• Stars
    star
    687
  • Rank 65,799 (Top 2 %)
  • Language
    Python
  • License
    Apache License 2.0
  • Created over 4 years ago
  • Updated 5 months ago

Reviews

There are no reviews yet. Be the first to send feedback to the community and the maintainers!

Repository Details

The World's Leading Cross Platform AI Engine for Edge Devices

DeepStack

The World's Leading Cross Platform AI Engine for Edge Devices, with over 10 million installs on Docker Hub.

black

license

DevTest

Website: https://deepstack.cc

Documentation: https://docs.deepstack.cc

Forum: https://forum.deepstack.cc

Dev Center: https://dev.deepstack.cc

DeepStack is owned and maintained by DeepQuest AI.

Introduction

DeepStack is an AI API engine that serves pre-built models and custom models on multiple edge devices locally or on your private cloud. Supported platforms are:

  • Linux OS via Docker ( CPU and NVIDIA GPU support )
  • Mac OS via Docker
  • Windows 10 ( native application, CPU and GPU )
  • NVIDIA Jetson via Docker.
  • Rasperry Pi & ARM64 Devices via Docker.

DeepStack runs completely offline and independent of the cloud. You can also install and run DeepStack on any cloud VM with docker installed to serve as your private, state-of-the-art and real-time AI server.

Features

  • Face APIs: Face detection, recognition and matching.

    Face API

  • Common Objects APIs: Object detection for 80 common objects

    Detection API

  • Custom Models: Train and deploy new models to detect any custom object(s)

    Custom Models API

  • Image Enhance: 4X image superresolution

    Input

    Image Enhance API Iput

    Output Image Enhance API Iput

  • Scene Recognition: Image scene recognition

  • SSL Support

  • API Key support: Security options to protect your DeepStack endpoints

Installation and Usage

Visit https://docs.deepstack.cc/getting-started for installation instructions. The documentation provides example codes for the following programming languages with more to be added soon.

  • Python
  • C#
  • NodeJS

Build from Source (For Docker Version)

  • Install Prerequisites

  • Clone DeepStack Repo

    git clone https://github.com/johnolafenwa/DeepStack.git

  • CD to DeepStack Repo Dir

    cd DeepStack

  • Fetch Repo Files

    git lfs pull

  • Download Binary Dependencies With Powershell .\download_dependencies.ps1

  • Build DeepStack CPU Version

    cd .. && sudo docker build -t deepquestai/deepstack:cpu . -f Dockerfile.cpu

  • Build DeepStack GPU Version

    sudo docker build -t deepquestai/deepstack:gpu . -f Dockerfile.gpu

  • Build DeepStack Jetson Version

    sudo docker build -t deepquestai/deepstack:jetpack . -f Dockerfile.gpu-jetpack

  • Running and Testing Locally Without Building

    • Unless you wish to install requirements system wide, create a virtual environment with python3.7 -m venv venv and activate with source venv/bin/activate

    • Install Requirements with pip3 install -r requirements.txt

    • For CPU Version, Install PyTorch with pip3 install torch==1.6.0+cpu torchvision==0.7.0+cpu -f https://download.pytorch.org/whl/torch_stable.html

    • For GPU Version, Install Pytorch with pip3 install torch==1.6.0+cu101 torchvision==0.7.0+cu101 -f https://download.pytorch.org/whl/torch_stable.html

    • Start Powershell pwsh

    • For CPU Version, Run .\setup_docker_cpu.ps1

    • For GPU Version, Run .\setup_docker_gpu.ps1

    • CD To Server Dir cd server

    • Build DeepStack Server go build

    • Set Any of the APIS to enable; $env:VISION_DETECTION = "True", $env:VISION_FACE = "True", $env:VISION_SCENE = "True"

    • Run DeepStack .\server

    You can find all logs in the directory in the repo root. Note that DeepStack will be running on the default port 5000.

Integrations and Community

The DeepStack ecosystem includes a number of popular integrations and libraries built to expand the functionalities of the AI engine to serve IoT, industrial, monitoring and research applications. A number of them are listed below

Contributors Guide

(coming soon)

More Repositories

1

TorchFusion

A modern deep learning framework built to accelerate research and development of AI systems
Python
257
star
2

Pytorch-Keras-ToAndroid

Java
107
star
3

PytorchMobile

Codes and Sample Application for converting and deploying pytorch models in android applications
Java
69
star
4

DeepStackPython

Official Python SDK for DeepStack
Python
29
star
5

deepstack-trainer

Custom Object Detection Training for DeepStack
Python
20
star
6

FastNet

Official Repository for FastNet, An Efficient Convolutional Neural Network Architecture, highly optimized for Smart Devices.
Python
17
star
7

TorchFusion-Utils

A pytorch helper library for Mixed Precision Training, Initialization, Metrics and More Utilities to simplify training of deep learning models
Python
15
star
8

deepstack-docs

Documentation for DeepStack
Python
8
star
9

DeepVision

Official Repository for my book, "Introduction to Deep Computer Vision"
Python
7
star
10

Ling10

A dataset of 190 000 sentences categorized into 10 languages, primarily for Language Detection tasks. This repository containes the dataset and code for processing it.
Python
6
star
11

DeepStack-Base

Base Docker Images for DeepStack AI Server
6
star
12

DevPlanet

Github Repository for the Dev Planet Publication.
5
star
13

deepstackgo

Go client library for DeepStack AI Server
Go
5
star
14

deepreview

Baseline Implementation of Popular Deep Learning Papers
Python
5
star
15

transformer_layer_swap

An experiment demonstrating the layers of a transformers model can be swapped without breaking the model
Jupyter Notebook
5
star
16

Neural-Network-Tutorials

Code for my tutorials on Artificial Neural Networks
Python
4
star
17

gozip

An easy to use Go Library for creating and extracting compressed files
Go
3
star
18

Docker-Intro

Official Github Repository for the book, "Introduction to Software Development with Docker"
HTML
3
star
19

CNNLecture

2
star
20

OpenAIClipTutorial

Python
2
star
21

transformers

Theory and Applications of Transformer DNNs
2
star
22

gantricks

Tricks for Stable Training of Generative Adversarial Networks for Image Generation
2
star
23

TorchFusionDocumentation

Python
1
star
24

DevOpsBook

Official Repository for the book, "Introduction to DevOps with Github and Kubernetes"
1
star
25

TorchFusionExamples

A set of examples for training and using deep neural networks using TorchFusion and PyTorch
1
star
26

TorchFusion-Applications

Reference implementations of state-of-the-art deep learning models in pytorch
1
star
27

TorchFusion-Learn

A high simple to use framework for training pytorch models in few lines of code
1
star
28

DeepNLPBook

1
star