ai.djl.modality.cv.translator.BigGANTranslator Maven / Gradle / Ivy

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/*
 * Copyright 2021 Amazon.com, Inc. or its affiliates. All Rights Reserved.
 *
 * Licensed under the Apache License, Version 2.0 (the "License"). You may not use this file except in compliance
 * with the License. A copy of the License is located at
 *
 * http://aws.amazon.com/apache2.0/
 *
 * or in the "license" file accompanying this file. This file is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES
 * OR CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions
 * and limitations under the License.
 */
package ai.djl.modality.cv.translator;

import ai.djl.modality.cv.Image;
import ai.djl.modality.cv.ImageFactory;
import ai.djl.ndarray.NDArray;
import ai.djl.ndarray.NDList;
import ai.djl.ndarray.NDManager;
import ai.djl.ndarray.types.Shape;
import ai.djl.translate.NoBatchifyTranslator;
import ai.djl.translate.TranslatorContext;

/** Built-in {@code Translator} that provides preprocessing and postprocessing for BigGAN. */
public final class BigGANTranslator implements NoBatchifyTranslator {

    private static final int NUMBER_OF_CATEGORIES = 1000;
    private static final int SEED_COLUMN_SIZE = 128;
    private float truncation;

    /**
     * Constructs a translator for BigGAN.
     *
     * @param truncation value used to scale the normal seed for BigGAN
     */
    public BigGANTranslator(float truncation) {
        this.truncation = truncation;
    }

    /** {@inheritDoc} */
    @Override
    public Image[] processOutput(TranslatorContext ctx, NDList list) {
        NDArray output = list.get(0).duplicate().addi(1).muli(128).clip(0, 255);
        int sampleSize = (int) output.getShape().get(0);
        Image[] images = new Image[sampleSize];

        for (int i = 0; i < sampleSize; ++i) {
            images[i] = ImageFactory.getInstance().fromNDArray(output.get(i));
        }
        return images;
    }

    /** {@inheritDoc} */
    @Override
    public NDList processInput(TranslatorContext ctx, int[] input) throws Exception {
        NDManager manager = ctx.getNDManager();

        NDArray classes = manager.create(input).oneHot(NUMBER_OF_CATEGORIES);
        NDArray seed =
                manager.truncatedNormal(new Shape(input.length, SEED_COLUMN_SIZE)).muli(truncation);

        return new NDList(seed, classes, manager.create(truncation));
    }
}