HolisticLandmarker Java API
PiperOrigin-RevId: 586113048
This commit is contained in:
parent
a898215c52
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@ -47,13 +47,14 @@ _VISION_TASKS_JAVA_PROTO_LITE_TARGETS = [
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"//mediapipe/tasks/cc/vision/gesture_recognizer/proto:gesture_embedder_graph_options_java_proto_lite",
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"//mediapipe/tasks/cc/vision/gesture_recognizer/proto:gesture_recognizer_graph_options_java_proto_lite",
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"//mediapipe/tasks/cc/vision/gesture_recognizer/proto:hand_gesture_recognizer_graph_options_java_proto_lite",
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"//mediapipe/tasks/cc/vision/hand_detector/proto:hand_detector_graph_options_java_proto_lite",
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"//mediapipe/tasks/cc/vision/hand_landmarker/proto:hand_landmarker_graph_options_java_proto_lite",
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"//mediapipe/tasks/cc/vision/hand_landmarker/proto:hand_landmarks_detector_graph_options_java_proto_lite",
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"//mediapipe/tasks/cc/vision/holistic_landmarker/proto:holistic_landmarker_graph_options_java_proto_lite",
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"//mediapipe/tasks/cc/vision/image_classifier/proto:image_classifier_graph_options_java_proto_lite",
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"//mediapipe/tasks/cc/vision/image_embedder/proto:image_embedder_graph_options_java_proto_lite",
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"//mediapipe/tasks/cc/vision/image_segmenter/proto:image_segmenter_graph_options_java_proto_lite",
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"//mediapipe/tasks/cc/vision/image_segmenter/proto:segmenter_options_java_proto_lite",
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"//mediapipe/tasks/cc/vision/hand_detector/proto:hand_detector_graph_options_java_proto_lite",
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"//mediapipe/tasks/cc/vision/hand_landmarker/proto:hand_landmarker_graph_options_java_proto_lite",
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"//mediapipe/tasks/cc/vision/hand_landmarker/proto:hand_landmarks_detector_graph_options_java_proto_lite",
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"//mediapipe/tasks/cc/vision/object_detector/proto:object_detector_options_java_proto_lite",
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"//mediapipe/tasks/cc/vision/pose_detector/proto:pose_detector_graph_options_java_proto_lite",
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"//mediapipe/tasks/cc/vision/pose_landmarker/proto:pose_landmarker_graph_options_java_proto_lite",
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@ -67,6 +67,7 @@ cc_binary(
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"//mediapipe/tasks/cc/vision/face_landmarker:face_landmarker_graph",
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"//mediapipe/tasks/cc/vision/face_stylizer:face_stylizer_graph",
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"//mediapipe/tasks/cc/vision/gesture_recognizer:gesture_recognizer_graph",
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"//mediapipe/tasks/cc/vision/holistic_landmarker:holistic_landmarker_graph",
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"//mediapipe/tasks/cc/vision/image_classifier:image_classifier_graph",
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"//mediapipe/tasks/cc/vision/image_embedder:image_embedder_graph",
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"//mediapipe/tasks/cc/vision/image_segmenter:image_segmenter_graph",
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@ -429,6 +430,7 @@ filegroup(
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android_library(
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name = "holisticlandmarker",
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srcs = [
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"holisticlandmarker/HolisticLandmarker.java",
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"holisticlandmarker/HolisticLandmarkerResult.java",
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],
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javacopts = [
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@ -439,10 +441,20 @@ android_library(
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":core",
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"//mediapipe/framework/formats:classification_java_proto_lite",
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"//mediapipe/framework/formats:landmark_java_proto_lite",
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"//mediapipe/java/com/google/mediapipe/framework:android_framework",
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"//mediapipe/java/com/google/mediapipe/framework/image",
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"//mediapipe/tasks/cc/core/proto:base_options_java_proto_lite",
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"//mediapipe/tasks/cc/vision/face_detector/proto:face_detector_graph_options_java_proto_lite",
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"//mediapipe/tasks/cc/vision/face_landmarker/proto:face_landmarks_detector_graph_options_java_proto_lite",
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"//mediapipe/tasks/cc/vision/hand_landmarker/proto:hand_landmarks_detector_graph_options_java_proto_lite",
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"//mediapipe/tasks/cc/vision/holistic_landmarker/proto:holistic_landmarker_graph_options_java_proto_lite",
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"//mediapipe/tasks/cc/vision/pose_detector/proto:pose_detector_graph_options_java_proto_lite",
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"//mediapipe/tasks/cc/vision/pose_landmarker/proto:pose_landmarks_detector_graph_options_java_proto_lite",
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"//mediapipe/tasks/java/com/google/mediapipe/tasks/components/containers:category",
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"//mediapipe/tasks/java/com/google/mediapipe/tasks/components/containers:landmark",
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"//mediapipe/tasks/java/com/google/mediapipe/tasks/components/containers:normalized_landmark",
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"//mediapipe/tasks/java/com/google/mediapipe/tasks/core",
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"//third_party:any_java_proto",
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"//third_party:autovalue",
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"@maven//:com_google_guava_guava",
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],
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@ -0,0 +1,8 @@
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<?xml version="1.0" encoding="utf-8"?>
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<manifest xmlns:android="http://schemas.android.com/apk/res/android"
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package="com.google.mediapipe.tasks.vision.holisticlandmarker">
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<uses-sdk android:minSdkVersion="24"
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android:targetSdkVersion="30" />
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</manifest>
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@ -0,0 +1,668 @@
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// Copyright 2023 The MediaPipe Authors.
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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.vision.holisticlandmarker;
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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.formats.proto.LandmarkProto.LandmarkList;
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import com.google.mediapipe.formats.proto.LandmarkProto.NormalizedLandmarkList;
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import com.google.mediapipe.formats.proto.ClassificationProto.ClassificationList;
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import com.google.mediapipe.framework.AndroidPacketGetter;
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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.image.BitmapImageBuilder;
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import com.google.mediapipe.framework.image.ByteBufferImageBuilder;
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import com.google.mediapipe.framework.image.MPImage;
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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.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 com.google.mediapipe.tasks.vision.core.BaseVisionTaskApi;
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import com.google.mediapipe.tasks.vision.core.ImageProcessingOptions;
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import com.google.mediapipe.tasks.vision.core.RunningMode;
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import com.google.mediapipe.tasks.vision.facedetector.proto.FaceDetectorGraphOptionsProto.FaceDetectorGraphOptions;
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import com.google.mediapipe.tasks.vision.facelandmarker.proto.FaceLandmarksDetectorGraphOptionsProto.FaceLandmarksDetectorGraphOptions;
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import com.google.mediapipe.tasks.vision.handlandmarker.proto.HandLandmarksDetectorGraphOptionsProto.HandLandmarksDetectorGraphOptions;
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import com.google.mediapipe.tasks.vision.holisticlandmarker.proto.HolisticLandmarkerGraphOptionsProto.HolisticLandmarkerGraphOptions;
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import com.google.mediapipe.tasks.vision.posedetector.proto.PoseDetectorGraphOptionsProto.PoseDetectorGraphOptions;
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import com.google.mediapipe.tasks.vision.poselandmarker.proto.PoseLandmarksDetectorGraphOptionsProto.PoseLandmarksDetectorGraphOptions;
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import com.google.protobuf.Any;
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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.ArrayList;
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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 holistic landmarks detection on images.
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*
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* <p>This API expects a pre-trained holistic landmarks model asset bundle.
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*
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* <ul>
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* <li>Input image {@link MPImage}
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* <ul>
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* <li>The image that holistic landmarks detection runs on.
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* </ul>
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* <li>Output {@link HolisticLandmarkerResult}
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* <ul>
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* <li>A HolisticLandmarkerResult containing holistic landmarks.
