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// Copyright 2022 The MediaPipe Authors. All Rights Reserved.
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//
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// Licensed under the Apache License, Version 2.0 (the "License");
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// you may not use this file except in compliance with the License.
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// You may obtain a copy of the License at
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//
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// http://www.apache.org/licenses/LICENSE-2.0
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//
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// Unless required by applicable law or agreed to in writing, software
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// distributed under the License is distributed on an "AS IS" BASIS,
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// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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// See the License for the specific language governing permissions and
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// limitations under the License.
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package com.google.mediapipe.tasks.audio.audioembedder;
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import android.content.Context;
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import android.os.ParcelFileDescriptor;
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import com.google.auto.value.AutoValue;
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import com.google.mediapipe.proto.CalculatorOptionsProto.CalculatorOptions;
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import com.google.mediapipe.framework.MediaPipeException;
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import com.google.mediapipe.framework.Packet;
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import com.google.mediapipe.framework.PacketGetter;
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import com.google.mediapipe.framework.ProtoUtil;
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import com.google.mediapipe.tasks.audio.audioembedder.proto.AudioEmbedderGraphOptionsProto;
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import com.google.mediapipe.tasks.audio.core.BaseAudioTaskApi;
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import com.google.mediapipe.tasks.audio.core.RunningMode;
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import com.google.mediapipe.tasks.components.containers.AudioData;
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import com.google.mediapipe.tasks.components.containers.Embedding;
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import com.google.mediapipe.tasks.components.containers.proto.EmbeddingsProto;
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import com.google.mediapipe.tasks.components.processors.EmbedderOptions;
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import com.google.mediapipe.tasks.components.utils.CosineSimilarity;
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import com.google.mediapipe.tasks.core.BaseOptions;
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import com.google.mediapipe.tasks.core.ErrorListener;
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import com.google.mediapipe.tasks.core.OutputHandler;
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import com.google.mediapipe.tasks.core.OutputHandler.PureResultListener;
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import com.google.mediapipe.tasks.core.OutputHandler.ResultListener;
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import com.google.mediapipe.tasks.core.TaskInfo;
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import com.google.mediapipe.tasks.core.TaskOptions;
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import com.google.mediapipe.tasks.core.TaskRunner;
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import com.google.mediapipe.tasks.core.proto.BaseOptionsProto;
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import java.io.File;
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import java.io.IOException;
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import java.nio.ByteBuffer;
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import java.util.Arrays;
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import java.util.Collections;
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import java.util.List;
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import java.util.Optional;
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/**
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* Performs audio embedding extraction on audio clips or audio stream.
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*
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* <p>This API expects a TFLite model with mandatory TFLite Model Metadata that contains the
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* mandatory AudioProperties of the solo input audio tensor and the optional (but recommended) label
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* items as AssociatedFiles with type TENSOR_AXIS_LABELS per output classification tensor.
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*
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* <p>Input tensor: (kTfLiteFloat32)
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*
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* <ul>
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* <li>input audio buffer of size `[batch * samples]`.
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* <li>batch inference is not supported (`batch` is required to be 1).
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* <li>for multi-channel models, the channels need be interleaved.
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* </ul>
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*
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* <p>At least one output tensor with: (kTfLiteFloat32)
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*
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* <ul>
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* <li>`N` components corresponding to the `N` dimensions of the returned feature vector for this
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* output layer.
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* <li>Either 2 or 4 dimensions, i.e. `[1 x N]` or `[1 x 1 x 1 x N]`.
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* </ul>
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*/
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public final class AudioEmbedder extends BaseAudioTaskApi {
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private static final String TAG = AudioEmbedder.class.getSimpleName();
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private static final String AUDIO_IN_STREAM_NAME = "audio_in";
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private static final String SAMPLE_RATE_IN_STREAM_NAME = "sample_rate_in";
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private static final List<String> INPUT_STREAMS =
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Collections.unmodifiableList(
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Arrays.asList(
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"AUDIO:" + AUDIO_IN_STREAM_NAME, "SAMPLE_RATE:" + SAMPLE_RATE_IN_STREAM_NAME));
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private static final List<String> OUTPUT_STREAMS =
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Collections.unmodifiableList(
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Arrays.asList(
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"EMBEDDINGS:embeddings_out", "TIMESTAMPED_EMBEDDINGS:timestamped_embeddings_out"));
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private static final int EMBEDDINGS_OUT_STREAM_INDEX = 0;
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private static final int TIMESTAMPED_EMBEDDINGS_OUT_STREAM_INDEX = 1;
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private static final String TASK_GRAPH_NAME =
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"mediapipe.tasks.audio.audio_embedder.AudioEmbedderGraph";
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private static final long MICROSECONDS_PER_MILLISECOND = 1000;
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static {
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ProtoUtil.registerTypeName(
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EmbeddingsProto.EmbeddingResult.class,
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"mediapipe.tasks.components.containers.proto.EmbeddingResult");
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}
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/**
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* Creates an {@link AudioEmbedder} instance from a model file and default {@link
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* AudioEmbedderOptions}.
