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* Added feature modules for OpenAI CLIP * Minor refactoring of utility classes * Refactored common image preprocessing logic into helper class Co-authored-by: Silvan Heller <[email protected]> Co-authored-by: Florian Spiess <[email protected]> Former-commit-id: c2315f0
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111 changes: 111 additions & 0 deletions
111
cineast-core/src/main/java/org/vitrivr/cineast/core/features/CLIPImage.java
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,111 @@ | ||
| package org.vitrivr.cineast.core.features; | ||
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| import org.apache.logging.log4j.LogManager; | ||
| import org.apache.logging.log4j.Logger; | ||
| import org.tensorflow.SavedModelBundle; | ||
| import org.tensorflow.Tensor; | ||
| import org.tensorflow.ndarray.Shape; | ||
| import org.tensorflow.ndarray.buffer.DataBuffers; | ||
| import org.tensorflow.ndarray.buffer.FloatDataBuffer; | ||
| import org.tensorflow.types.TFloat16; | ||
| import org.vitrivr.cineast.core.config.QueryConfig; | ||
| import org.vitrivr.cineast.core.config.ReadableQueryConfig; | ||
| import org.vitrivr.cineast.core.data.FloatVectorImpl; | ||
| import org.vitrivr.cineast.core.data.frames.VideoFrame; | ||
| import org.vitrivr.cineast.core.data.score.ScoreElement; | ||
| import org.vitrivr.cineast.core.data.segments.SegmentContainer; | ||
| import org.vitrivr.cineast.core.features.abstracts.AbstractFeatureModule; | ||
| import org.vitrivr.cineast.core.util.images.ImagePreprocessingHelper; | ||
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| import java.awt.image.BufferedImage; | ||
| import java.util.Collections; | ||
| import java.util.HashMap; | ||
| import java.util.List; | ||
| import java.util.Map; | ||
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| public class CLIPImage extends AbstractFeatureModule { | ||
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| private static final Logger LOGGER = LogManager.getLogger(); | ||
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| private static final int EMBEDDING_SIZE = 512; | ||
| private static final String TABLE_NAME = "features_clip"; | ||
| private static final ReadableQueryConfig.Distance DISTANCE = ReadableQueryConfig.Distance.cosine; | ||
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| private static final int IMAGE_SIZE = 224; | ||
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| private static final String RESOURCE_PATH = "resources/CLIP/"; | ||
| private static final String EMBEDDING_MODEL = "clip-image-vit-32-tf"; | ||
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| private static final String EMBEDDING_INPUT = "input"; | ||
| private static final String EMBEDDING_OUTPUT = "output"; | ||
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| private static final float[] MEAN = new float[]{0.48145466f, 0.4578275f, 0.40821073f}; | ||
| private static final float[] STD = new float[]{0.26862954f, 0.26130258f, 0.27577711f}; | ||
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| private SavedModelBundle model; | ||
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| public CLIPImage() { | ||
| super(TABLE_NAME, 1f, EMBEDDING_SIZE); | ||
| model = SavedModelBundle.load(RESOURCE_PATH + EMBEDDING_MODEL); | ||
| } | ||
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| @Override | ||
| public void processSegment(SegmentContainer shot) { | ||
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| if (shot.getMostRepresentativeFrame() == VideoFrame.EMPTY_VIDEO_FRAME) { | ||
| return; | ||
| } | ||
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| float[] embeddingArray = embedImage(shot.getMostRepresentativeFrame().getImage().getBufferedImage()); | ||
| this.persist(shot.getId(), new FloatVectorImpl(embeddingArray)); | ||
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| } | ||
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| @Override | ||
| protected ReadableQueryConfig setQueryConfig(ReadableQueryConfig qc) { | ||
| return QueryConfig.clone(qc).setDistance(DISTANCE); | ||
| } | ||
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| @Override | ||
| public List<ScoreElement> getSimilar(SegmentContainer sc, ReadableQueryConfig qc) { | ||
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| if (sc.getMostRepresentativeFrame() == VideoFrame.EMPTY_VIDEO_FRAME) { | ||
| return Collections.emptyList(); | ||
| } | ||
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| QueryConfig queryConfig = QueryConfig.clone(qc); | ||
| queryConfig.setDistance(DISTANCE); | ||
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| float[] embeddingArray = embedImage(sc.getMostRepresentativeFrame().getImage().getBufferedImage()); | ||
