Examples with ToTensor ai.djl.modality.cv.transform.ToTensor used on opensource projects

Example 11 with ToTensor

use of ai.djl.modality.cv.transform.ToTensor in project djl by deepjavalibrary.

the class TrainResnetWithCifar10 method getDataset.

private static RandomAccessDataset getDataset(Dataset.Usage usage, Arguments arguments) throws IOException {
    Pipeline pipeline = new Pipeline(new ToTensor(), new Normalize(Cifar10.NORMALIZE_MEAN, Cifar10.NORMALIZE_STD));
    Cifar10 cifar10 = Cifar10.builder().optUsage(usage).setSampling(arguments.getBatchSize(), true).optLimit(arguments.getLimit()).optPipeline(pipeline).build();
    cifar10.prepare(new ProgressBar());
    return cifar10;
}

Example 12 with ToTensor

use of ai.djl.modality.cv.transform.ToTensor in project djl by deepjavalibrary.

the class TrainPikachu method getDataset.

private static RandomAccessDataset getDataset(Dataset.Usage usage, Arguments arguments) throws IOException {
    Pipeline pipeline = new Pipeline(new ToTensor());
    PikachuDetection pikachuDetection = PikachuDetection.builder().optUsage(usage).optLimit(arguments.getLimit()).optPipeline(pipeline).setSampling(arguments.getBatchSize(), true).build();
    pikachuDetection.prepare(new ProgressBar());
    return pikachuDetection;
}

Example 13 with ToTensor

use of ai.djl.modality.cv.transform.ToTensor in project djl by deepjavalibrary.

the class ProfilerTest method testProfiler.

@Test
public void testProfiler() throws MalformedModelException, ModelNotFoundException, IOException, TranslateException {
    try (NDManager manager = NDManager.newBaseManager()) {
        ImageClassificationTranslator translator = ImageClassificationTranslator.builder().addTransform(new ToTensor()).build();
        Criteria<Image, Classifications> criteria = Criteria.builder().setTypes(Image.class, Classifications.class).optApplication(Application.CV.IMAGE_CLASSIFICATION).optFilter("layers", "18").optTranslator(translator).optProgress(new ProgressBar()).build();
        String outputFile = "build/profile.json";
        try (ZooModel<Image, Classifications> model = criteria.loadModel();
            Predictor<Image, Classifications> predictor = model.newPredictor()) {
            Image image = ImageFactory.getInstance().fromNDArray(manager.zeros(new Shape(3, 224, 224), DataType.UINT8));
            JniUtils.startProfile(false, true, true);
            predictor.predict(image);
            JniUtils.stopProfile(outputFile);
        }
        Assert.assertTrue(Files.exists(Paths.get(outputFile)), "The profiler file not found!");
    }
}

Example 14 with ToTensor

use of ai.djl.modality.cv.transform.ToTensor in project djl by deepjavalibrary.

the class TrainPikachu method predict.

public static int predict(String outputDir, String imageFile) throws IOException, MalformedModelException, TranslateException {
    try (Model model = Model.newInstance("pikachu-ssd")) {
        float detectionThreshold = 0.6f;
        // load parameters back to original training block
        model.setBlock(getSsdTrainBlock());
        model.load(Paths.get(outputDir));
        // append prediction logic at end of training block with parameter loaded
        Block ssdTrain = model.getBlock();
        model.setBlock(getSsdPredictBlock(ssdTrain));
        Path imagePath = Paths.get(imageFile);
        SingleShotDetectionTranslator translator = SingleShotDetectionTranslator.builder().addTransform(new ToTensor()).optSynset(Collections.singletonList("pikachu")).optThreshold(detectionThreshold).build();
        try (Predictor<Image, DetectedObjects> predictor = model.newPredictor(translator)) {
            Image image = ImageFactory.getInstance().fromFile(imagePath);
            DetectedObjects detectedObjects = predictor.predict(image);
            image.drawBoundingBoxes(detectedObjects);
            Path out = Paths.get(outputDir).resolve("pikachu_output.png");
            image.save(Files.newOutputStream(out), "png");
            // return number of pikachu detected
            return detectedObjects.getNumberOfObjects();
        }
    }
}

Example 15 with ToTensor

use of ai.djl.modality.cv.transform.ToTensor in project djl by deepjavalibrary.

the class TrainResnetWithCifar10 method testSaveParameters.

private static Classifications testSaveParameters(Block block, Path path) throws IOException, ModelException, TranslateException {
    String synsetUrl = "https://mlrepo.djl.ai/model/cv/image_classification/ai/djl/mxnet/synset_cifar10.txt";
    ImageClassificationTranslator translator = ImageClassificationTranslator.builder().addTransform(new ToTensor()).addTransform(new Normalize(Cifar10.NORMALIZE_MEAN, Cifar10.NORMALIZE_STD)).optSynsetUrl(synsetUrl).optApplySoftmax(true).build();
    Image img = ImageFactory.getInstance().fromUrl("src/test/resources/airplane1.png");
    Criteria<Image, Classifications> criteria = Criteria.builder().setTypes(Image.class, Classifications.class).optModelPath(path).optTranslator(translator).optBlock(block).optModelName("resnetv1").build();
    try (ZooModel<Image, Classifications> model = criteria.loadModel();
        Predictor<Image, Classifications> predictor = model.newPredictor()) {
        return predictor.predict(img);
    }
}