Traffic RecognitionΒΆ

The traffic recognition API classifies an image into one of the following

Sparse traffic

Dense traffic

Accident

Fire

With this, from images of live traffic, you can tell if an accident has occured, if their is traffic gridlock or if a vehicle is on fire.

To use this API, you need to set VISION-TRAFFIC=True when starting DeepStack

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

If using the GPU Version, run

sudo docker run --rm --runtime=nvidia -e VISION-TRAFFIC=True -v localstorage:/datastore \
-p 80:5000 deepquestai/deepstack:gpu

Note also that you can have multiple endpoints activated, for example, both traffic and object detection are activated below

sudo docker run -e VISION-TRAFFIC=True  -e VISION-DETECTION=True -v localstorage:/datastore \
-p 80:5000 deepquestai/deepstack

Example

_images/test-image4.jpg
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("test-image4.jpg"));
        var output = await client.PostAsync("http://localhost:80/v1/vision/traffic",request);
        var jsonString = await output.Content.ReadAsStringAsync();

        Console.WriteLine(jsonString);

    }

    static void Main(string[] args){

        makeRequest().Wait();

    }

    }

}

Result

{'success': True, 'confidence': 0.9488776, 'label': 'accident'}