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| return getSimilar(embeddingArray, queryConfig); | ||
| } | ||
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| private float[] embedImage(BufferedImage img) { | ||
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| float[] rgb = prepareImage(img); | ||
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| try (TFloat16 imageTensor = TFloat16.tensorOf(Shape.of(1, 3, IMAGE_SIZE, IMAGE_SIZE), DataBuffers.of(rgb))) { | ||
| HashMap<String, Tensor> inputMap = new HashMap<>(); | ||
| inputMap.put(EMBEDDING_INPUT, imageTensor); | ||
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| Map<String, Tensor> resultMap = model.call(inputMap); | ||
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| try (TFloat16 encoding = (TFloat16) resultMap.get(EMBEDDING_OUTPUT)) { | ||
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| float[] embeddingArray = new float[EMBEDDING_SIZE]; | ||
| FloatDataBuffer floatBuffer = DataBuffers.of(embeddingArray); | ||
| encoding.read(floatBuffer); | ||
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| return embeddingArray; | ||
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| } | ||
| } | ||
| } | ||
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| private static float[] prepareImage(BufferedImage img) { | ||
| return ImagePreprocessingHelper.imageToCHWArray( | ||
| ImagePreprocessingHelper.squaredScaleCenterCrop(img, IMAGE_SIZE), | ||
| MEAN, STD); | ||
| } | ||
| } |
149 changes: 149 additions & 0 deletions
149
cineast-core/src/main/java/org/vitrivr/cineast/core/features/CLIPText.java
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,149 @@ | ||
| package org.vitrivr.cineast.core.features; | ||
|
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| import org.apache.logging.log4j.LogManager; | ||
| import org.apache.logging.log4j.Logger; | ||
| import org.tensorflow.SavedModelBundle; | ||
| import org.tensorflow.Tensor; | ||
| import org.tensorflow.ndarray.LongNdArray; | ||
| import org.tensorflow.ndarray.NdArrays; | ||
| import org.tensorflow.ndarray.Shape; | ||
| import org.tensorflow.ndarray.buffer.DataBuffers; | ||
| import org.tensorflow.ndarray.buffer.FloatDataBuffer; | ||
| import org.tensorflow.types.TFloat16; | ||
| import org.tensorflow.types.TInt64; | ||
| import org.vitrivr.cineast.core.config.QueryConfig; | ||
| import org.vitrivr.cineast.core.config.ReadableQueryConfig; | ||
| import org.vitrivr.cineast.core.data.CorrespondenceFunction; | ||
| import org.vitrivr.cineast.core.data.distance.DistanceElement; | ||
| import org.vitrivr.cineast.core.data.distance.SegmentDistanceElement; | ||
| import org.vitrivr.cineast.core.data.providers.primitive.FloatArrayTypeProvider; | ||
| import org.vitrivr.cineast.core.data.providers.primitive.PrimitiveTypeProvider; | ||
| import org.vitrivr.cineast.core.data.providers.primitive.StringTypeProvider; | ||
| import org.vitrivr.cineast.core.data.score.ScoreElement; | ||
| import org.vitrivr.cineast.core.data.segments.SegmentContainer; | ||
| import org.vitrivr.cineast.core.db.DBSelector; | ||
| import org.vitrivr.cineast.core.db.DBSelectorSupplier; | ||
| import org.vitrivr.cineast.core.db.setup.EntityCreator; | ||
| import org.vitrivr.cineast.core.features.retriever.Retriever; | ||
| import org.vitrivr.cineast.core.util.text.ClipTokenizer; | ||
|
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| import java.util.Collections; | ||
| import java.util.HashMap; | ||
| import java.util.List; | ||
| import java.util.Map; | ||
| import java.util.function.Supplier; | ||
|
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| import static org.vitrivr.cineast.core.util.CineastConstants.FEATURE_COLUMN_QUALIFIER; | ||
| import static org.vitrivr.cineast.core.util.CineastConstants.GENERIC_ID_COLUMN_QUALIFIER; | ||
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| public class CLIPText implements Retriever { | ||
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| private static final Logger LOGGER = LogManager.getLogger(); | ||
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| private static final int EMBEDDING_SIZE = 512; | ||
| private static final String TABLE_NAME = "features_clip"; | ||
| private static final ReadableQueryConfig.Distance DISTANCE = ReadableQueryConfig.Distance.cosine; | ||
|
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| private static final String RESOURCE_PATH = "resources/CLIP/"; | ||
| private static final String EMBEDDING_MODEL = "clip-text-vit-32-tf"; | ||
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| private static final String EMBEDDING_INPUT = "input"; | ||
| private static final String EMBEDDING_OUTPUT = "output"; | ||
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| private static final CorrespondenceFunction CORRESPONDENCE = CorrespondenceFunction.linear(1f); | ||
