Add hand landmarker C++ api.
PiperOrigin-RevId: 486791711
This commit is contained in:
MediaPipe Team
Copybara-Service
parent
571c0b1fef
commit
6f38a7a21f
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@ -30,6 +30,15 @@ cc_library(
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],
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)
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cc_library(
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name = "hand_landmarks_detection_result",
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hdrs = ["hand_landmarks_detection_result.h"],
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deps = [
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"//mediapipe/framework/formats:classification_cc_proto",
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"//mediapipe/framework/formats:landmark_cc_proto",
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],
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)
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cc_library(
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name = "category",
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srcs = ["category.cc"],
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@ -0,0 +1,43 @@
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/* Copyright 2022 The MediaPipe Authors. All Rights Reserved.
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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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http://www.apache.org/licenses/LICENSE-2.0
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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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==============================================================================*/
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#ifndef MEDIAPIPE_TASKS_CC_COMPONENTS_CONTAINERS_HAND_LANDMARKS_DETECTION_RESULT_H_
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#define MEDIAPIPE_TASKS_CC_COMPONENTS_CONTAINERS_HAND_LANDMARKS_DETECTION_RESULT_H_
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#include "mediapipe/framework/formats/classification.pb.h"
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#include "mediapipe/framework/formats/landmark.pb.h"
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namespace mediapipe {
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namespace tasks {
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namespace components {
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namespace containers {
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// The hand landmarks detection result from HandLandmarker, where each vector
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// element represents a single hand detected in the image.
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struct HandLandmarksDetectionResult {
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// Classification of handedness.
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std::vector<mediapipe::ClassificationList> handedness;
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// Detected hand landmarks in normalized image coordinates.
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std::vector<mediapipe::NormalizedLandmarkList> hand_landmarks;
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// Detected hand landmarks in world coordinates.
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std::vector<mediapipe::LandmarkList> hand_world_landmarks;
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};
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} // namespace containers
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} // namespace components
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} // namespace tasks
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} // namespace mediapipe
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#endif // MEDIAPIPE_TASKS_CC_COMPONENTS_CONTAINERS_HAND_LANDMARKS_DETECTION_RESULT_H_
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@ -110,4 +110,38 @@ cc_library(
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alwayslink = 1,
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)
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cc_library(
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name = "hand_landmarker",
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srcs = ["hand_landmarker.cc"],
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hdrs = ["hand_landmarker.h"],
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deps = [
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":hand_landmarker_graph",
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"//mediapipe/framework/api2:builder",
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"//mediapipe/framework/api2:port",
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"//mediapipe/framework/formats:classification_cc_proto",
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"//mediapipe/framework/formats:image",
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"//mediapipe/framework/formats:landmark_cc_proto",
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"//mediapipe/framework/formats:rect_cc_proto",
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"//mediapipe/tasks/cc:common",
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"//mediapipe/tasks/cc/components:image_preprocessing",
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"//mediapipe/tasks/cc/components/containers:hand_landmarks_detection_result",
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"//mediapipe/tasks/cc/components/processors:classifier_options",
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"//mediapipe/tasks/cc/components/processors/proto:classifier_options_cc_proto",
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"//mediapipe/tasks/cc/core:base_options",
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"//mediapipe/tasks/cc/core:base_task_api",
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"//mediapipe/tasks/cc/core:model_resources",
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"//mediapipe/tasks/cc/core:task_runner",
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"//mediapipe/tasks/cc/core:utils",
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"//mediapipe/tasks/cc/core/proto:inference_subgraph_cc_proto",
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"//mediapipe/tasks/cc/vision/core:base_vision_task_api",
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"//mediapipe/tasks/cc/vision/core:image_processing_options",
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"//mediapipe/tasks/cc/vision/core:running_mode",
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"//mediapipe/tasks/cc/vision/core:vision_task_api_factory",
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"//mediapipe/tasks/cc/vision/hand_detector/proto:hand_detector_graph_options_cc_proto",
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"//mediapipe/tasks/cc/vision/hand_landmarker/proto:hand_landmarker_graph_options_cc_proto",
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"//mediapipe/tasks/cc/vision/hand_landmarker/proto:hand_landmarks_detector_graph_options_cc_proto",
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"@com_google_absl//absl/status:statusor",
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],
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)
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# TODO: Enable this test
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269
mediapipe/tasks/cc/vision/hand_landmarker/hand_landmarker.cc
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269
mediapipe/tasks/cc/vision/hand_landmarker/hand_landmarker.cc
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@ -0,0 +1,269 @@
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/* Copyright 2022 The MediaPipe Authors. All Rights Reserved.