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*
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* @param context an Android {@link Context}.
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* @param modelPath path to the embedding model in the assets.
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* @throws MediaPipeException if there is an error during {@link AudioEmbedder} creation.
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*/
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public static AudioEmbedder createFromFile(Context context, String modelPath) {
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BaseOptions baseOptions = BaseOptions.builder().setModelAssetPath(modelPath).build();
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return createFromOptions(
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context, AudioEmbedderOptions.builder().setBaseOptions(baseOptions).build());
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}
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/**
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* Creates an {@link AudioEmbedder} instance from a model file and default {@link
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* AudioEmbedderOptions}.
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*
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* @param context an Android {@link Context}.
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* @param modelFile the embedding model {@link File} instance.
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* @throws IOException if an I/O error occurs when opening the tflite model file.
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* @throws MediaPipeException if there is an error during {@link AudioEmbedder} creation.
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*/
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public static AudioEmbedder createFromFile(Context context, File modelFile) throws IOException {
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try (ParcelFileDescriptor descriptor =
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ParcelFileDescriptor.open(modelFile, ParcelFileDescriptor.MODE_READ_ONLY)) {
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BaseOptions baseOptions =
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BaseOptions.builder().setModelAssetFileDescriptor(descriptor.getFd()).build();
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return createFromOptions(
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context, AudioEmbedderOptions.builder().setBaseOptions(baseOptions).build());
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}
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}
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/**
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* Creates an {@link AudioEmbedder} instance from a model buffer and default {@link
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* AudioEmbedderOptions}.
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*
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* @param context an Android {@link Context}.
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* @param modelBuffer a direct {@link ByteBuffer} or a {@link MappedByteBuffer} of the embedding
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* model.
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* @throws MediaPipeException if there is an error during {@link AudioEmbedder} creation.
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*/
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public static AudioEmbedder createFromBuffer(Context context, final ByteBuffer modelBuffer) {
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BaseOptions baseOptions = BaseOptions.builder().setModelAssetBuffer(modelBuffer).build();
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return createFromOptions(
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context, AudioEmbedderOptions.builder().setBaseOptions(baseOptions).build());
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}
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/**
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* Creates an {@link AudioEmbedder} instance from an {@link AudioEmbedderOptions} instance.
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*
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* @param context an Android {@link Context}.
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* @param options an {@link AudioEmbedderOptions} instance.
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* @throws MediaPipeException if there is an error during {@link AudioEmbedder} creation.
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*/
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public static AudioEmbedder createFromOptions(Context context, AudioEmbedderOptions options) {
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OutputHandler<AudioEmbedderResult, Void> handler = new OutputHandler<>();
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handler.setOutputPacketConverter(
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new OutputHandler.OutputPacketConverter<AudioEmbedderResult, Void>() {
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@Override
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public AudioEmbedderResult convertToTaskResult(List<Packet> packets) {
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try {
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if (!packets.get(EMBEDDINGS_OUT_STREAM_INDEX).isEmpty()) {
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// For audio stream mode.
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return AudioEmbedderResult.createFromProto(
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PacketGetter.getProto(
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packets.get(EMBEDDINGS_OUT_STREAM_INDEX),
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EmbeddingsProto.EmbeddingResult.getDefaultInstance()),
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packets.get(EMBEDDINGS_OUT_STREAM_INDEX).getTimestamp()
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/ MICROSECONDS_PER_MILLISECOND);
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} else {
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// For audio clips mode.