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| private static SavedModelBundle model; | ||
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| private DBSelector selector; | ||
| private ClipTokenizer ct = new ClipTokenizer(); | ||
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| private static void init() { | ||
| if (model == null) { | ||
| model = SavedModelBundle.load(RESOURCE_PATH + EMBEDDING_MODEL); | ||
| } | ||
| } | ||
|
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| public CLIPText() { | ||
| init(); | ||
| } | ||
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| @Override | ||
| public void initalizePersistentLayer(Supplier<EntityCreator> supply) { | ||
| supply.get().createFeatureEntity(TABLE_NAME, true, EMBEDDING_SIZE); | ||
| } | ||
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| @Override | ||
| public void dropPersistentLayer(Supplier<EntityCreator> supply) { | ||
| supply.get().dropEntity(TABLE_NAME); | ||
| } | ||
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| @Override | ||
| public void init(DBSelectorSupplier selectorSupply) { | ||
| this.selector = selectorSupply.get(); | ||
| this.selector.open(TABLE_NAME); | ||
| } | ||
|
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| @Override | ||
| public List<ScoreElement> getSimilar(SegmentContainer sc, ReadableQueryConfig qc) { | ||
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| String text = sc.getText(); | ||
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| if (text == null || text.isBlank()) { | ||
| return Collections.emptyList(); | ||
| } | ||
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| return getSimilar(new FloatArrayTypeProvider(embedText(text)), qc); | ||
| } | ||
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| private float[] embedText(String text) { | ||
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| long[] tokens = ct.clipTokenize(text); | ||
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| LongNdArray arr = NdArrays.ofLongs(Shape.of(1, tokens.length)); | ||
| for (int i = 0; i < tokens.length; i++) { | ||
| arr.setLong(tokens[i], 0, i); | ||
| } | ||
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| try (TInt64 textTensor = TInt64.tensorOf(arr)) { | ||
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| HashMap<String, Tensor> inputMap = new HashMap<>(); | ||
| inputMap.put(EMBEDDING_INPUT, textTensor); | ||
|
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| Map<String, Tensor> resultMap = model.call(inputMap); | ||
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| try (TFloat16 embedding = (TFloat16) resultMap.get(EMBEDDING_OUTPUT)) { | ||
|
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| float[] embeddingArray = new float[EMBEDDING_SIZE]; | ||
| FloatDataBuffer floatBuffer = DataBuffers.of(embeddingArray); | ||
| embedding.read(floatBuffer); | ||
| return embeddingArray; | ||
|
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| } | ||
| } | ||
| } | ||
|
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| @Override | ||
| public List<ScoreElement> getSimilar(String segmentId, ReadableQueryConfig qc) { | ||
| List<PrimitiveTypeProvider> list = this.selector.getFeatureVectorsGeneric(GENERIC_ID_COLUMN_QUALIFIER, new StringTypeProvider(segmentId), FEATURE_COLUMN_QUALIFIER); | ||
| if (list.isEmpty()) { | ||
| LOGGER.warn("No feature vector for shotId {} found, returning empty result-list", segmentId); | ||
| return Collections.emptyList(); | ||
| } | ||
| return getSimilar(list.get(0), qc); | ||
| } | ||
|
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| private List<ScoreElement> getSimilar(PrimitiveTypeProvider queryProvider, ReadableQueryConfig qc) { | ||
| ReadableQueryConfig qcc = QueryConfig.clone(qc).setDistance(DISTANCE); | ||
| List<SegmentDistanceElement> distances = this.selector.getNearestNeighboursGeneric(qc.getResultsPerModule(), queryProvider, FEATURE_COLUMN_QUALIFIER, SegmentDistanceElement.class, qcc); | ||
| CorrespondenceFunction function = qcc.getCorrespondenceFunction().orElse(CORRESPONDENCE); | ||
| return DistanceElement.toScore(distances, function); | ||
| } | ||
|
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| @Override | ||
| public void finish() { | ||
| if (this.selector != null) { | ||
| this.selector.close(); | ||
| this.selector = null; | ||
| } | ||
| } | ||
| } |
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2 changes: 1 addition & 1 deletion
2
cineast-core/src/main/java/org/vitrivr/cineast/core/features/HOGMirflickr25K256.java
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2 changes: 1 addition & 1 deletion
2
cineast-core/src/main/java/org/vitrivr/cineast/core/features/HOGMirflickr25K512.java
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