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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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http://www.apache.org/licenses/LICENSE-2.0
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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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==============================================================================*/
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#include "mediapipe/tasks/cc/vision/hand_landmarker/hand_landmarker.h"
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#include "mediapipe/framework/api2/builder.h"
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#include "mediapipe/framework/api2/port.h"
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#include "mediapipe/framework/formats/classification.pb.h"
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#include "mediapipe/framework/formats/image.h"
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#include "mediapipe/framework/formats/landmark.pb.h"
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#include "mediapipe/framework/formats/rect.pb.h"
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#include "mediapipe/tasks/cc/common.h"
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#include "mediapipe/tasks/cc/components/containers/hand_landmarks_detection_result.h"
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#include "mediapipe/tasks/cc/components/image_preprocessing.h"
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#include "mediapipe/tasks/cc/components/processors/proto/classifier_options.pb.h"
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#include "mediapipe/tasks/cc/core/base_task_api.h"
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#include "mediapipe/tasks/cc/core/model_resources.h"
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#include "mediapipe/tasks/cc/core/proto/inference_subgraph.pb.h"
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#include "mediapipe/tasks/cc/core/task_runner.h"
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#include "mediapipe/tasks/cc/core/utils.h"
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#include "mediapipe/tasks/cc/vision/core/base_vision_task_api.h"
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#include "mediapipe/tasks/cc/vision/core/image_processing_options.h"
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#include "mediapipe/tasks/cc/vision/core/vision_task_api_factory.h"
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#include "mediapipe/tasks/cc/vision/hand_detector/proto/hand_detector_graph_options.pb.h"
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#include "mediapipe/tasks/cc/vision/hand_landmarker/proto/hand_landmarker_graph_options.pb.h"
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#include "mediapipe/tasks/cc/vision/hand_landmarker/proto/hand_landmarks_detector_graph_options.pb.h"
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namespace mediapipe {
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namespace tasks {
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namespace vision {
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namespace hand_landmarker {
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namespace {
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using HandLandmarkerGraphOptionsProto = ::mediapipe::tasks::vision::
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hand_landmarker::proto::HandLandmarkerGraphOptions;
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using ::mediapipe::tasks::components::containers::HandLandmarksDetectionResult;
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constexpr char kHandLandmarkerGraphTypeName[] =
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"mediapipe.tasks.vision.hand_landmarker.HandLandmarkerGraph";
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constexpr char kImageTag[] = "IMAGE";
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constexpr char kImageInStreamName[] = "image_in";
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constexpr char kImageOutStreamName[] = "image_out";
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constexpr char kNormRectTag[] = "NORM_RECT";
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constexpr char kNormRectStreamName[] = "norm_rect_in";
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constexpr char kHandednessTag[] = "HANDEDNESS";
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constexpr char kHandednessStreamName[] = "handedness";
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constexpr char kHandLandmarksTag[] = "LANDMARKS";
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constexpr char kHandLandmarksStreamName[] = "landmarks";
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constexpr char kHandWorldLandmarksTag[] = "WORLD_LANDMARKS";
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constexpr char kHandWorldLandmarksStreamName[] = "world_landmarks";
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constexpr int kMicroSecondsPerMilliSecond = 1000;
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// Creates a MediaPipe graph config that contains a subgraph node of
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// "mediapipe.tasks.vision.hand_ladnamrker.HandLandmarkerGraph". If the task is
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// running in the live stream mode, a "FlowLimiterCalculator" will be added to
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// limit the number of frames in flight.
