DeepStack Documentation!¶

Official Documentation and Guide for DeepStack AI Server.¶

DeepStack is an AI server that empowers every developer in the world to easily build state-of-the-art AI systems both on premise and in the cloud. The promises of Artificial Intelligence are huge but becoming a machine learning engineer is hard. DeepStack is device and language agnostic. You can run it on Windows, Mac OS, Linux, Raspberry PI and use it with any programming language.

DeepStack’s source code is available on GitHub via https://github.com/johnolafenwa/DeepStack

DeepStack is developed and maintained by DeepQuest AI .

Top Features¶

Example Code¶

Using DeepStack, we can classify the scene of the above image as seen below.

import requests

image_data = open("image.jpg","rb").read()

response = requests.post("http://localhost:80/v1/vision/scene",
files={"image":image_data}).json()
print(response)

const request = require("request")
const fs = require("fs")

image_stream = fs.createReadStream("image.jpg")

var form = {"image":image_stream}

request.post({url:"http://localhost:80/v1/vision/scene", formData:form},function(err,res,body){

    response = JSON.parse(body)
    console.log(response)
})

using System;
using System.IO;
using System.Net.Http;
using System.Threading.Tasks;


namespace app
{

    class App {

    static HttpClient client = new HttpClient();

    public static async Task makeRequest(){

        var request = new MultipartFormDataContent();
        var image_data = File.OpenRead("image.jpg");
        request.Add(new StreamContent(image_data),"image",Path.GetFileName("image.jpg"));
        var output = await client.PostAsync("http://localhost:80/v1/vision/scene",request);
        var jsonString = await output.Content.ReadAsStringAsync();

        Console.WriteLine(jsonString);

    }

    static void Main(string[] args){

        makeRequest().Wait();

    }

    }

}

Response

{ 'success': true, label: 'highway', confidence: 0.63377846 }

Installation¶

DeepStack is available in three variants, CPU Version, GPU Version, NVIDIA Jetson and Raspberry PI Version (With Support for Intel Neural Compute Stick)

Installation Guide for GPU Version

Installation Guide for NVIDIA Jetson

Installation Guide for Windows ( CPU and GPU )

Installation Guide for Raspberry Pi and Other Arm64 Devices

Installation Guide for CPU Version¶

Step 1: Install Docker (If not already installed) Mac OS and Windows Users can install docker from Docker’s Website .

To install on a Linux operating system, run the commands below

sudo apt-get update
sudo apt-get install docker.io

Step 2: Install DeepStack

docker pull deepquestai/deepstack

Run DeepStack with Scene Recognition API enabled¶

Run the command below as it applies to the version you have installed

docker run -e VISION-SCENE=True -v localstorage:/datastore -p 80:5000 deepquestai/deepstack

sudo docker run --gpus all -e VISION-SCENE=True -v localstorage:/datastore -p 80:5000 deepquestai/deepstack:gpu

deepstack --VISION-SCENE True --PORT 80

sudo docker run --runtime nvidia -e VISION-SCENE=True -p 80:5000 deepquestai/deepstack:jetpack

sudo deepstack start "VISION-SCENE=True"

Basic Parameters

-e VISION-SCENE=True This enables the scene recognition API.

-p 80:5000 This makes DeepStack accessible via port 80 of the machine.

Run the example scene recognition code at the begining of this page to verify your installation is working.

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