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

Example 1 with ToTensor

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

the class CanaryTest method testDlr.

private static void testDlr() throws ModelException, IOException, TranslateException {
    String os;
    if (System.getProperty("os.name").toLowerCase().startsWith("mac")) {
        os = "osx";
    } else if (System.getProperty("os.name").toLowerCase().startsWith("linux")) {
        os = "linux";
    } else {
        throw new AssertionError("DLR only work on mac and Linux.");
    }
    ImageClassificationTranslator translator = ImageClassificationTranslator.builder().addTransform(new Resize(224, 224)).addTransform(new ToTensor()).build();
    Criteria<Image, Classifications> criteria = Criteria.builder().setTypes(Image.class, Classifications.class).optApplication(Application.CV.IMAGE_CLASSIFICATION).optFilter("layers", "50").optFilter("os", os).optTranslator(translator).optEngine("DLR").optProgress(new ProgressBar()).build();
    String url = "https://resources.djl.ai/images/kitten.jpg";
    Image image = ImageFactory.getInstance().fromUrl(url);
    try (ZooModel<Image, Classifications> model = ModelZoo.loadModel(criteria);
        Predictor<Image, Classifications> predictor = model.newPredictor()) {
        Classifications classifications = predictor.predict(image);
        logger.info("{}", classifications);
    }
}

Example 2 with ToTensor

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

the class Inference method main.

public static void main(String[] args) throws ModelException, TranslateException, IOException {
    // the location where the model is saved
    Path modelDir = Paths.get("models");
    // the path of image to classify
    String imageFilePath;
    if (args.length == 0) {
        imageFilePath = "ut-zap50k-images-square/Sandals/Heel/Annie/7350693.3.jpg";
    } else {
        imageFilePath = args[0];
    }
    // Load the image file from the path
    Image img = ImageFactory.getInstance().fromFile(Paths.get(imageFilePath));
    try (Model model = Models.getModel()) {
        // empty model instance
        // load the model
        model.load(modelDir, Models.MODEL_NAME);
        // define a translator for pre and post processing
        // out of the box this translator converts images to ResNet friendly ResNet 18 shape
        Translator<Image, Classifications> translator = ImageClassificationTranslator.builder().addTransform(new Resize(Models.IMAGE_WIDTH, Models.IMAGE_HEIGHT)).addTransform(new ToTensor()).optApplySoftmax(true).build();
        // run the inference using a Predictor
        try (Predictor<Image, Classifications> predictor = model.newPredictor(translator)) {
            // holds the probability score per label
            Classifications predictResult = predictor.predict(img);
            System.out.println(predictResult);
        }
    }
}

Example 3 with ToTensor

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

the class PissAI method checkImage.

public JsonObject checkImage(Image image, Model model, List<String> classes) throws TranslateException {
    Translator<Image, Classifications> translator = ImageClassificationTranslator.builder().addTransform(new Resize(256, 256)).addTransform(new ToTensor()).optSynset(classes).optApplySoftmax(true).build();
    Predictor<Image, Classifications> predictor = model.newPredictor(translator);
    Classifications classifications = predictor.predict(image);
    JsonElement jsonElement = JsonParser.parseString(classifications.toJson());
    if (jsonElement.isJsonArray()) {
        JsonArray jsonArray = jsonElement.getAsJsonArray();
        JsonObject detected = new JsonObject();
        float highestValue = 0.0f;
        for (int i = 0; i < jsonArray.size(); i++) {
            JsonElement jsonElement1 = jsonArray.get(i);
            if (jsonElement1.isJsonObject()) {
                JsonObject jsonObject = jsonElement1.getAsJsonObject();
                String name = jsonObject.get("className").getAsString();
                float currentValue = jsonObject.get("probability").getAsFloat();
                System.out.println(name + " - " + Math.round(currentValue * 100) + "%");
                if (highestValue < currentValue) {
                    highestValue = currentValue;
                    detected = jsonObject;
                }
            }
        }
        return detected;
    }
    return new JsonObject();
}

Example 4 with ToTensor

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

the class PissAI method runTest.

public void runTest(Model model, List<String> classes, boolean valid) throws IOException, TranslateException {
    String validImage = "https://upload.wikimedia.org/wikipedia/en/thumb/1/1d/Dream_icon.svg/1200px-Dream_icon.svg.png";
    String invalidImage = "https://upload.wikimedia.org/wikipedia/commons/thumb/2/25/Red.svg/2048px-Red.svg.png";
    String imageUrl = valid ? validImage : invalidImage;
    Image imageToCheck = ImageFactory.getInstance().fromUrl(imageUrl);
    imageToCheck = ImageFactory.getInstance().fromNDArray(imageToCheck.toNDArray(NDManager.newBaseManager()).squeeze());
    Object wrappedImage = imageToCheck.getWrappedImage();
    Translator<Image, Float> translator = BinaryImageTranslator.builder().addTransform(new Resize(256, 256)).addTransform(new ToTensor()).addTransform(NDArray::squeeze).optApplySoftmax(true).build();
    Predictor<Image, Float> predictor = model.newPredictor(translator);
    float classifications = predictor.predict(imageToCheck);
    /*JsonElement jsonElement = JsonParser.parseString(classifications.toJson());

        if (jsonElement.isJsonArray()) {
            JsonArray jsonArray = jsonElement.getAsJsonArray();

            String detected = "";
            float highestValue = 0.0f;

            for (int i = 0; i < jsonArray.size(); i++) {
                JsonElement jsonElement1 = jsonArray.get(i);
                if (jsonElement1.isJsonObject()) {
                    JsonObject jsonObject = jsonElement1.getAsJsonObject();

                    String name = jsonObject.get("className").getAsString();
                    float currentValue = jsonObject.get("probability").getAsFloat();

                    System.out.println(name + " - " + Math.round(currentValue * 100) + "%");

                    if (highestValue < currentValue) {
                        highestValue = currentValue;
                        detected = name;
                    }
                }
              }
            }*/
    System.out.println("It is most likely dream, about " + Math.round(classifications * 100) + "%");
}

Example 5 with ToTensor

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

the class ModelTrainer method createDataSet.

public ImageFolder createDataSet() throws TranslateException, IOException {
    int batchSize = 32;
    // set the image folder path
    Repository repository = Repository.newInstance("folder", Paths.get("imagefolder"));
    ImageFolder dataset = ImageFolder.builder().setRepository(repository).addTransform(new Resize(256, 256)).addTransform(new ToTensor()).setSampling(batchSize, true).build();
    // call prepare before using
    dataset.prepare();
    return dataset;
}