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* </ul>
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* </ul>
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*/
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public final class HolisticLandmarker extends BaseVisionTaskApi {
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private static final String TAG = HolisticLandmarker.class.getSimpleName();
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private static final String IMAGE_IN_STREAM_NAME = "image_in";
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private static final String POSE_LANDMARKS_STREAM = "pose_landmarks";
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private static final String POSE_WORLD_LANDMARKS_STREAM = "pose_world_landmarks";
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private static final String POSE_SEGMENTATION_MASK_STREAM = "pose_segmentation_mask";
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private static final String FACE_LANDMARKS_STREAM = "face_landmarks";
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private static final String FACE_BLENDSHAPES_STREAM = "extra_blendshapes";
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private static final String LEFT_HAND_LANDMARKS_STREAM = "left_hand_landmarks";
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private static final String LEFT_HAND_WORLD_LANDMARKS_STREAM = "left_hand_world_landmarks";
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private static final String RIGHT_HAND_LANDMARKS_STREAM = "right_hand_landmarks";
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private static final String RIGHT_HAND_WORLD_LANDMARKS_STREAM = "right_hand_world_landmarks";
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private static final String IMAGE_OUT_STREAM_NAME = "image_out";
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private static final int FACE_LANDMARKS_OUT_STREAM_INDEX = 0;
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private static final int POSE_LANDMARKS_OUT_STREAM_INDEX = 1;
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private static final int POSE_WORLD_LANDMARKS_OUT_STREAM_INDEX = 2;
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private static final int LEFT_HAND_LANDMARKS_OUT_STREAM_INDEX = 3;
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private static final int LEFT_HAND_WORLD_LANDMARKS_OUT_STREAM_INDEX = 4;
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private static final int RIGHT_HAND_LANDMARKS_OUT_STREAM_INDEX = 5;
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private static final int RIGHT_HAND_WORLD_LANDMARKS_OUT_STREAM_INDEX = 6;
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private static final int IMAGE_OUT_STREAM_INDEX = 7;
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private static final float DEFAULT_PRESENCE_THRESHOLD = 0.5f;
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private static final float DEFAULT_SUPPRESION_THRESHOLD = 0.3f;
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private static final boolean DEFAULT_OUTPUT_FACE_BLENDSHAPES = false;
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private static final boolean DEFAULT_OUTPUT_SEGMENTATION_MASKS = false;
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private static final String TASK_GRAPH_NAME =
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"mediapipe.tasks.vision.holistic_landmarker.HolisticLandmarkerGraph";
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@SuppressWarnings("ConstantCaseForConstants")
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private static final List<String> INPUT_STREAMS =
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Collections.unmodifiableList(Arrays.asList("IMAGE:" + IMAGE_IN_STREAM_NAME));
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static {
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System.loadLibrary("mediapipe_tasks_vision_jni");
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}
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/**
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* Creates a {@link HolisticLandmarker} instance from a model asset bundle path and the default
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* {@link HolisticLandmarkerOptions}.
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*
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* @param context an Android {@link Context}.
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* @param modelAssetPath path to the holistic landmarks model with metadata in the assets.
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* @throws MediaPipeException if there is an error during {@link HolisticLandmarker} creation.
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*/
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public static HolisticLandmarker createFromFile(Context context, String modelAssetPath) {
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BaseOptions baseOptions = BaseOptions.builder().setModelAssetPath(modelAssetPath).build();
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return createFromOptions(
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context, HolisticLandmarkerOptions.builder().setBaseOptions(baseOptions).build());
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}
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/**
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* Creates a {@link HolisticLandmarker} instance from a model asset bundle file and the default
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* {@link HolisticLandmarkerOptions}.
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*
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* @param context an Android {@link Context}.
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* @param modelAssetFile the holistic landmarks 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 HolisticLandmarker} creation.
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*/
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public static HolisticLandmarker createFromFile(Context context, File modelAssetFile)
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throws IOException {
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try (ParcelFileDescriptor descriptor =
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ParcelFileDescriptor.open(modelAssetFile, 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, HolisticLandmarkerOptions.builder().setBaseOptions(baseOptions).build());
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}
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}
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/**
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* Creates a {@link HolisticLandmarker} instance from a model asset bundle buffer and the default
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* {@link HolisticLandmarkerOptions}.
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*
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* @param context an Android {@link Context}.
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* @param modelAssetBuffer a direct {@link ByteBuffer} or a {@link MappedByteBuffer} of the
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* detection model.
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* @throws MediaPipeException if there is an error during {@link HolisticLandmarker} creation.
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*/
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public static HolisticLandmarker createFromBuffer(
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Context context, final ByteBuffer modelAssetBuffer) {
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BaseOptions baseOptions = BaseOptions.builder().setModelAssetBuffer(modelAssetBuffer).build();
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return createFromOptions(
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context, HolisticLandmarkerOptions.builder().setBaseOptions(baseOptions).build());
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}
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/**
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* Creates a {@link HolisticLandmarker} instance from a {@link HolisticLandmarkerOptions}.
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*
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* @param context an Android {@link Context}.
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* @param landmarkerOptions a {@link HolisticLandmarkerOptions} instance.
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* @throws MediaPipeException if there is an error during {@link HolisticLandmarker} creation.
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*/
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public static HolisticLandmarker createFromOptions(
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Context context, HolisticLandmarkerOptions landmarkerOptions) {
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List<String> outputStreams = new ArrayList<>();
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outputStreams.add("FACE_LANDMARKS:" + FACE_LANDMARKS_STREAM);
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outputStreams.add("POSE_LANDMARKS:" + POSE_LANDMARKS_STREAM);
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outputStreams.add("POSE_WORLD_LANDMARKS:" + POSE_WORLD_LANDMARKS_STREAM);
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outputStreams.add("LEFT_HAND_LANDMARKS:" + LEFT_HAND_LANDMARKS_STREAM);
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outputStreams.add("LEFT_HAND_WORLD_LANDMARKS:" + LEFT_HAND_WORLD_LANDMARKS_STREAM);
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outputStreams.add("RIGHT_HAND_LANDMARKS:" + RIGHT_HAND_LANDMARKS_STREAM);
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outputStreams.add("RIGHT_HAND_WORLD_LANDMARKS:" + RIGHT_HAND_WORLD_LANDMARKS_STREAM);
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outputStreams.add("IMAGE:" + IMAGE_OUT_STREAM_NAME);
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int[] faceBlendshapesOutStreamIndex = new int[] {-1};
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if (landmarkerOptions.outputFaceBlendshapes()) {
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outputStreams.add("FACE_BLENDSHAPES:" + FACE_BLENDSHAPES_STREAM);
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faceBlendshapesOutStreamIndex[0] = outputStreams.size() - 1;
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}
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int[] poseSegmentationMasksOutStreamIndex = new int[] {-1};
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if (landmarkerOptions.outputPoseSegmentationMasks()) {
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outputStreams.add("POSE_SEGMENTATION_MASK:" + POSE_SEGMENTATION_MASK_STREAM);
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poseSegmentationMasksOutStreamIndex[0] = outputStreams.size() - 1;
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}
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OutputHandler<HolisticLandmarkerResult, MPImage> handler = new OutputHandler<>();
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handler.setOutputPacketConverter(
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new OutputHandler.OutputPacketConverter<HolisticLandmarkerResult, MPImage>() {
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@Override
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public HolisticLandmarkerResult convertToTaskResult(List<Packet> packets) {
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// If there are no detected landmarks, just returns empty lists.
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if (packets.get(FACE_LANDMARKS_OUT_STREAM_INDEX).isEmpty()) {
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return HolisticLandmarkerResult.createEmpty(
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BaseVisionTaskApi.generateResultTimestampMs(
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landmarkerOptions.runningMode(),
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packets.get(FACE_LANDMARKS_OUT_STREAM_INDEX)));
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}
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NormalizedLandmarkList faceLandmarkProtos =
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PacketGetter.getProto(
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packets.get(FACE_LANDMARKS_OUT_STREAM_INDEX), NormalizedLandmarkList.parser());
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Optional<ClassificationList> faceBlendshapeProtos =
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landmarkerOptions.outputFaceBlendshapes()
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? Optional.of(
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PacketGetter.getProto(
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packets.get(faceBlendshapesOutStreamIndex[0]),
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ClassificationList.parser()))
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: Optional.empty();
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NormalizedLandmarkList poseLandmarkProtos =
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PacketGetter.getProto(
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packets.get(POSE_LANDMARKS_OUT_STREAM_INDEX), NormalizedLandmarkList.parser());
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LandmarkList poseWorldLandmarkProtos =
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PacketGetter.getProto(
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packets.get(POSE_WORLD_LANDMARKS_OUT_STREAM_INDEX), LandmarkList.parser());
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Optional<MPImage> segmentationMask =
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landmarkerOptions.outputPoseSegmentationMasks()
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? Optional.of(
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getSegmentationMask(packets, poseSegmentationMasksOutStreamIndex[0]))
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: Optional.empty();
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NormalizedLandmarkList leftHandLandmarkProtos =
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PacketGetter.getProto(
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packets.get(LEFT_HAND_LANDMARKS_OUT_STREAM_INDEX),
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NormalizedLandmarkList.parser());
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LandmarkList leftHandWorldLandmarkProtos =
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PacketGetter.getProto(
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packets.get(LEFT_HAND_WORLD_LANDMARKS_OUT_STREAM_INDEX), LandmarkList.parser());
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NormalizedLandmarkList rightHandLandmarkProtos =
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PacketGetter.getProto(
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packets.get(RIGHT_HAND_LANDMARKS_OUT_STREAM_INDEX),
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NormalizedLandmarkList.parser());
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LandmarkList rightHandWorldLandmarkProtos =
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PacketGetter.getProto(
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packets.get(RIGHT_HAND_WORLD_LANDMARKS_OUT_STREAM_INDEX),
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LandmarkList.parser());
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return HolisticLandmarkerResult.create(
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faceLandmarkProtos,
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faceBlendshapeProtos,
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poseLandmarkProtos,
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poseWorldLandmarkProtos,
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segmentationMask,
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leftHandLandmarkProtos,
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leftHandWorldLandmarkProtos,
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rightHandLandmarkProtos,
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rightHandWorldLandmarkProtos,
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BaseVisionTaskApi.generateResultTimestampMs(
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landmarkerOptions.runningMode(), packets.get(FACE_LANDMARKS_OUT_STREAM_INDEX)));
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}
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@Override
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public MPImage convertToTaskInput(List<Packet> packets) {
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return new BitmapImageBuilder(
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AndroidPacketGetter.getBitmapFromRgb(packets.get(IMAGE_OUT_STREAM_INDEX)))
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.build();
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}
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});
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landmarkerOptions.resultListener().ifPresent(handler::setResultListener);
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landmarkerOptions.errorListener().ifPresent(handler::setErrorListener);
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TaskRunner runner =
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TaskRunner.create(
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context,
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TaskInfo.<HolisticLandmarkerOptions>builder()
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.setTaskName(HolisticLandmarker.class.getSimpleName())
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.setTaskRunningModeName(landmarkerOptions.runningMode().name())
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.setTaskGraphName(TASK_GRAPH_NAME)
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.setInputStreams(INPUT_STREAMS)
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.setOutputStreams(outputStreams)
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.setTaskOptions(landmarkerOptions)
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.setEnableFlowLimiting(landmarkerOptions.runningMode() == RunningMode.LIVE_STREAM)
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.build(),
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handler);
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return new HolisticLandmarker(runner, landmarkerOptions.runningMode());
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}
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/**
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* Constructor to initialize an {@link HolisticLandmarker} from a {@link TaskRunner} and a {@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 vision task {@link RunningMode}.
