Image embedding in Java
The current project attempts to develop a pure Java image encoder that can be used in pure Java or Android program. Such an image encoder can be used for image classification or image search, or image recommend-er.
The current project contains currently two deep learning networks:
- inception resnet
- cifar
The sample codes below shows how to use the cifar image classifier to predict the genres of image:
import com.github.chen0040.tensorflow.classifiers.models.cifar10.Cifar10ImageClassifier; import com.github.chen0040.tensorflow.classifiers.utils.ResourceUtils; import org.slf4j.Logger; import org.slf4j.LoggerFactory; import java.io.File; import java.io.IOException; import java.io.InputStream; import java.util.ArrayList; import java.util.Collections; import java.util.List; public class Demo { public static void main(String[] args) { InputStream inputStream = ResourceUtils.getInputStream("tf_models/cnn_cifar10.pb"); Cifar10ImageClassifier classifier = new Cifar10ImageClassifier(); classifier.load_model(inputStream); List<String> paths = getImageFiles(); Collections.shuffle(paths); for (String path : paths) { System.out.println("Predicting " + path + " ..."); File f = new File(path); String label = classifier.predict_image(f); System.out.println("Predicted: " + label); } } }
The sample codes below shows how to use the resnet v2 image classifier to predict the genres of image:
import com.github.chen0040.tensorflow.classifiers.images.models.inception.InceptionImageClassifier; import com.github.chen0040.tensorflow.classifiers.images.utils.ResourceUtils; import org.slf4j.Logger; import org.slf4j.LoggerFactory; import java.io.File; import java.io.IOException; import java.io.InputStream; import java.util.ArrayList; import java.util.Collections; import java.util.List; public class Demo { public static void main(String[] args){ InceptionImageClassifier classifier = new InceptionImageClassifier(); classifier.load_model(); List<String> paths = getImageFiles(); Collections.shuffle(paths); for (String path : paths) { System.out.println("Predicting " + path + " ..."); File f = new File(path); String label = classifier.predict_image(f); System.out.println("Predicted: " + label); } } }
The sample codes below shows how to use the cifar image classifier to encode an image file into an float array:
import com.github.chen0040.tensorflow.classifiers.images.models.cifar10.Cifar10ImageClassifier; import com.github.chen0040.tensorflow.classifiers.images.utils.ResourceUtils; import org.slf4j.Logger; import org.slf4j.LoggerFactory; import java.io.File; import java.io.IOException; import java.io.InputStream; import java.util.ArrayList; import java.util.Collections; import java.util.List; public class Demo { public static void main(String[] args) { InputStream inputStream = ResourceUtils.getInputStream("tf_models/cnn_cifar10.pb"); Cifar10ImageClassifier classifier = new Cifar10ImageClassifier(); classifier.load_model(inputStream); List<String> paths = getImageFiles(); Collections.shuffle(paths); for (String path : paths) { System.out.println("Encoding " + path + " ..."); File f = new File(path); float[] encoded_image = classifier.encode_image(f); System.out.println("Encoded: " + Arrays.toString(encoded_image)); } } }
The sample codes below shows how to the resnet v2 image classifier to encode an image file into an float array:
import com.github.chen0040.tensorflow.classifiers.images.models.inception.InceptionImageClassifier; import com.github.chen0040.tensorflow.classifiers.images.models.utils.ResourceUtils; import org.slf4j.Logger; import org.slf4j.LoggerFactory; import java.io.File; import java.io.IOException; import java.io.InputStream; import java.util.ArrayList; import java.util.Collections; import java.util.List; public class Demo { public static void main(String[] args) { InceptionImageClassifier classifier = new InceptionImageClassifier(); classifier.load_model(); List<String> paths = getImageFiles(); Collections.shuffle(paths); for (String path : paths) { System.out.println("Encoding " + path + " ..."); File f = new File(path); float[] encoded_image = classifier.encode_image(f); System.out.println("Encoded: " + Arrays.toString(encoded_image)); } } }
The sample codes below shows how to index and search for image file using the ImageSearchEngine class:
import com.github.chen0040.tensorflow.classifiers.images.utils.FileUtils; import com.github.chen0040.tensorflow.search.models.ImageSearchEngine; import com.github.chen0040.tensorflow.search.models.ImageSearchEngineInception; import com.github.chen0040.tensorflow.search.models.ImageSearchEntry; import java.io.File; import java.util.List; public class Demo { public static void main(String[] args){ ImageSearchEngine searchEngine = new ImageSearchEngineInception(); if(!searchEngine.loadIndexDbIfExists()) { searchEngine.indexAll(FileUtils.getImageFiles()); searchEngine.saveIndexDb(); } int pageIndex = 0; int pageSize = 20; boolean skipPerfectMatch = true; for(File f : FileUtils.getImageFiles()) { System.out.println("querying similar image to " + f.getName()); List<ImageSearchEntry> result = searchEngine.query(f, pageIndex, pageSize, skipPerfectMatch); for(int i=0; i < result.size(); ++i){ System.out.println("# " + i + ": " + result.get(i).getPath() + " (distSq: " + result.get(i).getDistanceSq() + ")"); } } } }
The sample codes below shows how to recommend images based on user's image history using the KnnImageRecommender class:
import com.github.chen0040.tensorflow.classifiers.images.utils.FileUtils; import com.github.chen0040.tensorflow.recommenders.models.ImageUserHistory; import com.github.chen0040.tensorflow.recommenders.models.KnnImageRecommender; import com.github.chen0040.tensorflow.search.models.ImageSearchEntry; import java.util.Collections; import java.util.List; public class Demo { public static void main(String[] args){ ImageUserHistory userHistory = new ImageUserHistory(); List<String> imageFiles = FileUtils.getImageFilePaths(); Collections.shuffle(imageFiles); for(int i=0; i < 40; ++i){ String filePath = imageFiles.get(i); userHistory.logImage(filePath); try { Thread.sleep(100L); } catch (InterruptedException e) { e.printStackTrace(); } } KnnImageRecommender recommender = new KnnImageRecommender(); if(!recommender.loadIndexDbIfExists()) { recommender.indexAll(new File("image_samples").listFiles(a -> a.getAbsolutePath().toLowerCase().endsWith(".au"))); recommender.saveIndexDb(); } System.out.println(userHistory.head(10)); int k = 10; List<ImageSearchEntry> result = recommender.recommends(userHistory.getHistory(), k); for(int i=0; i < result.size(); ++i){ ImageSearchEntry entry = result.get(i); System.out.println("Search Result #" + (i+1) + ": " + entry.getPath()); } } }