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CalculatorGraphConfig CreateGraphConfig(
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std::unique_ptr<HandLandmarkerGraphOptionsProto> options,
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bool enable_flow_limiting) {
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api2::builder::Graph graph;
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auto& subgraph = graph.AddNode(kHandLandmarkerGraphTypeName);
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subgraph.GetOptions<HandLandmarkerGraphOptionsProto>().Swap(options.get());
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graph.In(kImageTag).SetName(kImageInStreamName);
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graph.In(kNormRectTag).SetName(kNormRectStreamName);
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subgraph.Out(kHandednessTag).SetName(kHandednessStreamName) >>
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graph.Out(kHandednessTag);
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subgraph.Out(kHandLandmarksTag).SetName(kHandLandmarksStreamName) >>
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graph.Out(kHandLandmarksTag);
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subgraph.Out(kHandWorldLandmarksTag).SetName(kHandWorldLandmarksStreamName) >>
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graph.Out(kHandWorldLandmarksTag);
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subgraph.Out(kImageTag).SetName(kImageOutStreamName) >> graph.Out(kImageTag);
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if (enable_flow_limiting) {
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return tasks::core::AddFlowLimiterCalculator(
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graph, subgraph, {kImageTag, kNormRectTag}, kHandLandmarksTag);
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}
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graph.In(kImageTag) >> subgraph.In(kImageTag);
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graph.In(kNormRectTag) >> subgraph.In(kNormRectTag);
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return graph.GetConfig();
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}
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// Converts the user-facing HandLandmarkerOptions struct to the internal
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// HandLandmarkerGraphOptions proto.
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std::unique_ptr<HandLandmarkerGraphOptionsProto>
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ConvertHandLandmarkerGraphOptionsProto(HandLandmarkerOptions* options) {
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auto options_proto = std::make_unique<HandLandmarkerGraphOptionsProto>();
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auto base_options_proto = std::make_unique<tasks::core::proto::BaseOptions>(
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tasks::core::ConvertBaseOptionsToProto(&(options->base_options)));
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options_proto->mutable_base_options()->Swap(base_options_proto.get());
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options_proto->mutable_base_options()->set_use_stream_mode(
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options->running_mode != core::RunningMode::IMAGE);
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// Configure hand detector options.
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auto* hand_detector_graph_options =
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options_proto->mutable_hand_detector_graph_options();
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hand_detector_graph_options->set_num_hands(options->num_hands);
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hand_detector_graph_options->set_min_detection_confidence(
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options->min_hand_detection_confidence);
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// Configure hand landmark detector options.
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options_proto->set_min_tracking_confidence(options->min_tracking_confidence);
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auto* hand_landmarks_detector_graph_options =
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options_proto->mutable_hand_landmarks_detector_graph_options();
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hand_landmarks_detector_graph_options->set_min_detection_confidence(
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options->min_hand_presence_confidence);
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return options_proto;
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}
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} // namespace
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absl::StatusOr<std::unique_ptr<HandLandmarker>> HandLandmarker::Create(
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std::unique_ptr<HandLandmarkerOptions> options) {
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auto options_proto = ConvertHandLandmarkerGraphOptionsProto(options.get());
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tasks::core::PacketsCallback packets_callback = nullptr;
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if (options->result_callback) {
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auto result_callback = options->result_callback;
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packets_callback = [=](absl::StatusOr<tasks::core::PacketMap>
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status_or_packets) {
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if (!status_or_packets.ok()) {
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Image image;
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result_callback(status_or_packets.status(), image,
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Timestamp::Unset().Value());
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return;
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}
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if (status_or_packets.value()[kImageOutStreamName].IsEmpty()) {
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return;
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}
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Packet image_packet = status_or_packets.value()[kImageOutStreamName];
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if (status_or_packets.value()[kHandLandmarksStreamName].IsEmpty()) {
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Packet empty_packet =