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*/
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private HolisticLandmarker(TaskRunner taskRunner, RunningMode runningMode) {
|
||||
super(taskRunner, runningMode, IMAGE_IN_STREAM_NAME, /* normRectStreamName= */ "");
|
||||
}
|
||||
|
||||
/**
|
||||
* Performs holistic landmarks detection on the provided single image with default image
|
||||
* processing options, i.e. without any rotation applied. Only use this method when the {@link
|
||||
* HolisticLandmarker} is created with {@link RunningMode.IMAGE}.
|
||||
*
|
||||
* <p>{@link HolisticLandmarker} supports the following color space types:
|
||||
*
|
||||
* <ul>
|
||||
* <li>{@link Bitmap.Config.ARGB_8888}
|
||||
* </ul>
|
||||
*
|
||||
* @param image a MediaPipe {@link MPImage} object for processing.
|
||||
* @throws MediaPipeException if there is an internal error.
|
||||
*/
|
||||
public HolisticLandmarkerResult detect(MPImage image) {
|
||||
return detect(image, ImageProcessingOptions.builder().build());
|
||||
}
|
||||
|
||||
/**
|
||||
* Performs holistic landmarks detection on the provided single image. Only use this method when
|
||||
* the {@link HolisticLandmarker} is created with {@link RunningMode.IMAGE}.
|
||||
*
|
||||
* <p>{@link HolisticLandmarker} supports the following color space types:
|
||||
*
|
||||
* <ul>
|
||||
* <li>{@link Bitmap.Config.ARGB_8888}
|
||||
* </ul>
|
||||
*
|
||||
* @param image a MediaPipe {@link MPImage} object for processing.
|
||||
* @param imageProcessingOptions the {@link ImageProcessingOptions} specifying how to process the
|
||||
* input image before running inference. Note that region-of-interest is <b>not</b> supported
|
||||
* by this task: specifying {@link ImageProcessingOptions#regionOfInterest()} will result in
|
||||
* this method throwing an IllegalArgumentException.
|
||||
* @throws IllegalArgumentException if the {@link ImageProcessingOptions} specify a
|
||||
* region-of-interest.
|
||||
* @throws MediaPipeException if there is an internal error.
|
||||
*/
|
||||
public HolisticLandmarkerResult detect(
|
||||
MPImage image, ImageProcessingOptions imageProcessingOptions) {
|
||||
validateImageProcessingOptions(imageProcessingOptions);
|
||||
return (HolisticLandmarkerResult) processImageData(image, imageProcessingOptions);
|
||||
}
|
||||
|
||||
/**
|
||||
* Performs holistic landmarks detection on the provided video frame with default image processing
|
||||
* options, i.e. without any rotation applied. Only use this method when the {@link
|
||||
* HolisticLandmarker} is created with {@link RunningMode.VIDEO}.
|
||||
*
|
||||
* <p>It's required to provide the video frame"s timestamp (in milliseconds). The input timestamps
|
||||
* must be monotonically increasing.
|
||||
*
|
||||
* <p>{@link HolisticLandmarker} supports the following color space types:
|
||||
*
|
||||
* <ul>
|
||||
* <li>{@link Bitmap.Config.ARGB_8888}
|
||||
* </ul>
|
||||
*
|
||||
* @param image a MediaPipe {@link MPImage} object for processing.
|
||||
* @param timestampMs the input timestamp (in milliseconds).
|
||||
* @throws MediaPipeException if there is an internal error.
|
||||
*/
|
||||
public HolisticLandmarkerResult detectForVideo(MPImage image, long timestampMs) {
|
||||
return detectForVideo(image, ImageProcessingOptions.builder().build(), timestampMs);
|
||||
}
|
||||
|
||||
/**
|
||||
* Performs holistic landmarks detection on the provided video frame. Only use this method when
|
||||
* the {@link HolisticLandmarker} is created with {@link RunningMode.VIDEO}.
|
||||
*
|
||||
* <p>It's required to provide the video frame"s timestamp (in milliseconds). The input timestamps
|
||||
* must be monotonically increasing.
|
||||
*
|
||||
* <p>{@link HolisticLandmarker} supports the following color space types:
|
||||
*
|
||||
* <ul>
|
||||
* <li>{@link Bitmap.Config.ARGB_8888}
|
||||
* </ul>
|
||||
*
|
||||
* @param image a MediaPipe {@link MPImage} object for processing.
|
||||
* @param imageProcessingOptions the {@link ImageProcessingOptions} specifying how to process the
|
||||
* input image before running inference. Note that region-of-interest is <b>not</b> supported
|
||||
* by this task: specifying {@link ImageProcessingOptions#regionOfInterest()} will result in
|
||||
* this method throwing an IllegalArgumentException.
|
||||
* @param timestampMs the input timestamp (in milliseconds).
|
||||
* @throws IllegalArgumentException if the {@link ImageProcessingOptions} specify a
|
||||
* region-of-interest.
|
||||
* @throws MediaPipeException if there is an internal error.
|
||||
*/
|
||||
public HolisticLandmarkerResult detectForVideo(
|
||||
MPImage image, ImageProcessingOptions imageProcessingOptions, long timestampMs) {
|
||||
validateImageProcessingOptions(imageProcessingOptions);
|
||||
return (HolisticLandmarkerResult) processVideoData(image, imageProcessingOptions, timestampMs);
|
||||
}
|
||||
|
||||
/**
|
||||
* Sends live image data to perform holistic landmarks detection with default image processing
|
||||
* options, i.e. without any rotation applied, and the results will be available via the {@link
|
||||
* ResultListener} provided in the {@link HolisticLandmarkerOptions}. Only use this method when
|
||||
* the {@link HolisticLandmarker } is created with {@link RunningMode.LIVE_STREAM}.
|
||||
*
|
||||
* <p>It's required to provide a timestamp (in milliseconds) to indicate when the input image is
|
||||
* sent to the holistic landmarker. The input timestamps must be monotonically increasing.
|
||||
*
|
||||
* <p>{@link HolisticLandmarker} supports the following color space types:
|
||||
*
|
||||
* <ul>
|
||||
* <li>{@link Bitmap.Config.ARGB_8888}
|
||||
* </ul>
|
||||
*
|
||||
* @param image a MediaPipe {@link MPImage} object for processing.
|
||||
* @param timestampMs the input timestamp (in milliseconds).
|
||||
* @throws MediaPipeException if there is an internal error.
|
||||
*/
|
||||
public void detectAsync(MPImage image, long timestampMs) {
|
||||
detectAsync(image, ImageProcessingOptions.builder().build(), timestampMs);
|
||||
}
|
||||
|
||||
/**
|
||||
* Sends live image data to perform holistic landmarks detection, and the results will be
|
||||
* available via the {@link ResultListener} provided in the {@link HolisticLandmarkerOptions}.
|
||||
* Only use this method when the {@link HolisticLandmarker} is created with {@link
|
||||
* RunningMode.LIVE_STREAM}.
