Tanaka Kakeru


Instance Segmentation

View Model Graphs

Samples from Test Set

Upload Image

Drop files here or

Paste YouTube or Image URL

Try On My Machine

Try this model on images, video, or use your webcam

objects detected
Label Display Mode:
Roboflow Inference

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

How to Deploy the clothes_class 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
## 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); }); ```