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HolisticLandmarker Java API

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PiperOrigin-RevId: 586113048
This commit is contained in:
Sebastian Schmidt 2023-11-28 14:57:41 -08:00 committed by Copybara-Service
parent a898215c52
commit 62bafd39bb
8 changed files with 1248 additions and 3 deletions
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7
mediapipe/tasks/java/com/google/mediapipe/tasks/mediapipe_tasks_aar.bzl
View File

@ -47,13 +47,14 @@ _VISION_TASKS_JAVA_PROTO_LITE_TARGETS = [
"//mediapipe/tasks/cc/vision/gesture_recognizer/proto:gesture_embedder_graph_options_java_proto_lite",
"//mediapipe/tasks/cc/vision/gesture_recognizer/proto:gesture_recognizer_graph_options_java_proto_lite",
"//mediapipe/tasks/cc/vision/gesture_recognizer/proto:hand_gesture_recognizer_graph_options_java_proto_lite",
"//mediapipe/tasks/cc/vision/hand_detector/proto:hand_detector_graph_options_java_proto_lite",
"//mediapipe/tasks/cc/vision/hand_landmarker/proto:hand_landmarker_graph_options_java_proto_lite",
"//mediapipe/tasks/cc/vision/hand_landmarker/proto:hand_landmarks_detector_graph_options_java_proto_lite",
"//mediapipe/tasks/cc/vision/holistic_landmarker/proto:holistic_landmarker_graph_options_java_proto_lite",
"//mediapipe/tasks/cc/vision/image_classifier/proto:image_classifier_graph_options_java_proto_lite",
"//mediapipe/tasks/cc/vision/image_embedder/proto:image_embedder_graph_options_java_proto_lite",
"//mediapipe/tasks/cc/vision/image_segmenter/proto:image_segmenter_graph_options_java_proto_lite",
"//mediapipe/tasks/cc/vision/image_segmenter/proto:segmenter_options_java_proto_lite",
"//mediapipe/tasks/cc/vision/hand_detector/proto:hand_detector_graph_options_java_proto_lite",
"//mediapipe/tasks/cc/vision/hand_landmarker/proto:hand_landmarker_graph_options_java_proto_lite",
"//mediapipe/tasks/cc/vision/hand_landmarker/proto:hand_landmarks_detector_graph_options_java_proto_lite",
"//mediapipe/tasks/cc/vision/object_detector/proto:object_detector_options_java_proto_lite",
"//mediapipe/tasks/cc/vision/pose_detector/proto:pose_detector_graph_options_java_proto_lite",
"//mediapipe/tasks/cc/vision/pose_landmarker/proto:pose_landmarker_graph_options_java_proto_lite",

12
mediapipe/tasks/java/com/google/mediapipe/tasks/vision/BUILD
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@ -67,6 +67,7 @@ cc_binary(
"//mediapipe/tasks/cc/vision/face_landmarker:face_landmarker_graph",
"//mediapipe/tasks/cc/vision/face_stylizer:face_stylizer_graph",
"//mediapipe/tasks/cc/vision/gesture_recognizer:gesture_recognizer_graph",
"//mediapipe/tasks/cc/vision/holistic_landmarker:holistic_landmarker_graph",
"//mediapipe/tasks/cc/vision/image_classifier:image_classifier_graph",
"//mediapipe/tasks/cc/vision/image_embedder:image_embedder_graph",
"//mediapipe/tasks/cc/vision/image_segmenter:image_segmenter_graph",
@ -429,6 +430,7 @@ filegroup(
android_library(
name = "holisticlandmarker",
srcs = [
"holisticlandmarker/HolisticLandmarker.java",
"holisticlandmarker/HolisticLandmarkerResult.java",
],
javacopts = [
@ -439,10 +441,20 @@ android_library(
":core",
"//mediapipe/framework/formats:classification_java_proto_lite",
"//mediapipe/framework/formats:landmark_java_proto_lite",
"//mediapipe/java/com/google/mediapipe/framework:android_framework",
"//mediapipe/java/com/google/mediapipe/framework/image",
"//mediapipe/tasks/cc/core/proto:base_options_java_proto_lite",
"//mediapipe/tasks/cc/vision/face_detector/proto:face_detector_graph_options_java_proto_lite",
"//mediapipe/tasks/cc/vision/face_landmarker/proto:face_landmarks_detector_graph_options_java_proto_lite",
"//mediapipe/tasks/cc/vision/hand_landmarker/proto:hand_landmarks_detector_graph_options_java_proto_lite",
"//mediapipe/tasks/cc/vision/holistic_landmarker/proto:holistic_landmarker_graph_options_java_proto_lite",
"//mediapipe/tasks/cc/vision/pose_detector/proto:pose_detector_graph_options_java_proto_lite",
"//mediapipe/tasks/cc/vision/pose_landmarker/proto:pose_landmarks_detector_graph_options_java_proto_lite",
"//mediapipe/tasks/java/com/google/mediapipe/tasks/components/containers:category",
"//mediapipe/tasks/java/com/google/mediapipe/tasks/components/containers:landmark",
"//mediapipe/tasks/java/com/google/mediapipe/tasks/components/containers:normalized_landmark",
"//mediapipe/tasks/java/com/google/mediapipe/tasks/core",
"//third_party:any_java_proto",
"//third_party:autovalue",
"@maven//:com_google_guava_guava",
],

