org.nd4j.evaluation.serde.ConfusionMatrixDeserializer Maven / Gradle / Ivy
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* * terms of the Apache License, Version 2.0 which is available at
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* * information regarding copyright ownership.
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package org.nd4j.evaluation.serde;
import org.nd4j.evaluation.classification.ConfusionMatrix;
import org.nd4j.shade.jackson.core.JsonParser;
import org.nd4j.shade.jackson.core.JsonProcessingException;
import org.nd4j.shade.jackson.databind.DeserializationContext;
import org.nd4j.shade.jackson.databind.JsonDeserializer;
import org.nd4j.shade.jackson.databind.JsonNode;
import org.nd4j.shade.jackson.databind.node.ArrayNode;
import org.nd4j.shade.jackson.databind.node.ObjectNode;
import java.io.IOException;
import java.util.ArrayList;
import java.util.Iterator;
import java.util.List;
import java.util.Map;
public class ConfusionMatrixDeserializer extends JsonDeserializer> {
@Override
public ConfusionMatrix deserialize(JsonParser jp, DeserializationContext ctxt)
throws IOException, JsonProcessingException {
JsonNode n = jp.getCodec().readTree(jp);
//Get class names/labels
ArrayNode classesNode = (ArrayNode) n.get("classes");
List classes = new ArrayList<>();
for (JsonNode cn : classesNode) {
classes.add(cn.asInt());
}
ConfusionMatrix cm = new ConfusionMatrix<>(classes);
ObjectNode matrix = (ObjectNode) n.get("matrix");
Iterator> matrixIter = matrix.fields();
while (matrixIter.hasNext()) {
Map.Entry e = matrixIter.next();
int actualClass = Integer.parseInt(e.getKey());
ArrayNode an = (ArrayNode) e.getValue();
ArrayNode innerMultiSetKey = (ArrayNode) an.get(0);
ArrayNode innerMultiSetCount = (ArrayNode) an.get(1);
Iterator iterKey = innerMultiSetKey.iterator();
Iterator iterCnt = innerMultiSetCount.iterator();
while (iterKey.hasNext()) {
int predictedClass = iterKey.next().asInt();
int count = iterCnt.next().asInt();
cm.add(actualClass, predictedClass, count);
}
}
return cm;
}
}