|
||||
*
|
||||
* <p>It's required to provide a timestamp (in milliseconds) to indicate when the input image is
|
||||
* sent to the holistic landmarker. The input timestamps must be monotonically increasing.
|
||||
*
|
||||
* <p>{@link HolisticLandmarker} supports the following color space types:
|
||||
*
|
||||
* <ul>
|
||||
* <li>{@link Bitmap.Config.ARGB_8888}
|
||||
* </ul>
|
||||
*
|
||||
* @param image a MediaPipe {@link MPImage} object for processing.
|
||||
* @param imageProcessingOptions the {@link ImageProcessingOptions} specifying how to process the
|
||||
* input image before running inference. Note that region-of-interest is <b>not</b> supported
|
||||
* by this task: specifying {@link ImageProcessingOptions#regionOfInterest()} will result in
|
||||
* this method throwing an IllegalArgumentException.
|
||||
* @param timestampMs the input timestamp (in milliseconds).
|
||||
* @throws IllegalArgumentException if the {@link ImageProcessingOptions} specify a
|
||||
* region-of-interest.
|
||||
* @throws MediaPipeException if there is an internal error.
|
||||
*/
|
||||
public void detectAsync(
|
||||
MPImage image, ImageProcessingOptions imageProcessingOptions, long timestampMs) {
|
||||
validateImageProcessingOptions(imageProcessingOptions);
|
||||
sendLiveStreamData(image, imageProcessingOptions, timestampMs);
|
||||
}
|
||||
|
||||
/** Options for setting up an {@link HolisticLandmarker}. */
|
||||
@AutoValue
|
||||
public abstract static class HolisticLandmarkerOptions extends TaskOptions {
|
||||
|
||||
/** Builder for {@link HolisticLandmarkerOptions}. */
|
||||
@AutoValue.Builder
|
||||
public abstract static class Builder {
|
||||
/** Sets the base options for the holistic landmarker task. */
|
||||
public abstract Builder setBaseOptions(BaseOptions value);
|
||||
|
||||
/**
|
||||
* Sets the running mode for the holistic landmarker task. Defaults to the image mode.
|
||||
* Holistic landmarker has three modes:
|
||||
*
|
||||
* <ul>
|
||||
* <li>IMAGE: The mode for detecting holistic landmarks on single image inputs.
|
||||
* <li>VIDEO: The mode for detecting holistic landmarks on the decoded frames of a video.
|
||||
* <li>LIVE_STREAM: The mode for for detecting holistic landmarks on a live stream of input
|
||||
* data, such as from camera. In this mode, {@code setResultListener} must be called to
|
||||
* set up a listener to receive the detection results asynchronously.
|
||||
* </ul>
|
||||
*/
|
||||
public abstract Builder setRunningMode(RunningMode value);
|
||||
|
||||
/**
|
||||
* Sets minimum confidence score for the face detection to be considered successful. Defaults
|
||||
* to 0.5.
|
||||
*/
|
||||
public abstract Builder setMinFaceDetectionConfidence(Float value);
|
||||
|
||||
/**
|
||||
* The minimum threshold for the face suppression score in the face detection. Defaults to
|
||||
* 0.3.
|
||||
*/
|
||||
public abstract Builder setMinFaceSuppressionThreshold(Float value);
|
||||
|
||||
/**
|
||||
* Sets minimum confidence score for the face landmark detection to be considered successful.
|
||||
* Defaults to 0.5.
|
||||
*/
|
||||
public abstract Builder setMinFaceLandmarksConfidence(Float value);
|
||||
|
||||
/**
|
||||
* The minimum confidence score for the pose detection to be considered successful. Defaults
|
||||
* to 0.5.
|
||||
*/
|
||||
public abstract Builder setMinPoseDetectionConfidence(Float value);
|
||||
|
||||
/**
|
||||
* The minimum threshold for the pose suppression score in the pose detection. Defaults to
|
||||
* 0.3.
|
||||
*/
|
||||
public abstract Builder setMinPoseSuppressionThreshold(Float value);
|
||||
|
||||
/**
|
||||
* The minimum confidence score for the pose landmarks detection to be considered successful.
|
||||
* Defaults to 0.5.
|
||||
*/
|
||||
public abstract Builder setMinPoseLandmarksConfidence(Float value);
|
||||
|
||||
/**
|
||||
* The minimum confidence score for the hand landmark detection to be considered successful.
|
||||
* Defaults to 0.5.
|
||||
*/
|
||||
public abstract Builder setMinHandLandmarksConfidence(Float value);
|
||||
|
||||
/** Whether to output segmentation masks. Defaults to false. */
|
||||
public abstract Builder setOutputPoseSegmentationMasks(Boolean value);
|
||||
|
||||
/** Whether to output face blendshapes. Defaults to false. */
|
||||
public abstract Builder setOutputFaceBlendshapes(Boolean value);
|
||||
|
||||
/**
|
||||
* Sets the result listener to receive the detection results asynchronously when the holistic
|
||||
* landmarker is in the live stream mode.
|
||||
*/
|
||||
public abstract Builder setResultListener(
|
||||
ResultListener<HolisticLandmarkerResult, MPImage> value);
|
||||
|
||||
/** Sets an optional error listener. */
|
||||
public abstract Builder setErrorListener(ErrorListener value);
|
||||
|
||||
abstract HolisticLandmarkerOptions autoBuild();
|
||||
|
||||
/**
|
||||
* Validates and builds the {@link HolisticLandmarkerOptions} instance.
|
||||
*
|
||||
* @throws IllegalArgumentException if the result listener and the running mode are not
|
||||
* properly configured. The result listener should only be set when the holistic
|
||||
* landmarker is in the live stream mode.
|
||||
*/
|
||||
public final HolisticLandmarkerOptions build() {
|
||||
HolisticLandmarkerOptions options = autoBuild();
|
||||
if (options.runningMode() == RunningMode.LIVE_STREAM) {
|
||||
if (!options.resultListener().isPresent()) {
|
||||
throw new IllegalArgumentException(
|
||||
"The holistic landmarker is in the live stream mode, a user-defined result listener"
|
||||
+ " must be provided in HolisticLandmarkerOptions.");
|
||||
}
|
||||
} else if (options.resultListener().isPresent()) {
|
||||
throw new IllegalArgumentException(
|
||||
"The holistic landmarker is in the image or the video mode, a user-defined result"
|
||||
+ " listener shouldn't be provided in HolisticLandmarkerOptions.");
|
||||
}
|
||||
return options;
|
||||
}
|
||||
}
|
||||
|
||||
abstract BaseOptions baseOptions();
|
||||
|
||||
abstract RunningMode runningMode();
|
||||
|
||||
abstract Optional<Float> minFaceDetectionConfidence();
|
||||
|
||||
abstract Optional<Float> minFaceSuppressionThreshold();
|
||||
|
||||
abstract Optional<Float> minFaceLandmarksConfidence();
|
||||
|
||||
abstract Optional<Float> minPoseDetectionConfidence();
|
||||
|
||||
abstract Optional<Float> minPoseSuppressionThreshold();
|
||||
|
||||
abstract Optional<Float> minPoseLandmarksConfidence();
|
||||
|
||||
abstract Optional<Float> minHandLandmarksConfidence();
|
||||
|
||||
abstract Boolean outputFaceBlendshapes();
|
||||
|
||||
abstract Boolean outputPoseSegmentationMasks();
|
||||
|
||||
abstract Optional<ResultListener<HolisticLandmarkerResult, MPImage>> resultListener();
|
||||
|
||||
abstract Optional<ErrorListener> errorListener();
|
||||
|
||||
public static Builder builder() {
|
||||
return new AutoValue_HolisticLandmarker_HolisticLandmarkerOptions.Builder()
|
||||
.setRunningMode(RunningMode.IMAGE)
|
||||
.setMinFaceDetectionConfidence(DEFAULT_PRESENCE_THRESHOLD)
|
||||
.setMinFaceSuppressionThreshold(DEFAULT_SUPPRESION_THRESHOLD)
|
||||
.setMinFaceLandmarksConfidence(DEFAULT_PRESENCE_THRESHOLD)
|
||||
.setMinPoseDetectionConfidence(DEFAULT_PRESENCE_THRESHOLD)
|
||||
.setMinPoseSuppressionThreshold(DEFAULT_SUPPRESION_THRESHOLD)
|
||||
.setMinPoseLandmarksConfidence(DEFAULT_PRESENCE_THRESHOLD)
|
||||
.setMinHandLandmarksConfidence(DEFAULT_PRESENCE_THRESHOLD)
|
||||
.setOutputFaceBlendshapes(DEFAULT_OUTPUT_FACE_BLENDSHAPES)
|
||||
.setOutputPoseSegmentationMasks(DEFAULT_OUTPUT_SEGMENTATION_MASKS);
|
||||
}
|
||||
|
||||
/** Converts a {@link HolisticLandmarkerOptions} to a {@link Any} protobuf message. */
|
||||
@Override
|
||||
public Any convertToAnyProto() {
|
||||
HolisticLandmarkerGraphOptions.Builder holisticLandmarkerGraphOptions =
|
||||
HolisticLandmarkerGraphOptions.newBuilder()
|
||||
.setBaseOptions(
|
||||
BaseOptionsProto.BaseOptions.newBuilder()
|
||||
.setUseStreamMode(runningMode() != RunningMode.IMAGE)
|
||||
.mergeFrom(convertBaseOptionsToProto(baseOptions()))
|
||||
.build());
|
||||
|
||||
HandLandmarksDetectorGraphOptions.Builder handLandmarksDetectorGraphOptions =
|
||||
HandLandmarksDetectorGraphOptions.newBuilder();
|
||||
FaceDetectorGraphOptions.Builder faceDetectorGraphOptions =
|
||||
FaceDetectorGraphOptions.newBuilder();
|
||||
FaceLandmarksDetectorGraphOptions.Builder faceLandmarksDetectorGraphOptions =
|
||||
FaceLandmarksDetectorGraphOptions.newBuilder();
|
||||
PoseDetectorGraphOptions.Builder poseDetectorGraphOptions =
|
||||
PoseDetectorGraphOptions.newBuilder();
|
||||
PoseLandmarksDetectorGraphOptions.Builder poseLandmarkerGraphOptions =
|
||||
PoseLandmarksDetectorGraphOptions.newBuilder();
|
||||
|
||||
// Configure hand detector options.
