/* * 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; } }