8
mediapipe/tasks/java/com/google/mediapipe/tasks/vision/holisticlandmarker/AndroidManifest.xml Normal file
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@ -0,0 +1,8 @@
<?xml version="1.0" encoding="utf-8"?>
<manifest xmlns:android="http://schemas.android.com/apk/res/android"
package="com.google.mediapipe.tasks.vision.holisticlandmarker">
<uses-sdk android:minSdkVersion="24"
android:targetSdkVersion="30" />
</manifest>

668
mediapipe/tasks/java/com/google/mediapipe/tasks/vision/holisticlandmarker/HolisticLandmarker.java Normal file
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@ -0,0 +1,668 @@
// 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 android.content.Context;
import android.os.ParcelFileDescriptor;
import com.google.auto.value.AutoValue;
import com.google.mediapipe.formats.proto.LandmarkProto.LandmarkList;
import com.google.mediapipe.formats.proto.LandmarkProto.NormalizedLandmarkList;
import com.google.mediapipe.formats.proto.ClassificationProto.ClassificationList;
import com.google.mediapipe.framework.AndroidPacketGetter;
import com.google.mediapipe.framework.MediaPipeException;
import com.google.mediapipe.framework.Packet;
import com.google.mediapipe.framework.PacketGetter;
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.core.BaseOptions;
import com.google.mediapipe.tasks.core.ErrorListener;
import com.google.mediapipe.tasks.core.OutputHandler;
import com.google.mediapipe.tasks.core.OutputHandler.ResultListener;
import com.google.mediapipe.tasks.core.TaskInfo;
import com.google.mediapipe.tasks.core.TaskOptions;
import com.google.mediapipe.tasks.core.TaskRunner;
import com.google.mediapipe.tasks.core.proto.BaseOptionsProto;
import com.google.mediapipe.tasks.vision.core.BaseVisionTaskApi;
import com.google.mediapipe.tasks.vision.core.ImageProcessingOptions;
import com.google.mediapipe.tasks.vision.core.RunningMode;
import com.google.mediapipe.tasks.vision.facedetector.proto.FaceDetectorGraphOptionsProto.FaceDetectorGraphOptions;
import com.google.mediapipe.tasks.vision.facelandmarker.proto.FaceLandmarksDetectorGraphOptionsProto.FaceLandmarksDetectorGraphOptions;
import com.google.mediapipe.tasks.vision.handlandmarker.proto.HandLandmarksDetectorGraphOptionsProto.HandLandmarksDetectorGraphOptions;
import com.google.mediapipe.tasks.vision.holisticlandmarker.proto.HolisticLandmarkerGraphOptionsProto.HolisticLandmarkerGraphOptions;
import com.google.mediapipe.tasks.vision.posedetector.proto.PoseDetectorGraphOptionsProto.PoseDetectorGraphOptions;
import com.google.mediapipe.tasks.vision.poselandmarker.proto.PoseLandmarksDetectorGraphOptionsProto.PoseLandmarksDetectorGraphOptions;
import com.google.protobuf.Any;
import java.io.File;
import java.io.IOException;
import java.nio.ByteBuffer;
import java.util.ArrayList;
import java.util.Arrays;
import java.util.Collections;
import java.util.List;
import java.util.Optional;
/**
* Performs holistic landmarks detection on images.
*
* <p>This API expects a pre-trained holistic landmarks model asset bundle.
*
* <ul>
* <li>Input image {@link MPImage}
* <ul>
* <li>The image that holistic landmarks detection runs on.
* </ul>
* <li>Output {@link HolisticLandmarkerResult}
* <ul>
* <li>A HolisticLandmarkerResult containing holistic landmarks.
* </ul>
* </ul>
*/
public final class HolisticLandmarker extends BaseVisionTaskApi {