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return AudioEmbedderResult.createFromProtoList(
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PacketGetter.getProtoVector(
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packets.get(TIMESTAMPED_EMBEDDINGS_OUT_STREAM_INDEX),
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EmbeddingsProto.EmbeddingResult.parser()),
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-1);
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}
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} catch (IOException e) {
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throw new MediaPipeException(
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MediaPipeException.StatusCode.INTERNAL.ordinal(), e.getMessage());
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}
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}
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@Override
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public Void convertToTaskInput(List<Packet> packets) {
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return null;
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}
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});
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if (options.resultListener().isPresent()) {
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ResultListener<AudioEmbedderResult, Void> resultListener =
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new ResultListener<AudioEmbedderResult, Void>() {
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@Override
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public void run(AudioEmbedderResult audioEmbedderResult, Void input) {
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options.resultListener().get().run(audioEmbedderResult);
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}
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};
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handler.setResultListener(resultListener);
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}
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options.errorListener().ifPresent(handler::setErrorListener);
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// Audio tasks should not drop input audio due to flow limiting, which may cause data
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// inconsistency.
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TaskRunner runner =
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TaskRunner.create(
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context,
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TaskInfo.<AudioEmbedderOptions>builder()
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.setTaskGraphName(TASK_GRAPH_NAME)
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.setInputStreams(INPUT_STREAMS)
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.setOutputStreams(OUTPUT_STREAMS)
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.setTaskOptions(options)
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.setEnableFlowLimiting(false)
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.build(),
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handler);
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return new AudioEmbedder(runner, options.runningMode());
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}
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/**
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* Constructor to initialize an {@link AudioEmbedder} from a {@link TaskRunner} and {@link
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* RunningMode}.
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*
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* @param taskRunner a {@link TaskRunner}.
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* @param runningMode a mediapipe audio task {@link RunningMode}.
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*/
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private AudioEmbedder(TaskRunner taskRunner, RunningMode runningMode) {
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super(taskRunner, runningMode, AUDIO_IN_STREAM_NAME, SAMPLE_RATE_IN_STREAM_NAME);
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}
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/*
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* Performs embedding extraction on the provided audio clips. Only use this method when the
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* AudioEmbedder is created with the audio clips mode.
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*
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* <p>The audio clip is represented as a MediaPipe {@link AudioData} object The method accepts
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* audio clips with various length and audio sample rate. It's required to provide the
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* corresponding audio sample rate within the {@link AudioData} object.
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*
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* <p>The input audio clip may be longer than what the model is able to process in a single
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* inference. When this occurs, the input audio clip is split into multiple chunks starting at
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* different timestamps. For this reason, this function returns a vector of EmbeddingResult
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* objects, each associated with a timestamp corresponding to the start (in milliseconds) of the
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* chunk data that was extracted.
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*
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* @param audioClip a MediaPipe {@link AudioData} object for processing.
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* @throws MediaPipeException if there is an internal error.
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*/
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public AudioEmbedderResult embed(AudioData audioClip) {
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return (AudioEmbedderResult) processAudioClip(audioClip);
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}
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/*
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* Sends audio data (a block in a continuous audio stream) to perform audio embedding, and
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* the results will be available via the {@link ResultListener} provided in the
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* {@link AudioClassifierOptions}. Only use this method when the AudioEmbedder is created with
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* the audio stream mode.
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*
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* <p>The audio block is represented as a MediaPipe {@link AudioData} object. The audio data will
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* be resampled, accumulated, and framed to the proper size for the underlying model to consume.
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* It's required to provide the corresponding audio sample rate within {@link AudioData} object as
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* well as a timestamp (in milliseconds) to indicate the start time of the input audio block. The
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* timestamps must be monotonically increasing. This method will return immediately after
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* the input audio data is accepted. The results will be available in the `resultListener`
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* provided in the `AudioEmbedderOptions`. The `embedAsync` method is designed to process
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* auido stream data such as microphone input.
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*
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* <p>The input audio block may be longer than what the model is able to process in a single
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* inference. When this occurs, the input audio block is split into multiple chunks. For this
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* reason, the callback may be called multiple times (once per chunk) for each call to this
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* function.
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*
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* @param audioBlock a MediaPipe {@link AudioData} object for processing.
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* @param timestampMs the input timestamp (in milliseconds).
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* @throws MediaPipeException if there is an internal error.
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*/
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public void embedAsync(AudioData audioBlock, long timestampMs) {
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checkOrSetSampleRate(audioBlock.getFormat().getSampleRate());
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sendAudioStreamData(audioBlock, timestampMs);
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}
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/**
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* Utility function to compute <a href="https://en.wikipedia.org/wiki/Cosine_similarity">cosine
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* similarity</a> between two {@link Embedding} objects.
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*
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* @throws IllegalArgumentException if the embeddings are of different types (float vs.
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* quantized), have different sizes, or have an L2-norm of 0.
