Synthetic Corrosion

Synthetic Corrosion Dataset

Synthetic Corrosion Dataset



Drop Image


Paste YouTube / Image URL

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

objects detected

How to Deploy the Synthetic Corrosion Dataset Classification API

Using Roboflow, you can deploy your classification 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.

Hosted API
## Infer on Local and Hosted Images To install dependencies, `pip install roboflow` ``` from roboflow import Roboflow rf = Roboflow(api_key="API_KEY") project = rf.workspace().project("MODEL_ENDPOINT") model = project.version(VERSION).model # infer on a local image print(model.predict("your_image.jpg").json()) # infer on an image hosted elsewhere print(model.predict("URL_OF_YOUR_IMAGE", hosted=True).json()) # save an image annotated with your predictions model.predict("your_image.jpg").save("prediction.jpg") ```
## Node.js We're using [axios]( to perform the POST request in this example so first run npm install axios to install the dependency. ### Inferring on a Local Image ``` const axios = require("axios"); const fs = require("fs"); const image = fs.readFileSync("YOUR_IMAGE.jpg", { encoding: "base64" }); axios({ method: "POST", url: "", params: { api_key: "API_KEY" }, data: image, headers: { "Content-Type": "application/x-www-form-urlencoded" } }) .then(function(response) { console.log(; }) .catch(function(error) { console.log(error.message); }); ```
## Uploading a Local Image Using base64 ``` import UIKit // Load Image and Convert to Base64 let image = UIImage(named: "your-image-path") // path to image to upload ex: image.jpg let imageData = image?.jpegData(compressionQuality: 1) let fileContent = imageData?.base64EncodedString() let postData = fileContent!.data(using: .utf8) // Initialize Inference Server Request with API_KEY, Model, and Model Version var request = URLRequest(url: URL(string: "")!,timeoutInterval: Double.infinity) request.addValue("application/x-www-form-urlencoded", forHTTPHeaderField: "Content-Type") request.httpMethod = "POST" request.httpBody = postData // Execute Post Request URLSession.shared.dataTask(with: request, completionHandler: { data, response, error in // Parse Response to String guard let data = data else { print(String(describing: error)) return } // Convert Response String to Dictionary do { let dict = try JSONSerialization.jsonObject(with: data, options: []) as? [String: Any] } catch { print(error.localizedDescription) } // Print String Response print(String(data: data, encoding: .utf8)!) }).resume() ```