|
||||
minHandLandmarksConfidence()
|
||||
.ifPresent(handLandmarksDetectorGraphOptions::setMinDetectionConfidence);
|
||||
|
||||
// Configure pose detector options.
|
||||
minPoseDetectionConfidence().ifPresent(poseDetectorGraphOptions::setMinDetectionConfidence);
|
||||
minPoseSuppressionThreshold().ifPresent(poseDetectorGraphOptions::setMinSuppressionThreshold);
|
||||
minPoseLandmarksConfidence().ifPresent(poseLandmarkerGraphOptions::setMinDetectionConfidence);
|
||||
|
||||
// Configure face detector options.
|
||||
minFaceDetectionConfidence().ifPresent(faceDetectorGraphOptions::setMinDetectionConfidence);
|
||||
minFaceSuppressionThreshold().ifPresent(faceDetectorGraphOptions::setMinSuppressionThreshold);
|
||||
minFaceLandmarksConfidence()
|
||||
.ifPresent(faceLandmarksDetectorGraphOptions::setMinDetectionConfidence);
|
||||
|
||||
holisticLandmarkerGraphOptions
|
||||
.setHandLandmarksDetectorGraphOptions(handLandmarksDetectorGraphOptions.build())
|
||||
.setFaceDetectorGraphOptions(faceDetectorGraphOptions.build())
|
||||
.setFaceLandmarksDetectorGraphOptions(faceLandmarksDetectorGraphOptions.build())
|
||||
.setPoseDetectorGraphOptions(poseDetectorGraphOptions.build())
|
||||
.setPoseLandmarksDetectorGraphOptions(poseLandmarkerGraphOptions.build());
|
||||
|
||||
return Any.newBuilder()
|
||||
.setTypeUrl(
|
||||
"type.googleapis.com/mediapipe.tasks.vision.holistic_landmarker.proto.HolisticLandmarkerGraphOptions")
|
||||
.setValue(holisticLandmarkerGraphOptions.build().toByteString())
|
||||
.build();
|
||||
}
|
||||
}
|
||||
|
||||
/**
|
||||
* Validates that the provided {@link ImageProcessingOptions} doesn"t contain a
|
||||
* region-of-interest.
|
||||
*/
|
||||
private static void validateImageProcessingOptions(
|
||||
ImageProcessingOptions imageProcessingOptions) {
|
||||
if (imageProcessingOptions.regionOfInterest().isPresent()) {
|
||||
throw new IllegalArgumentException("HolisticLandmarker doesn't support region-of-interest.");
|
||||
}
|
||||
}
|
||||
|
||||
private static MPImage getSegmentationMask(List<Packet> packets, int packetIndex) {
|
||||
int width = PacketGetter.getImageWidth(packets.get(packetIndex));
|
||||
int height = PacketGetter.getImageHeight(packets.get(packetIndex));
|
||||
ByteBuffer buffer = ByteBuffer.allocateDirect(width * height * 4);
|
||||
|
||||
if (!PacketGetter.getImageData(packets.get(packetIndex), buffer)) {
|
||||
throw new MediaPipeException(
|
||||
MediaPipeException.StatusCode.INTERNAL.ordinal(),
|
||||
"There was an error getting the sefmentation mask.");
|
||||
}
|
||||
|
||||
ByteBufferImageBuilder builder =
|
||||
new ByteBufferImageBuilder(buffer, width, height, MPImage.IMAGE_FORMAT_VEC32F1);
|
||||
return builder.build();
|
||||
}
|
||||
}
|
|
@ -0,0 +1,24 @@
|
|||
<?xml version="1.0" encoding="utf-8"?>
|
||||
<manifest xmlns:android="http://schemas.android.com/apk/res/android"
|
||||
package="com.google.mediapipe.tasks.vision.holisticlandmarkertest"
|
||||
android:versionCode="1"
|
||||
android:versionName="1.0" >
|
||||
|
||||
<uses-permission android:name="android.permission.READ_EXTERNAL_STORAGE"/>
|
||||
<uses-permission android:name="android.permission.WRITE_EXTERNAL_STORAGE"/>
|
||||
|
||||
<uses-sdk android:minSdkVersion="24"
|
||||
android:targetSdkVersion="30" />
|
||||
|
||||
<application
|
||||
android:label="holisticlandmarkertest"
|
||||
android:name="android.support.multidex.MultiDexApplication"
|
||||
android:taskAffinity="">
|
||||
<uses-library android:name="android.test.runner" />
|
||||
</application>
|
||||
|
||||
<instrumentation
|
||||
android:name="com.google.android.apps.common.testing.testrunner.GoogleInstrumentationTestRunner"
|
||||
android:targetPackage="com.google.mediapipe.tasks.vision.holisticlandmarkertest" />
|
||||
|
||||
</manifest>
|
|
@ -0,0 +1,19 @@
|
|||
# Copyright 2023 The MediaPipe Authors.
|
||||
#
|
||||
# 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(default_visibility = ["//mediapipe/tasks:internal"])
|
||||
|
||||
licenses(["notice"])
|
||||
|
||||
# TODO: Enable this in OSS
|
|
@ -0,0 +1,512 @@
|
|||
// Copyright 2023 The MediaPipe Authors.