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status_or_packets.value()[kHandLandmarksStreamName];
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result_callback(
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{HandLandmarksDetectionResult()}, image_packet.Get<Image>(),
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empty_packet.Timestamp().Value() / kMicroSecondsPerMilliSecond);
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return;
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}
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Packet handedness_packet =
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status_or_packets.value()[kHandednessStreamName];
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Packet hand_landmarks_packet =
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status_or_packets.value()[kHandLandmarksStreamName];
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Packet hand_world_landmarks_packet =
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status_or_packets.value()[kHandWorldLandmarksStreamName];
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result_callback(
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{{handedness_packet.Get<std::vector<ClassificationList>>(),
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hand_landmarks_packet.Get<std::vector<NormalizedLandmarkList>>(),
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hand_world_landmarks_packet.Get<std::vector<LandmarkList>>()}},
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image_packet.Get<Image>(),
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hand_landmarks_packet.Timestamp().Value() /
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kMicroSecondsPerMilliSecond);
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};
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}
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return core::VisionTaskApiFactory::Create<HandLandmarker,
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HandLandmarkerGraphOptionsProto>(
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CreateGraphConfig(
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std::move(options_proto),
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options->running_mode == core::RunningMode::LIVE_STREAM),
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std::move(options->base_options.op_resolver), options->running_mode,
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std::move(packets_callback));
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}
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absl::StatusOr<HandLandmarksDetectionResult> HandLandmarker::Detect(
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mediapipe::Image image,
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std::optional<core::ImageProcessingOptions> image_processing_options) {
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if (image.UsesGpu()) {
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return CreateStatusWithPayload(
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absl::StatusCode::kInvalidArgument,
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"GPU input images are currently not supported.",
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MediaPipeTasksStatus::kRunnerUnexpectedInputError);
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}
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ASSIGN_OR_RETURN(
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NormalizedRect norm_rect,
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ConvertToNormalizedRect(image_processing_options, /*roi_allowed=*/false));
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ASSIGN_OR_RETURN(
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auto output_packets,
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ProcessImageData(
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{{kImageInStreamName, MakePacket<Image>(std::move(image))},
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{kNormRectStreamName,
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MakePacket<NormalizedRect>(std::move(norm_rect))}}));
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if (output_packets[kHandLandmarksStreamName].IsEmpty()) {
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return {HandLandmarksDetectionResult()};
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}
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return {{/* handedness= */
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{output_packets[kHandednessStreamName]
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.Get<std::vector<mediapipe::ClassificationList>>()},
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/* hand_landmarks= */
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{output_packets[kHandLandmarksStreamName]
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.Get<std::vector<mediapipe::NormalizedLandmarkList>>()},
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/* hand_world_landmarks */
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{output_packets[kHandWorldLandmarksStreamName]
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.Get<std::vector<mediapipe::LandmarkList>>()}}};
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}
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absl::StatusOr<HandLandmarksDetectionResult> HandLandmarker::DetectForVideo(
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mediapipe::Image image, int64 timestamp_ms,
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std::optional<core::ImageProcessingOptions> image_processing_options) {
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if (image.UsesGpu()) {
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return CreateStatusWithPayload(
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absl::StatusCode::kInvalidArgument,
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absl::StrCat("GPU input images are currently not supported."),
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MediaPipeTasksStatus::kRunnerUnexpectedInputError);
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}
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ASSIGN_OR_RETURN(
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NormalizedRect norm_rect,
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ConvertToNormalizedRect(image_processing_options, /*roi_allowed=*/false));
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ASSIGN_OR_RETURN(
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auto output_packets,
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ProcessVideoData(
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{{kImageInStreamName,