private static final String TAG = HolisticLandmarker.class.getSimpleName();
private static final String IMAGE_IN_STREAM_NAME = "image_in";
private static final String POSE_LANDMARKS_STREAM = "pose_landmarks";
private static final String POSE_WORLD_LANDMARKS_STREAM = "pose_world_landmarks";
private static final String POSE_SEGMENTATION_MASK_STREAM = "pose_segmentation_mask";
private static final String FACE_LANDMARKS_STREAM = "face_landmarks";
private static final String FACE_BLENDSHAPES_STREAM = "extra_blendshapes";
private static final String LEFT_HAND_LANDMARKS_STREAM = "left_hand_landmarks";
private static final String LEFT_HAND_WORLD_LANDMARKS_STREAM = "left_hand_world_landmarks";
private static final String RIGHT_HAND_LANDMARKS_STREAM = "right_hand_landmarks";
private static final String RIGHT_HAND_WORLD_LANDMARKS_STREAM = "right_hand_world_landmarks";
private static final String IMAGE_OUT_STREAM_NAME = "image_out";
private static final int FACE_LANDMARKS_OUT_STREAM_INDEX = 0;
private static final int POSE_LANDMARKS_OUT_STREAM_INDEX = 1;
private static final int POSE_WORLD_LANDMARKS_OUT_STREAM_INDEX = 2;
private static final int LEFT_HAND_LANDMARKS_OUT_STREAM_INDEX = 3;
private static final int LEFT_HAND_WORLD_LANDMARKS_OUT_STREAM_INDEX = 4;
private static final int RIGHT_HAND_LANDMARKS_OUT_STREAM_INDEX = 5;
private static final int RIGHT_HAND_WORLD_LANDMARKS_OUT_STREAM_INDEX = 6;
private static final int IMAGE_OUT_STREAM_INDEX = 7;
private static final float DEFAULT_PRESENCE_THRESHOLD = 0.5f;
private static final float DEFAULT_SUPPRESION_THRESHOLD = 0.3f;
private static final boolean DEFAULT_OUTPUT_FACE_BLENDSHAPES = false;
private static final boolean DEFAULT_OUTPUT_SEGMENTATION_MASKS = false;
private static final String TASK_GRAPH_NAME =
"mediapipe.tasks.vision.holistic_landmarker.HolisticLandmarkerGraph";
@SuppressWarnings("ConstantCaseForConstants")
private static final List<String> INPUT_STREAMS =
Collections.unmodifiableList(Arrays.asList("IMAGE:" + IMAGE_IN_STREAM_NAME));
static {
System.loadLibrary("mediapipe_tasks_vision_jni");
}
/**
* Creates a {@link HolisticLandmarker} instance from a model asset bundle path and the default
* {@link HolisticLandmarkerOptions}.
*
* @param context an Android {@link Context}.
* @param modelAssetPath path to the holistic landmarks model with metadata in the assets.
* @throws MediaPipeException if there is an error during {@link HolisticLandmarker} creation.
*/
public static HolisticLandmarker createFromFile(Context context, String modelAssetPath) {
BaseOptions baseOptions = BaseOptions.builder().setModelAssetPath(modelAssetPath).build();
return createFromOptions(
context, HolisticLandmarkerOptions.builder().setBaseOptions(baseOptions).build());
}
/**
* Creates a {@link HolisticLandmarker} instance from a model asset bundle file and the default
* {@link HolisticLandmarkerOptions}.
*
* @param context an Android {@link Context}.
* @param modelAssetFile the holistic landmarks model {@link File} instance.
* @throws IOException if an I/O error occurs when opening the tflite model file.
* @throws MediaPipeException if there is an error during {@link HolisticLandmarker} creation.
*/
public static HolisticLandmarker createFromFile(Context context, File modelAssetFile)
throws IOException {
try (ParcelFileDescriptor descriptor =
