simple_face.ts

import * as tf from "@tensorflow/tfjs";

import type { Model, TaskProvider } from "../index.js";
import { models } from "../index.js";
import baseModel from "../models/mobileNetV2_35_alpha_2_classes.js";

export const simpleFace: TaskProvider<"image", "federated"> = {
  getTask() {
    return Promise.resolve({
      id: "simple_face",
      dataType: "image",
      displayInformation: {
        title: "Simple Face",
        summary: {
          preview:
            "Can you detect if the person in a picture is a child or an adult?",
          overview:
            "Simple face is a small subset of the public face_task dataset from Kaggle",
        },
        dataFormatInformation: "",
        dataExample:
          "https://storage.googleapis.com/deai-313515.appspot.com/example_training_data/simple_face-example.png",
        sampleDataset: {
          link: "https://storage.googleapis.com/deai-313515.appspot.com/example_training_data.tar.gz",
          instructions:
            'Opening the link should start downloading a zip file which you can unzip. Inside the "example_training_data" directory you should find the "simple_face" folder which contains the "adult" and "child" folders. To connect the data, select the Group option below and connect adults and children image groups.',
        },
      },
      trainingInformation: {
        epochs: 50,
        roundDuration: 1,
        validationSplit: 0.2,
        batchSize: 10,
        IMAGE_H: 200,
        IMAGE_W: 200,
        LABEL_LIST: ["child", "adult"],
        scheme: "federated",
        aggregationStrategy: "mean",
        minNbOfParticipants: 2,
        tensorBackend: "tfjs",
      },
    });
  },

  async getModel(): Promise<Model<"image">> {
    const model = await tf.loadLayersModel({
      load: async () => Promise.resolve(baseModel),
    });

    model.compile({
      optimizer: tf.train.sgd(0.001),
      loss: "categoricalCrossentropy",
      metrics: ["accuracy"],
    });

    return new models.TFJS("image", model);
  },
};