https://github.com/geon0430/dev-docker-image-build

https://github.com/geon0430/dev-docker-image-build

build cuda docker ffmpeg golang gstreamer image java jeston nvidia python tensorrt

Last synced: 3 months ago
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• Host: GitHub
• URL: https://github.com/geon0430/dev-docker-image-build
• Owner: geon0430
• Created: 2024-12-18T01:58:29.000Z (6 months ago)
• Default Branch: main
• Last Pushed: 2025-01-13T03:10:11.000Z (5 months ago)
• Last Synced: 2025-01-13T04:20:41.225Z (5 months ago)
• Topics: build, cuda, docker, ffmpeg, golang, gstreamer, image, java, jeston, nvidia, python, tensorrt
• Language: Shell
• Homepage:
• Size: 22.5 KB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        

# Dev Docker Image Build Setting

This repository contains Dockerfiles used to build Docker images for development purposes across multiple programming languages: **Python**, **Golang**, and **Java**.

---

## Overview

| **Language** | **Description**                                                                                 |

|--------------|-------------------------------------------------------------------------------------------------|

| **Python**   | Images configured for NVIDIA GPU-based development using CUDA libraries like TensorRT, CuPy, and cuCIM. Also includes video processing libraries such as GStreamer and FFmpeg. |

| **Golang**   | Images set up for Go-based application development in containerized environments.               |

| **Java**     | Images for building and running Java-based applications within Docker containers.               |

---

## Language-Specific Details

### Python

- **Purpose**:

  - Enable NVIDIA GPU-based development.

  - Support CUDA-accelerated libraries:

    - **TensorRT**: AI/ML model optimization and inference.

    - **CuPy**: GPU-accelerated array computation.

    - **cuCIM**: GPU-accelerated image processing.

  - Video processing setup with:

    - **GStreamer**

    - **FFmpeg**

- **Target Platform**: NVIDIA Jetson devices and general-purpose NVIDIA GPU development.

---

### Golang

- **Purpose**:

  - Lightweight and efficient containerized development for Go applications.

- **Key Features**:

  - Configured for general-purpose Golang development.

  - Can be extended for use with specific Go frameworks or tools.

---

### Java

- **Purpose**:

  - Build and run Java-based applications in a containerized environment.

- **Key Features**:

  - Supports JDK installation and configuration.

  - Extensible for various Java frameworks and tools.

---

## Usage

Clone the repository and use the provided Dockerfiles to build development images for the desired language environment.