org.deeplearning4j.nn.adapters.YoloModelAdapter Maven / Gradle / Ivy

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 *  * terms of the Apache License, Version 2.0 which is available at
 *  * https://www.apache.org/licenses/LICENSE-2.0.
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 *  *  information regarding copyright ownership.
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package org.deeplearning4j.nn.adapters;

import lombok.AllArgsConstructor;
import lombok.Builder;
import lombok.NoArgsConstructor;
import lombok.val;
import org.deeplearning4j.nn.api.Model;
import org.deeplearning4j.nn.api.ModelAdapter;
import org.deeplearning4j.nn.graph.ComputationGraph;
import org.deeplearning4j.nn.layers.objdetect.DetectedObject;
import org.deeplearning4j.nn.layers.objdetect.Yolo2OutputLayer;
import org.nd4j.linalg.api.ndarray.INDArray;
import org.nd4j.linalg.exception.ND4JIllegalStateException;

import java.util.List;

@Builder
@AllArgsConstructor
@NoArgsConstructor
public class YoloModelAdapter implements ModelAdapter> {
    @Builder.Default private int outputLayerIndex = 0;
    @Builder.Default private int outputIndex = 0;
    @Builder.Default private double detectionThreshold = 0.5;

    @Override
    public List apply(Model model, INDArray[] inputs, INDArray[] masks, INDArray[] labelsMasks) {
        if (model instanceof ComputationGraph) {
            val blindLayer = ((ComputationGraph) model).getOutputLayer(outputLayerIndex);
            if (blindLayer instanceof Yolo2OutputLayer) {
                val output = ((ComputationGraph) model).output(false, inputs, masks, labelsMasks);
                return ((Yolo2OutputLayer) blindLayer).getPredictedObjects(output[outputIndex], detectionThreshold);
            } else {
                throw new ND4JIllegalStateException("Output layer with index [" + outputLayerIndex + "] is NOT Yolo2OutputLayer");
            }
        } else
            throw new ND4JIllegalStateException("Yolo2 model must be ComputationGraph");
    }

    @Override
    public List apply(INDArray... outputs) {
        throw new UnsupportedOperationException("Please use apply(Model, INDArray[], INDArray[]) signature");
    }
}