ParcelFileDescriptor.open(modelAssetFile, ParcelFileDescriptor.MODE_READ_ONLY)) {
BaseOptions baseOptions =
BaseOptions.builder().setModelAssetFileDescriptor(descriptor.getFd()).build();
return createFromOptions(
context, HolisticLandmarkerOptions.builder().setBaseOptions(baseOptions).build());
}
}
/**
* Creates a {@link HolisticLandmarker} instance from a model asset bundle buffer and the default
* {@link HolisticLandmarkerOptions}.
*
* @param context an Android {@link Context}.
* @param modelAssetBuffer a direct {@link ByteBuffer} or a {@link MappedByteBuffer} of the
* detection model.
* @throws MediaPipeException if there is an error during {@link HolisticLandmarker} creation.
*/
public static HolisticLandmarker createFromBuffer(
Context context, final ByteBuffer modelAssetBuffer) {
BaseOptions baseOptions = BaseOptions.builder().setModelAssetBuffer(modelAssetBuffer).build();
return createFromOptions(
context, HolisticLandmarkerOptions.builder().setBaseOptions(baseOptions).build());
}
/**
* Creates a {@link HolisticLandmarker} instance from a {@link HolisticLandmarkerOptions}.
*
* @param context an Android {@link Context}.
* @param landmarkerOptions a {@link HolisticLandmarkerOptions} instance.
* @throws MediaPipeException if there is an error during {@link HolisticLandmarker} creation.
*/
public static HolisticLandmarker createFromOptions(
Context context, HolisticLandmarkerOptions landmarkerOptions) {
List<String> outputStreams = new ArrayList<>();
outputStreams.add("FACE_LANDMARKS:" + FACE_LANDMARKS_STREAM);
outputStreams.add("POSE_LANDMARKS:" + POSE_LANDMARKS_STREAM);
outputStreams.add("POSE_WORLD_LANDMARKS:" + POSE_WORLD_LANDMARKS_STREAM);
outputStreams.add("LEFT_HAND_LANDMARKS:" + LEFT_HAND_LANDMARKS_STREAM);
outputStreams.add("LEFT_HAND_WORLD_LANDMARKS:" + LEFT_HAND_WORLD_LANDMARKS_STREAM);
outputStreams.add("RIGHT_HAND_LANDMARKS:" + RIGHT_HAND_LANDMARKS_STREAM);
outputStreams.add("RIGHT_HAND_WORLD_LANDMARKS:" + RIGHT_HAND_WORLD_LANDMARKS_STREAM);
outputStreams.add("IMAGE:" + IMAGE_OUT_STREAM_NAME);
int[] faceBlendshapesOutStreamIndex = new int[] {-1};
if (landmarkerOptions.outputFaceBlendshapes()) {
outputStreams.add("FACE_BLENDSHAPES:" + FACE_BLENDSHAPES_STREAM);
faceBlendshapesOutStreamIndex[0] = outputStreams.size() - 1;
}
int[] poseSegmentationMasksOutStreamIndex = new int[] {-1};
if (landmarkerOptions.outputPoseSegmentationMasks()) {
outputStreams.add("POSE_SEGMENTATION_MASK:" + POSE_SEGMENTATION_MASK_STREAM);
poseSegmentationMasksOutStreamIndex[0] = outputStreams.size() - 1;
}
OutputHandler<HolisticLandmarkerResult, MPImage> handler = new OutputHandler<>();
handler.setOutputPacketConverter(
new OutputHandler.OutputPacketConverter<HolisticLandmarkerResult, MPImage>() {
@Override
public HolisticLandmarkerResult convertToTaskResult(List<Packet> packets) {
// If there are no detected landmarks, just returns empty lists.
if (packets.get(FACE_LANDMARKS_OUT_STREAM_INDEX).isEmpty()) {
return HolisticLandmarkerResult.createEmpty(
BaseVisionTaskApi.generateResultTimestampMs(
landmarkerOptions.runningMode(),
packets.get(FACE_LANDMARKS_OUT_STREAM_INDEX)));
}
NormalizedLandmarkList faceLandmarkProtos =
PacketGetter.getProto(
packets.get(FACE_LANDMARKS_OUT_STREAM_INDEX), NormalizedLandmarkList.parser());
Optional<ClassificationList> faceBlendshapeProtos =
