
org.nd4j.evaluation.serde.ConfusionMatrixDeserializer Maven / Gradle / Ivy
/*******************************************************************************
* Copyright (c) 2015-2018 Skymind, Inc.
*
* This program and the accompanying materials are made available under the
* terms of the Apache License, Version 2.0 which is available at
* https://www.apache.org/licenses/LICENSE-2.0.
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS, WITHOUT
* WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the
* License for the specific language governing permissions and limitations
* under the License.
*
* SPDX-License-Identifier: Apache-2.0
******************************************************************************/
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;
/**
* A JSON deserializer for {@code ConfusionMatrix} instances, used in {@link org.deeplearning4j.eval.Evaluation}
*
* @author Alex Black
*/
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;
}
}
© 2015 - 2025 Weber Informatics LLC | Privacy Policy