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MakePacket<Image>(std::move(image))
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.At(Timestamp(timestamp_ms * kMicroSecondsPerMilliSecond))},
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{kNormRectStreamName,
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MakePacket<NormalizedRect>(std::move(norm_rect))
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.At(Timestamp(timestamp_ms * kMicroSecondsPerMilliSecond))}}));
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if (output_packets[kHandLandmarksStreamName].IsEmpty()) {
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return {HandLandmarksDetectionResult()};
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}
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return {
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{/* handedness= */
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{output_packets[kHandednessStreamName]
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.Get<std::vector<mediapipe::ClassificationList>>()},
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/* hand_landmarks= */
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{output_packets[kHandLandmarksStreamName]
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.Get<std::vector<mediapipe::NormalizedLandmarkList>>()},
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/* hand_world_landmarks */
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{output_packets[kHandWorldLandmarksStreamName]
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.Get<std::vector<mediapipe::LandmarkList>>()}},
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};
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}
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absl::Status HandLandmarker::DetectAsync(
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mediapipe::Image image, int64 timestamp_ms,
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std::optional<core::ImageProcessingOptions> image_processing_options) {
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if (image.UsesGpu()) {
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return CreateStatusWithPayload(
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absl::StatusCode::kInvalidArgument,
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absl::StrCat("GPU input images are currently not supported."),
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MediaPipeTasksStatus::kRunnerUnexpectedInputError);
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}
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ASSIGN_OR_RETURN(
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NormalizedRect norm_rect,
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ConvertToNormalizedRect(image_processing_options, /*roi_allowed=*/false));
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return SendLiveStreamData(
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{{kImageInStreamName,
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MakePacket<Image>(std::move(image))
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.At(Timestamp(timestamp_ms * kMicroSecondsPerMilliSecond))},
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{kNormRectStreamName,
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MakePacket<NormalizedRect>(std::move(norm_rect))
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.At(Timestamp(timestamp_ms * kMicroSecondsPerMilliSecond))}});
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}
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} // namespace hand_landmarker
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} // namespace vision
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} // namespace tasks
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} // namespace mediapipe
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192
mediapipe/tasks/cc/vision/hand_landmarker/hand_landmarker.h
Normal file
192
mediapipe/tasks/cc/vision/hand_landmarker/hand_landmarker.h
Normal file
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@ -0,0 +1,192 @@
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/* Copyright 2022 The MediaPipe Authors. All Rights Reserved.
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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
|
||||
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
|
||||
limitations under the License.
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==============================================================================*/
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#ifndef MEDIAPIPE_TASKS_CC_VISION_HAND_LANDMARKER_HAND_LANDMARKER_H_
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#define MEDIAPIPE_TASKS_CC_VISION_HAND_LANDMARKER_HAND_LANDMARKER_H_
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#include <memory>
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#include <optional>
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#include <vector>
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#include "absl/status/statusor.h"
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#include "mediapipe/framework/formats/classification.pb.h"
|
||||
#include "mediapipe/framework/formats/image.h"
|
||||
#include "mediapipe/framework/formats/landmark.pb.h"
|
||||
#include "mediapipe/tasks/cc/components/containers/hand_landmarks_detection_result.h"
|
||||
#include "mediapipe/tasks/cc/components/processors/classifier_options.h"
|
||||
#include "mediapipe/tasks/cc/core/base_options.h"
|
||||
#include "mediapipe/tasks/cc/vision/core/base_vision_task_api.h"
|
||||
#include "mediapipe/tasks/cc/vision/core/image_processing_options.h"
|
||||
#include "mediapipe/tasks/cc/vision/core/running_mode.h"
|
||||
|
||||
namespace mediapipe {
|
||||
namespace tasks {
|
||||
namespace vision {
|
||||
namespace hand_landmarker {
|
||||
|
||||
struct HandLandmarkerOptions {
|
||||
// Base options for configuring MediaPipe Tasks library, such as specifying
|
||||
// the TfLite model bundle file with metadata, accelerator options, op
|
||||
// resolver, etc.
|
||||
tasks::core::BaseOptions base_options;
|
||||
|
||||
// The running mode of the task. Default to the image mode.
|
||||
// HandLandmarker has three running modes:
|
||||
// 1) The image mode for detecting hand landmarks on single image inputs.
|
||||
// 2) The video mode for detecting hand landmarks on the decoded frames of a
|
||||
// video.
|
||||
// 3) The live stream mode for detecting hand landmarks on the live stream of
|
||||
// input data, such as from camera. In this mode, the "result_callback"
|
||||
// below must be specified to receive the detection results asynchronously.