|
||||
//
|
||||
// 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 com.google.mediapipe.tasks.vision.holisticlandmarker;
|
||||
|
||||
import static com.google.common.truth.Truth.assertThat;
|
||||
import static org.junit.Assert.assertThrows;
|
||||
|
||||
import android.content.res.AssetManager;
|
||||
import android.graphics.BitmapFactory;
|
||||
import android.graphics.RectF;
|
||||
import androidx.test.core.app.ApplicationProvider;
|
||||
import androidx.test.ext.junit.runners.AndroidJUnit4;
|
||||
import com.google.common.truth.Correspondence;
|
||||
import com.google.mediapipe.formats.proto.LandmarkProto.LandmarkList;
|
||||
import com.google.mediapipe.formats.proto.ClassificationProto.ClassificationList;
|
||||
import com.google.mediapipe.framework.MediaPipeException;
|
||||
import com.google.mediapipe.framework.image.BitmapImageBuilder;
|
||||
import com.google.mediapipe.framework.image.ByteBufferImageBuilder;
|
||||
import com.google.mediapipe.framework.image.MPImage;
|
||||
import com.google.mediapipe.tasks.components.containers.Category;
|
||||
import com.google.mediapipe.tasks.components.containers.NormalizedLandmark;
|
||||
import com.google.mediapipe.tasks.core.BaseOptions;
|
||||
import com.google.mediapipe.tasks.vision.core.ImageProcessingOptions;
|
||||
import com.google.mediapipe.tasks.vision.core.RunningMode;
|
||||
import com.google.mediapipe.tasks.vision.holisticlandmarker.HolisticLandmarker.HolisticLandmarkerOptions;
|
||||
import com.google.mediapipe.tasks.vision.holisticlandmarker.HolisticResultProto.HolisticResult;
|
||||
import java.io.InputStream;
|
||||
import java.nio.ByteBuffer;
|
||||
import java.util.Optional;
|
||||
import org.junit.Test;
|
||||
import org.junit.runner.RunWith;
|
||||
import org.junit.runners.Suite;
|
||||
import org.junit.runners.Suite.SuiteClasses;
|
||||
|
||||
/** Test for {@link HolisticLandmarker}. */
|
||||
@RunWith(Suite.class)
|
||||
@SuiteClasses({HolisticLandmarkerTest.General.class, HolisticLandmarkerTest.RunningModeTest.class})
|
||||
public class HolisticLandmarkerTest {
|
||||
private static final String HOLISTIC_LANDMARKER_BUNDLE_ASSET_FILE = "holistic_landmarker.task";
|
||||
private static final String POSE_IMAGE = "male_full_height_hands.jpg";
|
||||
private static final String CAT_IMAGE = "cat.jpg";
|
||||
private static final String HOLISTIC_RESULT = "male_full_height_hands_result_cpu.pb";
|
||||
private static final String TAG = "Holistic Landmarker Test";
|
||||
private static final float FACE_LANDMARKS_ERROR_TOLERANCE = 0.03f;
|
||||
private static final float FACE_BLENDSHAPES_ERROR_TOLERANCE = 0.13f;
|
||||
private static final MPImage PLACEHOLDER_MASK =
|
||||
new ByteBufferImageBuilder(
|
||||
ByteBuffer.allocate(0), /* widht= */ 0, /* height= */ 0, MPImage.IMAGE_FORMAT_VEC32F1)
|
||||
.build();
|
||||
private static final int IMAGE_WIDTH = 638;
|
||||
private static final int IMAGE_HEIGHT = 1000;
|
||||
|
||||
private static final Correspondence<NormalizedLandmark, NormalizedLandmark> VALIDATE_LANDMARRKS =
|
||||
Correspondence.from(
|
||||
(Correspondence.BinaryPredicate<NormalizedLandmark, NormalizedLandmark>)
|
||||
(actual, expected) -> {
|
||||
return Correspondence.tolerance(FACE_LANDMARKS_ERROR_TOLERANCE)
|
||||
.compare(actual.x(), expected.x())
|
||||
&& Correspondence.tolerance(FACE_LANDMARKS_ERROR_TOLERANCE)
|
||||
.compare(actual.y(), expected.y());
|
||||
},
|
||||
"landmarks approximately equal to");
|
||||
|
||||
private static final Correspondence<Category, Category> VALIDATE_BLENDSHAPES =
|
||||
Correspondence.from(
|
||||
(Correspondence.BinaryPredicate<Category, Category>)
|
||||
(actual, expected) ->
|
||||
Correspondence.tolerance(FACE_BLENDSHAPES_ERROR_TOLERANCE)
|
||||
.compare(actual.score(), expected.score())
|
||||
&& actual.index() == expected.index()
|
||||
&& actual.categoryName().equals(expected.categoryName()),
|
||||
"face blendshapes approximately equal to");
|
||||
|
||||
@RunWith(AndroidJUnit4.class)
|
||||
public static final class General extends HolisticLandmarkerTest {
|
||||
|
||||
@Test
|
||||
public void detect_successWithValidModels() throws Exception {
|
||||
HolisticLandmarkerOptions options =
|
||||
HolisticLandmarkerOptions.builder()
|
||||
.setBaseOptions(
|
||||
BaseOptions.builder()
|
||||
.setModelAssetPath(HOLISTIC_LANDMARKER_BUNDLE_ASSET_FILE)
|
||||
.build())
|
||||
.build();
|
||||
HolisticLandmarker holisticLandmarker =
|
||||
HolisticLandmarker.createFromOptions(
|
||||
ApplicationProvider.getApplicationContext(), options);
|
||||
HolisticLandmarkerResult actualResult =
|
||||
holisticLandmarker.detect(getImageFromAsset(POSE_IMAGE));
|
||||
HolisticLandmarkerResult expectedResult =
|
||||
getExpectedHolisticLandmarkerResult(
|
||||
HOLISTIC_RESULT, /* hasFaceBlendshapes= */ false, /* hasSegmentationMask= */ false);
|
||||
assertActualResultApproximatelyEqualsToExpectedResult(actualResult, expectedResult);
|
||||
}
|
||||
|
||||
@Test
|
||||
public void detect_successWithBlendshapes() throws Exception {
|
||||
HolisticLandmarkerOptions options =
|
||||
HolisticLandmarkerOptions.builder()
|
||||
.setBaseOptions(
|
||||
BaseOptions.builder()
|
||||
.setModelAssetPath(HOLISTIC_LANDMARKER_BUNDLE_ASSET_FILE)
|
||||
.build())
|
||||
.setOutputFaceBlendshapes(true)
|
||||
.build();
|
||||
HolisticLandmarker holisticLandmarker =
|
||||
HolisticLandmarker.createFromOptions(
|
||||
ApplicationProvider.getApplicationContext(), options);
|
||||
HolisticLandmarkerResult actualResult =
|
||||
holisticLandmarker.detect(getImageFromAsset(POSE_IMAGE));
|
||||
HolisticLandmarkerResult expectedResult =
|
||||
getExpectedHolisticLandmarkerResult(
|
||||
HOLISTIC_RESULT, /* hasFaceBlendshapes= */ true, /* hasSegmentationMask= */ false);
|
||||
assertActualResultApproximatelyEqualsToExpectedResult(actualResult, expectedResult);
|
||||
}
|
||||
|
||||
@Test
|
||||
public void detect_successWithSegmentationMasks() throws Exception {
|
||||
HolisticLandmarkerOptions options =
|
||||
HolisticLandmarkerOptions.builder()
|
||||
.setBaseOptions(
|
||||
BaseOptions.builder()
|
||||
.setModelAssetPath(HOLISTIC_LANDMARKER_BUNDLE_ASSET_FILE)
|
||||
.build())
|
||||
.setOutputPoseSegmentationMasks(true)
|
||||
.build();
|
||||
HolisticLandmarker holisticLandmarker =
|
||||
HolisticLandmarker.createFromOptions(
|
||||
ApplicationProvider.getApplicationContext(), options);
|
||||
HolisticLandmarkerResult actualResult =
|
||||
holisticLandmarker.detect(getImageFromAsset(POSE_IMAGE));
|
||||
HolisticLandmarkerResult expectedResult =
|
||||
getExpectedHolisticLandmarkerResult(
|
||||
HOLISTIC_RESULT, /* hasFaceBlendshapes= */ false, /* hasSegmentationMask= */ true);
|
||||
assertActualResultApproximatelyEqualsToExpectedResult(actualResult, expectedResult);
|
||||
}
|
||||
|
||||
@Test
|
||||
public void detect_successWithEmptyResult() throws Exception {
|
||||
HolisticLandmarkerOptions options =
|
||||
HolisticLandmarkerOptions.builder()
|
||||
.setBaseOptions(
|
||||
BaseOptions.builder()
|
||||
.setModelAssetPath(HOLISTIC_LANDMARKER_BUNDLE_ASSET_FILE)
|
||||
.build())
|
||||
.build();
|
||||
HolisticLandmarker holisticLandmarker =
|
||||
HolisticLandmarker.createFromOptions(
|
||||
ApplicationProvider.getApplicationContext(), options);
|
||||
HolisticLandmarkerResult actualResult =
|
||||
holisticLandmarker.detect(getImageFromAsset(CAT_IMAGE));
|
||||
assertThat(actualResult.faceLandmarks()).isEmpty();
|
||||
}
|
||||
|
||||
@Test
|
||||
