/*
* Copyright (c) 2011-2016, Peter Abeles. All Rights Reserved.
*
* This file is part of BoofCV (http://boofcv.org).
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://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.
*/
package boofcv.deepboof;
import boofcv.struct.image.GrayF32;
import boofcv.struct.image.Planar;
/**
* @author Peter Abeles
*/
public class TestImageClassifierNiNImageNet extends CheckBaseImageClassifier {
int width = ImageClassifierNiNImageNet.imageCrop;
int height = ImageClassifierNiNImageNet.imageCrop;
@Override
public Planar<GrayF32> createImage() {
return new Planar<>(GrayF32.class,width,height,3);
}
@Override
public BaseImageClassifier createClassifier() {
ImageClassifierNiNImageNet nin = new ImageClassifierNiNImageNet();
// dummy normalization
nin.mean = new float[width*height];
nin.stdev = new float[width*height];
for (int i = 0; i < nin.mean.length; i++) {
nin.mean[i] = rand.nextFloat()*30+110;
nin.stdev[i] = 120;
}
return nin;
}
}