWorks Programs are licensed under the MathWorks Software License Agreement, available in the MATLAB installation in this container. Related materials in this container are licensed under separate licenses which can be found in their respective folders.

To learn more about MATLAB containers, see MATLAB Container on Docker Hub.

To see the source files used to build this Docker image, see the https://github.com/mathworks-ref-arch/container-images/tree/main/matlab.

To provide suggestions for additional features or capabilities, contact us.

Technical support

If you require assistance or have a request for additional features or capabilities, contact MathWorks Technical Support.

Copyright 2021-2026 The MathWorks, Inc.

更多相关 Docker 镜像与资源

以下是 mathworks/matlab-deep-learning 相关的常用 Docker 镜像,适用于 不同场景 等不同场景:

  • nvidia/cuda Docker 镜像说明
  • pytorch/pytorch Docker 镜像说明
  • rocker/cuda Docker 镜像说明(CUDA 运行时,Rocker 维护版本,适合 GPU 计算)
  • rocm/pytorch Docker 镜像说明(PyTorch 机器学习框架,ROCm GPU 加速版本)
  • bitnami/pytorch Docker 镜像说明(PyTorch 深度学习框架,Bitnami 企业级配置)

镜像拉取方式

您可以使用以下命令拉取该镜像。请将 <标签> 替换为具体的标签版本。如需查看所有可用标签版本,请访问 标签列表页面。

轩辕镜像加速拉取命令点我查看更多 matlab-deep-learning 镜像标签

docker pull docker.xuanyuan.run/mathworks/matlab-deep-learning:<标签>

使用方法:

  • 登录认证方式
  • 免认证方式

DockerHub 原生拉取命令

docker pull mathworks/matlab-deep-learning:<标签>

更多 matlab-deep-learning 镜像推荐

mathworks/matlab logo

mathworks/matlab

mathworks
MATLAB Docker容器,用于在云和服务器环境中访问MATLAB,支持通过浏览器和VNC进行交互,提供基于Ubuntu的预构建镜像,适用于工程师和科学家的编程平台,集成矩阵数学编程语言与桌面环境。
89 次收藏100万+ 次下载
28 天前更新
mathworks/matlab-deps logo

mathworks/matlab-deps

mathworks
包含运行MATLAB®、Simulink®及其他MathWorks产品所需依赖的Docker镜像,不含MATLAB本身,适用于构建或运行MATLAB相关容器环境。
9 次收藏10万+ 次下载
28 天前更新
intel/deep-learning-essentials logo

intel/deep-learning-essentials

intel
使AI开发者和从业者能够快速高效地为Intel GPU和CPU构建、增强、测试和调试高性能深度学习框架和工具。
3 次收藏10万+ 次下载
1 个月前更新
demisto/ssdeep logo

demisto/ssdeep

demisto
暂无描述
10万+ 次下载
29 天前更新
mathworks/matlab-runtime-deps logo

mathworks/matlab-runtime-deps

mathworks
包含MATLAB Runtime所需依赖项的Docker镜像,不包含MATLAB Runtime本身,支持多个MATLAB版本和Ubuntu操作系统。
1万+ 次下载
28 天前更新
bitnamicharts/deepspeed logo

bitnamicharts/deepspeed

bitnamicharts
Bitnami Helm chart,用于在Kubernetes集群部署DeepSpeed深度学习套件,支持类ChatGPT模型训练,具备密集/稀疏模型推理、高吞吐量和高压缩特性。
50万+ 次下载
9 个月前更新

查看更多 matlab-deep-learning 相关镜像

轩辕镜像配置手册

按平台快速找到配置文档

Docker

登录仓库拉取

登录认证 · 私有仓库

专属域名拉取

免登录 · 高速拉取

Linux

Docker 镜像配置

Windows / Mac

Docker Desktop 配置

MacOS OrbStack

OrbStack 容器

Docker Compose

Compose 项目配置

NAS

群晖

Synology 配置

飞牛

fnOS 镜像配置

绿联

绿联 NAS

威联通

QNAP 配置

极空间

极空间 NAS

企业仓库

其他仓库

ghcr · Quay · nvcr

Harbor 镜像源

Proxy Repository 对接

Portainer 镜像源

Registries 配置

Nexus 镜像源

Docker Proxy 缓存

开发工具

Dev Containers

VS Code 开发容器

Podman

Podman 配置指南

Singularity / Apptainer

HPC 科学计算容器

Kubernetes

K8s Containerd

Kubernetes · Containerd

K3s

轻量级集群

面板 / 网络

爱快路由

iKuai 镜像加速

宝塔面板

一键配置镜像源

AI

用 AI 使用轩辕镜像

agents.md · AI 对话 · 提示词

一键安装

一键安装 Docker

Linux Docker 一键安装

需要其他帮助?请查看我们的 常见问题 Docker 镜像访问常见问题解答 或 提交工单

镜像拉取常见问题

功能

免费版与专业版区别

功能对比 · 版本选择

支持的镜像仓库

Docker Hub · GCR · GHCR

新手拉取配置

登录 · 专属域名 · 配置

docker search 限制

专属域名 · Hub 搜索

不支持 push

仅支持 pull · 不支持

拉取速度原因

带宽 · 缓存 · 冷热镜像

错误码

402 与流量用尽

402 · 流量包 · 充值

401 认证失败

401 · docker login

manifest unknown

标签错误 · 镜像不存在

410 Gone 排查

410 · Docker 升级

429 限流

免费版 · 请求频率

其他报错

DNS 超时

DNS 解析 · 网络超时

TLS 证书失败

no matching manifest(架构)

账号

失败是否计费

manifest · blob · 计费

申请开发票(企业 / 个人)

企业 · 个人 · 工单

修改登录密码

网站 · 仓库 · 重置

注销账户

工单 · 数据 · 注销

原理

mirrors 不生效

daemon.json · 重启

去掉域名前缀

docker tag · 重命名

指定架构拉取

ARM64 · AMD64 · 多架构

latest 与「最新」

digest · 版本号 · 标签

查看全部问题→

用户好评

来自真实用户的反馈,见证轩辕镜像的优质服务

用户头像

oldzhang

运维工程师

Linux服务器

5

"Docker访问体验非常流畅,大镜像也能快速完成下载。"

轩辕镜像
镜像详情
...
mathworks/matlab-deep-learning
教程轩辕镜像功能与使用教程
价格查看流量套餐与价格
热门查看热门 Docker 镜像推荐
博客Docker 镜像公告与技术博客
官方公众号:源码跳动|官方技术交流群:831623681
官方公众号:源码跳动|官方技术交流群:|问题咨询请:提交工单
商务合作:点击复制邮箱
©2024-2026 源码跳动
商务合作:点击复制邮箱Copyright © 2024-2026 杭州源码跳动科技有限公司. All rights reserved.