public void detect_failsWithRegionOfInterest() throws Exception {
|
||||
HolisticLandmarkerOptions options =
|
||||
HolisticLandmarkerOptions.builder()
|
||||
.setBaseOptions(
|
||||
BaseOptions.builder()
|
||||
.setModelAssetPath(HOLISTIC_LANDMARKER_BUNDLE_ASSET_FILE)
|
||||
.build())
|
||||
.build();
|
||||
HolisticLandmarker holisticLandmarker =
|
||||
HolisticLandmarker.createFromOptions(
|
||||
ApplicationProvider.getApplicationContext(), options);
|
||||
ImageProcessingOptions imageProcessingOptions =
|
||||
ImageProcessingOptions.builder().setRegionOfInterest(new RectF(0, 0, 1, 1)).build();
|
||||
IllegalArgumentException exception =
|
||||
assertThrows(
|
||||
IllegalArgumentException.class,
|
||||
() ->
|
||||
holisticLandmarker.detect(getImageFromAsset(POSE_IMAGE), imageProcessingOptions));
|
||||
assertThat(exception)
|
||||
.hasMessageThat()
|
||||
.contains("HolisticLandmarker doesn't support region-of-interest");
|
||||
}
|
||||
}
|
||||
|
||||
@RunWith(AndroidJUnit4.class)
|
||||
public static final class RunningModeTest extends HolisticLandmarkerTest {
|
||||
private void assertCreationFailsWithResultListenerInNonLiveStreamMode(RunningMode runningMode)
|
||||
throws Exception {
|
||||
IllegalArgumentException exception =
|
||||
assertThrows(
|
||||
IllegalArgumentException.class,
|
||||
() ->
|
||||
HolisticLandmarkerOptions.builder()
|
||||
.setBaseOptions(
|
||||
BaseOptions.builder()
|
||||
.setModelAssetPath(HOLISTIC_LANDMARKER_BUNDLE_ASSET_FILE)
|
||||
.build())
|
||||
.setRunningMode(runningMode)
|
||||
.setResultListener((HolisticLandmarkerResult, inputImage) -> {})
|
||||
.build());
|
||||
assertThat(exception)
|
||||
.hasMessageThat()
|
||||
.contains("a user-defined result listener shouldn't be provided");
|
||||
}
|
||||
|
||||
@Test
|
||||
public void create_failsWithIllegalResultListenerInVideoMode() throws Exception {
|
||||
assertCreationFailsWithResultListenerInNonLiveStreamMode(RunningMode.VIDEO);
|
||||
}
|
||||
|
||||
@Test
|
||||
public void create_failsWithIllegalResultListenerInImageMode() throws Exception {
|
||||
assertCreationFailsWithResultListenerInNonLiveStreamMode(RunningMode.IMAGE);
|
||||
}
|
||||
|
||||
@Test
|
||||
public void create_failsWithMissingResultListenerInLiveSteamMode() throws Exception {
|
||||
IllegalArgumentException exception =
|
||||
assertThrows(
|
||||
IllegalArgumentException.class,
|
||||
() ->
|
||||
HolisticLandmarkerOptions.builder()
|
||||
.setBaseOptions(
|
||||
BaseOptions.builder()
|
||||
.setModelAssetPath(HOLISTIC_LANDMARKER_BUNDLE_ASSET_FILE)
|
||||
.build())
|
||||
.setRunningMode(RunningMode.LIVE_STREAM)
|
||||
.build());
|
||||
assertThat(exception)
|
||||
.hasMessageThat()
|
||||
.contains("a user-defined result listener must be provided");
|
||||
}
|
||||
|
||||
@Test
|
||||
public void detect_failsWithCallingWrongApiInImageMode() throws Exception {
|
||||
HolisticLandmarkerOptions options =
|
||||
HolisticLandmarkerOptions.builder()
|
||||
.setBaseOptions(
|
||||
BaseOptions.builder()
|
||||
.setModelAssetPath(HOLISTIC_LANDMARKER_BUNDLE_ASSET_FILE)
|
||||
.build())
|
||||
.setRunningMode(RunningMode.IMAGE)
|
||||
.build();
|
||||
|
||||
HolisticLandmarker holisticLandmarker =
|
||||
HolisticLandmarker.createFromOptions(
|
||||
ApplicationProvider.getApplicationContext(), options);
|
||||
MediaPipeException exception =
|
||||
assertThrows(
|
||||
MediaPipeException.class,
|
||||
() ->
|
||||
holisticLandmarker.detectForVideo(
|
||||
getImageFromAsset(POSE_IMAGE), /* timestampsMs= */ 0));
|
||||
assertThat(exception).hasMessageThat().contains("not initialized with the video mode");
|
||||
exception =
|
||||
assertThrows(
|
||||
MediaPipeException.class,
|
||||
() ->
|
||||
holisticLandmarker.detectAsync(
|
||||
getImageFromAsset(POSE_IMAGE), /* timestampsMs= */ 0));
|
||||
assertThat(exception).hasMessageThat().contains("not initialized with the live stream mode");
|
||||
}
|
||||
|
||||
@Test
|
||||
public void detect_failsWithCallingWrongApiInVideoMode() throws Exception {
|
||||
HolisticLandmarkerOptions options =
|
||||
HolisticLandmarkerOptions.builder()
|
||||
.setBaseOptions(
|
||||
BaseOptions.builder()
|
||||
.setModelAssetPath(HOLISTIC_LANDMARKER_BUNDLE_ASSET_FILE)
|
||||
.build())
|
||||
.setRunningMode(RunningMode.VIDEO)
|
||||
.build();
|
||||
|
||||
HolisticLandmarker holisticLandmarker =
|
||||
HolisticLandmarker.createFromOptions(
|
||||
ApplicationProvider.getApplicationContext(), options);
|
||||
MediaPipeException exception =
|
||||
assertThrows(
|
||||
MediaPipeException.class,
|
||||
() -> holisticLandmarker.detect(getImageFromAsset(POSE_IMAGE)));
|
||||
assertThat(exception).hasMessageThat().contains("not initialized with the image mode");
|
||||
exception =
|
||||
assertThrows(
|
||||
MediaPipeException.class,
|
||||
() ->
|
||||
holisticLandmarker.detectAsync(
|
||||
getImageFromAsset(POSE_IMAGE), /* timestampsMs= */ 0));
|
||||
assertThat(exception).hasMessageThat().contains("not initialized with the live stream mode");
|
||||
}
|
||||
|
||||
@Test
|
||||
public void detect_failsWithCallingWrongApiInLiveSteamMode() throws Exception {
|
||||
HolisticLandmarkerOptions options =
|
||||
HolisticLandmarkerOptions.builder()
|
||||
.setBaseOptions(
|
||||
BaseOptions.builder()
|
||||
.setModelAssetPath(HOLISTIC_LANDMARKER_BUNDLE_ASSET_FILE)
|
||||
.build())
|
||||
.setRunningMode(RunningMode.LIVE_STREAM)
|
||||
.setResultListener((HolisticLandmarkerResult, inputImage) -> {})
|
||||
.build();
|
||||
|
||||
HolisticLandmarker holisticLandmarker =
|
||||
HolisticLandmarker.createFromOptions(
|
||||
ApplicationProvider.getApplicationContext(), options);
|
||||
MediaPipeException exception =
|
||||
assertThrows(
|
||||
MediaPipeException.class,
|
||||
() -> holisticLandmarker.detect(getImageFromAsset(POSE_IMAGE)));
|
||||
assertThat(exception).hasMessageThat().contains("not initialized with the image mode");
|
||||
exception =
|
||||
assertThrows(
|
||||
MediaPipeException.class,
|
||||
() ->
|
||||
holisticLandmarker.detectForVideo(
|
||||
getImageFromAsset(POSE_IMAGE), /* timestampsMs= */ 0));
|
||||
assertThat(exception).hasMessageThat().contains("not initialized with the video mode");
|
||||
}
|
||||
|
||||
@Test
|
||||
public void detect_successWithImageMode() throws Exception {
|
||||
HolisticLandmarkerOptions options =
|
||||
HolisticLandmarkerOptions.builder()
|
||||
.setBaseOptions(
|
||||
BaseOptions.builder()
|
||||
.setModelAssetPath(HOLISTIC_LANDMARKER_BUNDLE_ASSET_FILE)
|
||||
.build())
|
||||
.setRunningMode(RunningMode.IMAGE)
|
||||
.build();
|
||||
|
||||
HolisticLandmarker holisticLandmarker =
|
||||
HolisticLandmarker.createFromOptions(
|
||||
ApplicationProvider.getApplicationContext(), options);
|
||||
HolisticLandmarkerResult actualResult =
|
||||
holisticLandmarker.detect(getImageFromAsset(POSE_IMAGE));
|
||||
HolisticLandmarkerResult expectedResult =
|
||||
getExpectedHolisticLandmarkerResult(
|
||||
HOLISTIC_RESULT, /* hasFaceBlendshapes= */ false, /* hasSegmentationMask= */ false);
|
||||
assertActualResultApproximatelyEqualsToExpectedResult(actualResult, expectedResult);
|
||||
}
|
||||
|
||||
@Test
|
||||
public void detect_successWithVideoMode() throws Exception {
|
||||
HolisticLandmarkerOptions options =
|
||||
HolisticLandmarkerOptions.builder()
|
||||
.setBaseOptions(
|
||||
BaseOptions.builder()
|
||||
.setModelAssetPath(HOLISTIC_LANDMARKER_BUNDLE_ASSET_FILE)
|
||||
.build())
|
||||
.setRunningMode(RunningMode.VIDEO)