landmarkerOptions.outputFaceBlendshapes()
? Optional.of(
PacketGetter.getProto(
packets.get(faceBlendshapesOutStreamIndex[0]),
ClassificationList.parser()))
: Optional.empty();
NormalizedLandmarkList poseLandmarkProtos =
PacketGetter.getProto(
packets.get(POSE_LANDMARKS_OUT_STREAM_INDEX), NormalizedLandmarkList.parser());
LandmarkList poseWorldLandmarkProtos =
PacketGetter.getProto(
packets.get(POSE_WORLD_LANDMARKS_OUT_STREAM_INDEX), LandmarkList.parser());
Optional<MPImage> segmentationMask =
landmarkerOptions.outputPoseSegmentationMasks()
? Optional.of(
getSegmentationMask(packets, poseSegmentationMasksOutStreamIndex[0]))
: Optional.empty();
NormalizedLandmarkList leftHandLandmarkProtos =
PacketGetter.getProto(
packets.get(LEFT_HAND_LANDMARKS_OUT_STREAM_INDEX),
NormalizedLandmarkList.parser());
LandmarkList leftHandWorldLandmarkProtos =
PacketGetter.getProto(
packets.get(LEFT_HAND_WORLD_LANDMARKS_OUT_STREAM_INDEX), LandmarkList.parser());
NormalizedLandmarkList rightHandLandmarkProtos =
PacketGetter.getProto(
packets.get(RIGHT_HAND_LANDMARKS_OUT_STREAM_INDEX),
NormalizedLandmarkList.parser());
LandmarkList rightHandWorldLandmarkProtos =
PacketGetter.getProto(
packets.get(RIGHT_HAND_WORLD_LANDMARKS_OUT_STREAM_INDEX),
LandmarkList.parser());
return HolisticLandmarkerResult.create(
faceLandmarkProtos,
faceBlendshapeProtos,
poseLandmarkProtos,
poseWorldLandmarkProtos,
segmentationMask,
leftHandLandmarkProtos,
leftHandWorldLandmarkProtos,
rightHandLandmarkProtos,
rightHandWorldLandmarkProtos,
BaseVisionTaskApi.generateResultTimestampMs(
landmarkerOptions.runningMode(), packets.get(FACE_LANDMARKS_OUT_STREAM_INDEX)));
}
@Override
public MPImage convertToTaskInput(List<Packet> packets) {
return new BitmapImageBuilder(
AndroidPacketGetter.getBitmapFromRgb(packets.get(IMAGE_OUT_STREAM_INDEX)))
.build();
}
});
landmarkerOptions.resultListener().ifPresent(handler::setResultListener);
landmarkerOptions.errorListener().ifPresent(handler::setErrorListener);
TaskRunner runner =
TaskRunner.create(
context,
TaskInfo.<HolisticLandmarkerOptions>builder()
.setTaskName(HolisticLandmarker.class.getSimpleName())
.setTaskRunningModeName(landmarkerOptions.runningMode().name())
.setTaskGraphName(TASK_GRAPH_NAME)
.setInputStreams(INPUT_STREAMS)
.setOutputStreams(outputStreams)
.setTaskOptions(landmarkerOptions)
.setEnableFlowLimiting(landmarkerOptions.runningMode() == RunningMode.LIVE_STREAM)
.build(),
handler);
return new HolisticLandmarker(runner, landmarkerOptions.runningMode());
}
/**
* Constructor to initialize an {@link HolisticLandmarker} from a {@link TaskRunner} and a {@link
* RunningMode}.
*
* @param taskRunner a {@link TaskRunner}.
* @param runningMode a mediapipe vision task {@link RunningMode}.
*/
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();
}
}

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<?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>

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@ -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

512
mediapipe/tasks/javatests/com/google/mediapipe/tasks/vision/holisticlandmarker/HolisticLandmarkerTest.java Normal file
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// 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
View File

@ -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",