Picture ML Tool

Basic Flutter app that saves the boilerplate code to upload annotated images for your machine learning projects.

Screenshot

Getting Started

Clone the repository and open it with Android Studio.

Run the project.

The app sends image and annotation (optionally) as form multi-part.

The image use form file name "file" and the annotation text, "annotation".

If the backend send a 2xx code, the app show the "Success" dialog. In another case, "Error" with the status code.

Available in Google Play

If you prefer, you can install directly from Google Play.

PIC ML Tool - Google Play

Example backend

To test it you can use this simple backend written in NodeJS

var http = require('http');
var formidable = require('formidable');
var fs = require('fs');

const PORT = 8080;

console.log("Pic ML Tool - Example backend in node.js");
console.log("Listening in: " + PORT);

http.createServer(function (req, res) {
  if (req.method != "POST") {
    res.writeHead(405);
    res.end();
    return;
  }
  var form = new formidable.IncomingForm();
  form.parse(req, function (err, fields, files) {
    if (!('file' in files)) {
      res.writeHead(404)
      res.end();
      return;
    }
    var f = files['file'];
    console.log("File: \""+ f.name +"\" (" + f.size + " bytes)");
    if ('annotation' in fields) {
      console.log("Annotation: \"" + fields['annotation'] + "\"");
    }
    try {
      fs.rename(f.path, "/tmp/" + f.name, function (err) {
        if (err) throw err;
      });
    } catch (err) {
      res.writeHead(500);
      res.end();
      return;
    }
    console.log("Saved in: /tmp/" + f.name);
    res.writeHead(201)
    //res.write("Paco")
    res.end();
  })
}).listen(PORT);

If you prefer, you can clone it from its repository.

Made with Flutter

License

Apache 2.0