|
||||
.build();
|
||||
HolisticLandmarker holisticLandmarker =
|
||||
HolisticLandmarker.createFromOptions(
|
||||
ApplicationProvider.getApplicationContext(), options);
|
||||
HolisticLandmarkerResult expectedResult =
|
||||
getExpectedHolisticLandmarkerResult(
|
||||
HOLISTIC_RESULT, /* hasFaceBlendshapes= */ false, /* hasSegmentationMask= */ false);
|
||||
for (int i = 0; i < 3; i++) {
|
||||
HolisticLandmarkerResult actualResult =
|
||||
holisticLandmarker.detectForVideo(getImageFromAsset(POSE_IMAGE), /* timestampsMs= */ i);
|
||||
assertActualResultApproximatelyEqualsToExpectedResult(actualResult, expectedResult);
|
||||
}
|
||||
}
|
||||
|
||||
@Test
|
||||
public void detect_failsWithOutOfOrderInputTimestamps() throws Exception {
|
||||
MPImage image = getImageFromAsset(POSE_IMAGE);
|
||||
HolisticLandmarkerOptions options =
|
||||
HolisticLandmarkerOptions.builder()
|
||||
.setBaseOptions(
|
||||
BaseOptions.builder()
|
||||
.setModelAssetPath(HOLISTIC_LANDMARKER_BUNDLE_ASSET_FILE)
|
||||
.build())
|
||||
.setRunningMode(RunningMode.LIVE_STREAM)
|
||||
.setResultListener((actualResult, inputImage) -> {})
|
||||
.build();
|
||||
try (HolisticLandmarker holisticLandmarker =
|
||||
HolisticLandmarker.createFromOptions(
|
||||
ApplicationProvider.getApplicationContext(), options)) {
|
||||
holisticLandmarker.detectAsync(image, /* timestampsMs= */ 1);
|
||||
MediaPipeException exception =
|
||||
assertThrows(
|
||||
MediaPipeException.class,
|
||||
() -> holisticLandmarker.detectAsync(image, /* timestampsMs= */ 0));
|
||||
assertThat(exception)
|
||||
.hasMessageThat()
|
||||
.contains("having a smaller timestamp than the processed timestamp");
|
||||
}
|
||||
}
|
||||
|
||||
@Test
|
||||
public void detect_successWithLiveSteamMode() throws Exception {
|
||||
MPImage image = getImageFromAsset(POSE_IMAGE);
|
||||
HolisticLandmarkerResult expectedResult =
|
||||
getExpectedHolisticLandmarkerResult(
|
||||
HOLISTIC_RESULT, /* hasFaceBlendshapes= */ false, /* hasSegmentationMask= */ false);
|
||||
HolisticLandmarkerOptions options =
|
||||
HolisticLandmarkerOptions.builder()
|
||||
.setBaseOptions(
|
||||
BaseOptions.builder()
|
||||
.setModelAssetPath(HOLISTIC_LANDMARKER_BUNDLE_ASSET_FILE)
|
||||
.build())
|
||||
.setRunningMode(RunningMode.LIVE_STREAM)
|
||||
.setResultListener(
|
||||
(actualResult, inputImage) -> {
|
||||
assertActualResultApproximatelyEqualsToExpectedResult(
|
||||
actualResult, expectedResult);
|
||||
assertImageSizeIsExpected(inputImage);
|
||||
})
|
||||
.build();
|
||||
try (HolisticLandmarker holisticLandmarker =
|
||||
HolisticLandmarker.createFromOptions(
|
||||
ApplicationProvider.getApplicationContext(), options)) {
|
||||
for (int i = 0; i < 3; i++) {
|
||||
holisticLandmarker.detectAsync(image, /* timestampsMs= */ i);
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
private static MPImage getImageFromAsset(String filePath) throws Exception {
|
||||
AssetManager assetManager = ApplicationProvider.getApplicationContext().getAssets();
|
||||
InputStream istr = assetManager.open(filePath);
|
||||
return new BitmapImageBuilder(BitmapFactory.decodeStream(istr)).build();
|
||||
}
|
||||
|
||||
private static HolisticLandmarkerResult getExpectedHolisticLandmarkerResult(
|
||||
String resultPath, boolean hasFaceBlendshapes, boolean hasSegmentationMask) throws Exception {
|
||||
AssetManager assetManager = ApplicationProvider.getApplicationContext().getAssets();
|
||||
|
||||
HolisticResult holisticResult = HolisticResult.parseFrom(assetManager.open(resultPath));
|
||||
|
||||
Optional<ClassificationList> blendshapes =
|
||||
hasFaceBlendshapes
|
||||
? Optional.of(holisticResult.getFaceBlendshapes())
|
||||
: Optional.<ClassificationList>empty();
|
||||
Optional<MPImage> segmentationMask =
|
||||
hasSegmentationMask ? Optional.of(PLACEHOLDER_MASK) : Optional.<MPImage>empty();
|
||||
|
||||
return HolisticLandmarkerResult.create(
|
||||
holisticResult.getFaceLandmarks(),
|
||||
blendshapes,
|
||||
holisticResult.getPoseLandmarks(),
|
||||
LandmarkList.getDefaultInstance(),
|
||||
segmentationMask,
|
||||
holisticResult.getLeftHandLandmarks(),
|
||||
LandmarkList.getDefaultInstance(),
|
||||
holisticResult.getRightHandLandmarks(),
|
||||
LandmarkList.getDefaultInstance(),
|
||||
/* timestampMs= */ 0);
|
||||
}
|
||||
|
||||
private static void assertActualResultApproximatelyEqualsToExpectedResult(
|
||||
HolisticLandmarkerResult actualResult, HolisticLandmarkerResult expectedResult) {
|
||||
// Expects to have the same number of holistics detected.
|
||||
assertThat(actualResult.faceLandmarks()).hasSize(expectedResult.faceLandmarks().size());
|
||||
assertThat(actualResult.faceBlendshapes().isPresent())
|
||||
.isEqualTo(expectedResult.faceBlendshapes().isPresent());
|
||||
assertThat(actualResult.poseLandmarks()).hasSize(expectedResult.poseLandmarks().size());
|
||||
assertThat(actualResult.segmentationMask().isPresent())
|
||||
.isEqualTo(expectedResult.segmentationMask().isPresent());
|
||||
assertThat(actualResult.leftHandLandmarks()).hasSize(expectedResult.leftHandLandmarks().size());
|
||||
assertThat(actualResult.rightHandLandmarks())
|
||||
.hasSize(expectedResult.rightHandLandmarks().size());
|
||||
|
||||
// Actual face landmarks match expected face landmarks.
|
||||
assertThat(actualResult.faceLandmarks())
|
||||
.comparingElementsUsing(VALIDATE_LANDMARRKS)
|
||||
.containsExactlyElementsIn(expectedResult.faceLandmarks());
|
||||
|
||||
// Actual face blendshapes match expected face blendshapes.
|
||||
if (actualResult.faceBlendshapes().isPresent()) {
|
||||
assertThat(actualResult.faceBlendshapes().get())
|
||||
.comparingElementsUsing(VALIDATE_BLENDSHAPES)
|
||||
.containsExactlyElementsIn(expectedResult.faceBlendshapes().get());
|
||||
}
|
||||
|
||||
// Actual pose landmarks match expected pose landmarks.
|
||||
assertThat(actualResult.poseLandmarks())
|
||||
.comparingElementsUsing(VALIDATE_LANDMARRKS)
|
||||
.containsExactlyElementsIn(expectedResult.poseLandmarks());
|
||||
|
||||
if (actualResult.segmentationMask().isPresent()) {
|
||||
assertImageSizeIsExpected(actualResult.segmentationMask().get());
|
||||
}
|
||||
|
||||
// Actual left hand landmarks match expected left hand landmarks.
|
||||
assertThat(actualResult.leftHandLandmarks())
|
||||
.comparingElementsUsing(VALIDATE_LANDMARRKS)
|
||||
.containsExactlyElementsIn(expectedResult.leftHandLandmarks());
|
||||
|
||||
// Actual right hand landmarks match expected right hand landmarks.
|
||||
assertThat(actualResult.rightHandLandmarks())
|
||||
.comparingElementsUsing(VALIDATE_LANDMARRKS)
|
||||
.containsExactlyElementsIn(expectedResult.rightHandLandmarks());
|
||||
}
|
||||
|
||||
private static void assertImageSizeIsExpected(MPImage inputImage) {
|
||||
assertThat(inputImage).isNotNull();
|
||||
assertThat(inputImage.getWidth()).isEqualTo(IMAGE_WIDTH);
|
||||
assertThat(inputImage.getHeight()).isEqualTo(IMAGE_HEIGHT);
|
||||
}
|
||||
}
|
1
mediapipe/tasks/testdata/vision/BUILD
vendored
1
mediapipe/tasks/testdata/vision/BUILD
vendored
|
@ -224,6 +224,7 @@ filegroup(
|
|||
"hand_detector_result_one_hand.pbtxt",
|
||||
"hand_detector_result_one_hand_rotated.pbtxt",
|
||||
"hand_detector_result_two_hands.pbtxt",
|
||||
"male_full_height_hands_result_cpu.pbtxt",
|
||||
"pointing_up_landmarks.pbtxt",
|
||||
"pointing_up_rotated_landmarks.pbtxt",
|
||||
"portrait_expected_detection.pbtxt",
|
||||
|
|
Loading…
Reference in New Issue
Block a user