How to Use the v3 Detection API

Use this pre-trained v3 computer vision model to retrieve predictions with our hosted API or deploy to the edge. Learn More About Roboflow Inference

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v17
v3-kgfed/17
v17
v3-kgfed/17
Trained On: 2024-04-02-2-50am
v16
v3-kgfed/16
Trained On: 2024-04-01-4-32pm
v15
v3-kgfed/15
Trained On: 2024-04-01-4-20pm
v13
v3-kgfed/13
Trained On: 2024-03-30-5-25pm
v11
v3-kgfed/11
Trained On: 2024-03-30-9-45am
v10
v3-kgfed/10
Trained On: 2024-03-30-4-05am
v9
v3-kgfed/9
Trained On: 2024-03-30-3-21am
v6
v3-kgfed/6
Trained On: 2024-03-27-4-32am
v4
v3-kgfed/4
Trained On: 2024-03-27-4-14am
v3
v3-kgfed/3
Trained On: 2024-03-26-12-38pm
v1
v3-kgfed/1
Trained On: 2024-03-26-12-31pm
Trained On: v3-kgfed 52861 Images
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Model Type: Roboflow 3.0 Instance Segmentation (Fast)
Checkpoint: v3-kgfed/16
mAP
10.4%
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Roboflow Inference

Inference is Roboflow's open source deployment package for developer-friendly vision inference.

How to Deploy the v3 Detection API

Using Roboflow, you can deploy your object detection model to a range of environments, including:

  • Luxonis OAK
  • Raspberry Pi
  • NVIDIA Jetson
  • A Docker container
  • A web page
  • A Python script using the Roboflow SDK.

Below, we have instructions on how to use our deployment options.

Code Snippets

Hosted API
Utilities
Python
JavaScript
## Infer on Local and Hosted Images To install dependencies, `pip install inference-sdk`. Then, add the following code snippet to a Python script: ```python from inference_sdk import InferenceHTTPClient CLIENT = InferenceHTTPClient( api_url="https://outline.roboflow.com", api_key="API_KEY" ) result = CLIENT.infer(your_image.jpg, model_id="MODEL_ENDPOINT/VERSION") ``` [See the inference-sdk docs](https://inference.roboflow.com/inference_helpers/inference_sdk/)
## Node.js We're using [axios](https://github.com/axios/axios) to perform the POST request in this example so first run npm install axios to install the dependency. ### Inferring on a Local Image ```javascript const axios = require("axios"); const fs = require("fs"); const image = fs.readFileSync("YOUR_IMAGE.jpg", { encoding: "base64" }); axios({ method: "POST", url: "https://outline.roboflow.com/MODEL_ENDPOINT/VERSION", params: { api_key: "API_KEY" }, data: image, headers: { "Content-Type": "application/x-www-form-urlencoded" } }) .then(function (response) { console.log(response.data); }) .catch(function (error) { console.log(error.message); }); ``` ### Inferring on an Image Hosted Elsewhere via URL ```javascript const axios = require("axios"); axios({ method: "POST", url: "https://outline.roboflow.com/MODEL_ENDPOINT/VERSION", params: { api_key: "API_KEY", image: "IMAGE_URL" } }) .then(function (response) { console.log(response.data); }) .catch(function (error) { console.log(error.message); }); ```
More Deployment Resources
Roboflow Documentation

Look through our full documentation for more information and resources on how to utilize this model.
Example Web App

Use this model with a full fledged web application that has all sample code included.
Deploy to NVIDIA Jetson

Perform inference at the edge with a Jetson via our Docker container.
Deploy to Luxonis OAK

Perform inference at the edge with an OAK device via our Docker container.
Deploy Mobile iOS

Utilize your model on your mobile device.

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