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*/
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public static double cosineSimilarity(Embedding u, Embedding v) {
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return CosineSimilarity.compute(u, v);
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}
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/** Options for setting up and {@link AudioEmbedder}. */
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@AutoValue
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public abstract static class AudioEmbedderOptions extends TaskOptions {
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/** Builder for {@link AudioEmbedderOptions}. */
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@AutoValue.Builder
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public abstract static class Builder {
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/** Sets the {@link BaseOptions} for the audio embedder task. */
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public abstract Builder setBaseOptions(BaseOptions baseOptions);
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/**
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* Sets the {@link RunningMode} for the audio embedder task. Default to the audio clips mode.
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* Image embedder has two modes:
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*
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* <ul>
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* <li>AUDIO_CLIPS: The mode for running audio embedding on audio clips. Users feed audio
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* clips to the `embed` method, and will receive the embedding results as the return
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* value.
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* <li>AUDIO_STREAM: The mode for running audio embedding on the audio stream, such as from
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* microphone. Users call `embedAsync` to push the audio data into the AudioEmbedder,
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* the embedding results will be available in the result callback when the audio
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* embedder finishes the work.
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* </ul>
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*/
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public abstract Builder setRunningMode(RunningMode runningMode);
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/**
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* Sets the optional {@link EmbedderOptions} controling embedding behavior, such as score
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* threshold, number of results, etc.
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*/
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public abstract Builder setEmbedderOptions(EmbedderOptions embedderOptions);
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/**
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* Sets the {@link ResultListener} to receive the embedding results asynchronously when the
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* audio embedder is in the audio stream mode.
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*/
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public abstract Builder setResultListener(
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PureResultListener<AudioEmbedderResult> resultListener);
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/** Sets an optional {@link ErrorListener}. */
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public abstract Builder setErrorListener(ErrorListener errorListener);
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abstract AudioEmbedderOptions autoBuild();
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/**
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* Validates and builds the {@link AudioEmbedderOptions} instance.
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*
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* @throws IllegalArgumentException if the result listener and the running mode are not
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* properly configured. The result listener should only be set when the audio embedder is
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* in the audio stream mode.
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*/
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public final AudioEmbedderOptions build() {
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AudioEmbedderOptions options = autoBuild();
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if (options.runningMode() == RunningMode.AUDIO_STREAM) {
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if (!options.resultListener().isPresent()) {
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throw new IllegalArgumentException(
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"The audio embedder is in the audio stream mode, a user-defined result listener"
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+ " must be provided in the AudioEmbedderOptions.");
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}
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} else if (options.resultListener().isPresent()) {
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throw new IllegalArgumentException(
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"The audio embedder is in the audio clips mode, a user-defined result listener"
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+ " shouldn't be provided in AudioEmbedderOptions.");
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}
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return options;
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}
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}
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abstract BaseOptions baseOptions();
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abstract RunningMode runningMode();
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abstract Optional<EmbedderOptions> embedderOptions();
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abstract Optional<PureResultListener<AudioEmbedderResult>> resultListener();
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abstract Optional<ErrorListener> errorListener();
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public static Builder builder() {
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return new AutoValue_AudioEmbedder_AudioEmbedderOptions.Builder()
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.setRunningMode(RunningMode.AUDIO_CLIPS);
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}
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/** Converts a {@link AudioEmbedderOptions} to a {@link CalculatorOptions} protobuf message. */
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@Override
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public CalculatorOptions convertToCalculatorOptionsProto() {
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BaseOptionsProto.BaseOptions.Builder baseOptionsBuilder =
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BaseOptionsProto.BaseOptions.newBuilder();
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baseOptionsBuilder.setUseStreamMode(runningMode() == RunningMode.AUDIO_STREAM);
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baseOptionsBuilder.mergeFrom(convertBaseOptionsToProto(baseOptions()));
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AudioEmbedderGraphOptionsProto.AudioEmbedderGraphOptions.Builder taskOptionsBuilder =
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AudioEmbedderGraphOptionsProto.AudioEmbedderGraphOptions.newBuilder()
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.setBaseOptions(baseOptionsBuilder);
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if (embedderOptions().isPresent()) {
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taskOptionsBuilder.setEmbedderOptions(embedderOptions().get().convertToProto());
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}
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return CalculatorOptions.newBuilder()
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.setExtension(
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AudioEmbedderGraphOptionsProto.AudioEmbedderGraphOptions.ext,
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taskOptionsBuilder.build())
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.build();
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}
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}
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}
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Jiuqiang Tang
Copybara-Service