Examples with NDArray ai.djl.ndarray.NDArray used on opensource projects

Example 1 with NDArray

use of ai.djl.ndarray.NDArray in project djl-demo by deepjavalibrary.

the class CSVDataset method encodeData.

/**
 * Convert the URL string to NDArray encoded form
 *
 * @param manager NDManager for NDArray context
 * @param url URL in string format
 */
private NDArray encodeData(NDManager manager, String url) {
    NDArray encoded = manager.zeros(new Shape(alphabets.size(), FEATURE_LENGTH));
    char[] arrayText = url.toCharArray();
    for (int i = 0; i < url.length(); i++) {
        if (i > FEATURE_LENGTH) {
            break;
        }
        if (alphabetsIndex.containsKey(arrayText[i])) {
            encoded.set(new NDIndex(alphabetsIndex.get(arrayText[i]), i), 1);
        }
    }
    return encoded;
}

Example 2 with NDArray

use of ai.djl.ndarray.NDArray in project djl-demo by deepjavalibrary.

the class URLTranslator method processOutput.

/**
 * Converts the Output NDArray (classification labels) to Classifications object for easy
 * formatting.
 *
 * @param ctx context of the translator.
 * @param list NDlist of prediction output
 * @return returns a Classifications objects
 */
@Override
public Classifications processOutput(TranslatorContext ctx, NDList list) {
    NDArray array = list.get(0);
    NDArray pred = array.softmax(-1);
    List<String> labels = new ArrayList<>();
    labels.add("benign");
    labels.add("malicious");
    return new Classifications(labels, pred);
}

Example 3 with NDArray

use of ai.djl.ndarray.NDArray in project djl-demo by deepjavalibrary.

the class FaceDetectionTranslator method processInput.

@Override
public NDList processInput(TranslatorContext ctx, Image input) {
    width = input.getWidth();
    height = input.getHeight();
    NDArray array = input.toNDArray(ctx.getNDManager(), Image.Flag.COLOR);
    // HWC -> CHW RGB -> BGR
    array = array.transpose(2, 0, 1).flip(0);
    // The network by default takes float32
    if (!array.getDataType().equals(DataType.FLOAT32)) {
        array = array.toType(DataType.FLOAT32, false);
    }
    NDArray mean = ctx.getNDManager().create(new float[] { 104f, 117f, 123f }, new Shape(3, 1, 1));
    array = array.sub(mean);
    NDList list = new NDList(array);
    return list;
}

Example 4 with NDArray

use of ai.djl.ndarray.NDArray 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 NDArray

use of ai.djl.ndarray.NDArray in project djl-serving by deepjavalibrary.

the class PyEngineTest method testEchoModel.

@Test
public void testEchoModel() throws TranslateException, IOException, ModelException {
    // Echo model doesn't support initialize
    Criteria<NDList, NDList> criteria = Criteria.builder().setTypes(NDList.class, NDList.class).optModelPath(Paths.get("src/test/resources/echo")).optTranslator(new NoopTranslator()).optEngine("Python").build();
    try (ZooModel<NDList, NDList> model = criteria.loadModel();
        Predictor<NDList, NDList> predictor = model.newPredictor()) {
        NDArray x = model.getNDManager().create(new float[] { 1 });
        NDList ret = predictor.predict(new NDList(x));
        float[] expected = { 1 };
        float[] actual = ret.head().toFloatArray();
        Assert.assertEquals(actual, expected);
    }
}