Image Annotation via openimaj - Java Machine Learning AI

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Description

Image Annotation via openimaj

Demo Code

import clarifai2.api.ClarifaiBuilder;
import clarifai2.api.ClarifaiClient;
import clarifai2.api.ClarifaiResponse;
import clarifai2.dto.input.ClarifaiInput;
import clarifai2.dto.input.image.ClarifaiImage;
import clarifai2.dto.model.output.ClarifaiOutput;
import clarifai2.dto.prediction.Concept;
import okhttp3.OkHttpClient;
import org.openimaj.image.DisplayUtilities;
import org.openimaj.image.ImageUtilities;
import org.openimaj.image.MBFImage;
import org.openimaj.image.colour.RGBColour;
import org.openimaj.image.typography.hershey.HersheyFont;

import java.io.File;
import java.io.IOException;
import java.util.List;
import java.io.FileWriter;


public class ImageAnnotation {
    public static void main(String[] args) throws IOException {
        final ClarifaiClient client = new ClarifaiBuilder(
                "key",
                "key").client(
                new OkHttpClient()) // OPTIONAL. Allows customization of OkHttp by the user
                .buildSync(); // or use .build() to get a Future<ClarifaiClient>
        client.getToken();/*from w  w w .ja  va 2s.c o  m*/

        File file = new File("output/mainframes");
        File[] files = file.listFiles();
        String[][] arr = new String[50][50];
        File fileop = new File("harry.txt");
        FileWriter fileWriter = new FileWriter(fileop);
        for (int i = 0; i < files.length; i++) {
            ClarifaiResponse response = client
                    .getDefaultModels()
                    .generalModel()
                    .predict()
                    .withInputs(
                            ClarifaiInput.forImage(ClarifaiImage
                                    .of(files[i]))).executeSync();
            List<ClarifaiOutput<Concept>> predictions = (List<ClarifaiOutput<Concept>>) response
                    .get();
            MBFImage image = ImageUtilities.readMBF(files[i]);
            int x = image.getWidth();
            int y = image.getHeight();

            System.out.println(files[i]);
            List<Concept> data = predictions.get(0).data();
            System.out.println(data);
            for (int j = 0; j < data.size(); j++) {
                fileWriter.write(data.get(j).name() + "\n");

                System.out.println(data.get(j).name() + " - "
                        + data.get(j).value());
                image.drawText(data.get(j).name(),
                        (int) Math.floor(Math.random() * x),
                        (int) Math.floor(Math.random() * y),
                        HersheyFont.ASTROLOGY, 20, RGBColour.RED);
            }
            System.out.println("Top 6 words in each frame are");

            for (int k = 0; k < 6; k++) {
                arr[i][k] = data.get(k).name();
                System.out.println(arr[i][k]);
                System.out.println("\t");
            }
            DisplayUtilities.displayName(image, "image" + i);

        }
        fileWriter.close();
    }
}

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