Inferring on an image hosted elsewhere on the web via its URL (don't forget to URL encode it):
curl -X POST "https://detect.roboflow.com/your-model/42?\
api_key=YOUR_KEY&\
image=https%3A%2F%2Fi.imgur.com%2FPEEvqPN.png"
Windows
You will need to install curl for Windows and GNU's base64 tool for Windows. The easiest way to do this is to use the git for Windows installer which also includes the curl and base64 command line tools when you select "Use Git and optional Unix tools from the Command Prompt" during installation.
Then you can use the same commands as above.
Node.js
We're using axios to perform the POST request in this example so first run npm install axios to install the dependency.
using System;
using System.IO;
using System.Net;
using System.Text;
namespace InferenceLocal
{
class InferenceLocal
{
static void Main(string[] args)
{
byte[] imageArray = System.IO.File.ReadAllBytes(@"YOUR_IMAGE.jpg");
string encoded = Convert.ToBase64String(imageArray);
byte[] data = Encoding.ASCII.GetBytes(encoded);
string API_KEY = ""; // Your API Key
string MODEL_ENDPOINT = "dataset/v"; // Set model endpoint
// Construct the URL
string uploadURL =
"https://detect.roboflow.com/" + MODEL_ENDPOINT + "?api_key=" + API_KEY
+ "&name=YOUR_IMAGE.jpg";
// Service Request Config
ServicePointManager.Expect100Continue = true;
ServicePointManager.SecurityProtocol = SecurityProtocolType.Tls12;
// Configure Request
WebRequest request = WebRequest.Create(uploadURL);
request.Method = "POST";
request.ContentType = "application/x-www-form-urlencoded";
request.ContentLength = data.Length;
// Write Data
using (Stream stream = request.GetRequestStream())
{
stream.Write(data, 0, data.Length);
}
// Get Response
string responseContent = null;
using (WebResponse response = request.GetResponse())
{
using (Stream stream = response.GetResponseStream())
{
using (StreamReader sr99 = new StreamReader(stream))
{
responseContent = sr99.ReadToEnd();
}
}
}
Console.WriteLine(responseContent);
}
}
}
Inferring on an Image Hosted Elsewhere via URL
using System;
using System.IO;
using System.Net;
using System.Web;
namespace InferenceHosted
{
class InferenceHosted
{
static void Main(string[] args)
{
string API_KEY = ""; // Your API Key
string imageURL = "https://i.ibb.co/jzr27x0/YOUR-IMAGE.jpg";
string MODEL_ENDPOINT = "dataset/v"; // Set model endpoint
// Construct the URL
string uploadURL =
"https://detect.roboflow.com/" + MODEL_ENDPOINT
+ "?api_key=" + API_KEY
+ "&image=" + HttpUtility.UrlEncode(imageURL);
// Service Point Config
ServicePointManager.Expect100Continue = true;
ServicePointManager.SecurityProtocol = SecurityProtocolType.Tls12;
// Configure Http Request
WebRequest request = WebRequest.Create(uploadURL);
request.Method = "POST";
request.ContentType = "application/x-www-form-urlencoded";
request.ContentLength = 0;
// Get Response
string responseContent = null;
using (WebResponse response = request.GetResponse())
{
using (Stream stream = response.GetResponseStream())
{
using (StreamReader sr99 = new StreamReader(stream))
{
responseContent = sr99.ReadToEnd();
}
}
}
Console.WriteLine(responseContent);
}
}
}
We are adding code snippets as they are requested by users. If you'd like to integrate the inference API into your Elixir app, please click here to record your upvote.
Response Object Format
The hosted API inference route returns a JSON object containing an array of predictions. Each prediction has the following properties:
x = the horizontal center point of the detected object
y = the vertical center point of the detected object
width = the width of the bounding box
height = the height of the bounding box
class = the class label of the detected object
confidence = the model's confidence that the detected object has the correct label and position coordinates
keypoints = an array of keypoint predictions
x = horizontal center of keypoint (relative to image top-left corner)
y = vertical center of keypoint (relative to image top-left corner)
class_name = name of keypoint
class_id = id of keypoint, maps to skeleton vertices in version record, to map vertex color and skeleton edges, View your Project Version
confidence = confidence that the keypoint has correct position, and is visible (not occluded or deleted)
Here is an example response object from the REST API:
You can POST a base64 encoded image directly to your model endpoint. Or you can pass a URL as the image parameter in the query string if your image is already hosted elsewhere.
Path Parameters
Name
Type
Description
datasetSlug
string
The url-safe version of the dataset name. You can find it in the web UI by looking at the URL on the main project view or by clicking the "Get curl command" button in the train results section of your dataset version after training your model.
version
number
The version number identifying the version of of your dataset
Query Parameters
Name
Type
Description
image
string
URL of the image to add. Use if your image is hosted elsewhere. (Required when you don't POST a base64 encoded image in the request body.)
Note: don't forget to URL-encode it.
classes
string
Restrict the predictions to only those of certain classes. Provide as a comma-separated string.
Example: dog,cat
Default: not present (show all classes)
overlap
number
The maximum percentage (on a scale of 0-100) that bounding box predictions of the same class are allowed to overlap before being combined into a single box.
Default: 30
confidence
number
A threshold for the returned predictions on a scale of 0-100. A lower number will return more predictions. A higher number will return fewer high-certainty predictions.
Default: 40
stroke
number
The width (in pixels) of the bounding box displayed around predictions (only has an effect when format is image).
Default: 1
labels
boolean
Whether or not to display text labels on the predictions (only has an effect when format is image).
Default: false
format
string
json - returns an array of JSON predictions. (See response format tab).
image - returns an image with annotated predictions as a binary blob with a Content-Type of image/jpeg. image_and_json - returns an array of JSON predictions, including a visualization field in base64.
Default: json
api_key
string
Your API key (obtained via your workspace API settings page)
Request Body
Name
Type
Description
string
A base64 encoded image. (Required when you don't pass an image URL in the query parameters).