|
||||
core::RunningMode running_mode = core::RunningMode::IMAGE;
|
||||
|
||||
// The maximum number of hands can be detected by the HandLandmarker.
|
||||
int num_hands = 1;
|
||||
|
||||
// The minimum confidence score for the hand detection to be considered
|
||||
// successful.
|
||||
float min_hand_detection_confidence = 0.5;
|
||||
|
||||
// The minimum confidence score of hand presence score in the hand landmark
|
||||
// detection.
|
||||
float min_hand_presence_confidence = 0.5;
|
||||
|
||||
// The minimum confidence score for the hand tracking to be considered
|
||||
// successful.
|
||||
float min_tracking_confidence = 0.5;
|
||||
|
||||
// The user-defined result callback for processing live stream data.
|
||||
// The result callback should only be specified when the running mode is set
|
||||
// to RunningMode::LIVE_STREAM.
|
||||
std::function<void(
|
||||
absl::StatusOr<components::containers::HandLandmarksDetectionResult>,
|
||||
const Image&, int64)>
|
||||
result_callback = nullptr;
|
||||
};
|
||||
|
||||
// Performs hand landmarks detection on the given image.
|
||||
//
|
||||
// TODO add the link to DevSite.
|
||||
// This API expects a pre-trained hand landmarker model asset bundle.
|
||||
//
|
||||
// Inputs:
|
||||
// Image
|
||||
// - The image that hand landmarks detection runs on.
|
||||
// std::optional<NormalizedRect>
|
||||
// - If provided, can be used to specify the rotation to apply to the image
|
||||
// before performing hand landmarks detection, by setting its 'rotation'
|
||||
// field in radians (e.g. 'M_PI / 2' for a 90° anti-clockwise rotation).
|
||||
// Note that specifying a region-of-interest using the 'x_center',
|
||||
// 'y_center', 'width' and 'height' fields is NOT supported and will
|
||||
// result in an invalid argument error being returned.
|
||||
// Outputs:
|
||||
// HandLandmarksDetectionResult
|
||||
// - The hand landmarks detection results.
|
||||
class HandLandmarker : tasks::vision::core::BaseVisionTaskApi {
|
||||
public:
|
||||
using BaseVisionTaskApi::BaseVisionTaskApi;
|
||||
|
||||
// Creates a HandLandmarker from a HandLandmarkerOptions to process image data
|
||||
// or streaming data. Hand landmarker can be created with one of the following
|
||||
// three running modes:
|
||||
// 1) Image mode for detecting hand landmarks on single image inputs. Users
|
||||
// provide mediapipe::Image to the `Detect` method, and will receive the
|
||||
// deteced hand landmarks results as the return value.
|
||||
// 2) Video mode for detecting hand landmarks on the decoded frames of a
|
||||
// video. Users call `DetectForVideo` method, and will receive the detected
|
||||
// hand landmarks results as the return value.
|
||||
// 3) Live stream mode for detecting hand landmarks on the live stream of the
|
||||
// input data, such as from camera. Users call `DetectAsync` to push the
|
||||
// image data into the HandLandmarker, the detected results along with the
|
||||
// input timestamp and the image that hand landmarker runs on will be
|
||||
// available in the result callback when the hand landmarker finishes the
|
||||
// work.
|
||||
static absl::StatusOr<std::unique_ptr<HandLandmarker>> Create(
|
||||
std::unique_ptr<HandLandmarkerOptions> options);
|
||||
|
||||
// Performs hand landmarks detection on the given image.
|
||||
// Only use this method when the HandLandmarker is created with the image
|
||||
// running mode.
|
||||
//
|
||||
// The optional 'image_processing_options' parameter can be used to specify
|
||||
// the rotation to apply to the image before performing detection, by setting
|
||||
// its 'rotation_degrees' field. Note that specifying a region-of-interest
|
||||
// using the 'region_of_interest' field is NOT supported and will result in an
|
||||
// invalid argument error being returned.
|
||||
//
|
||||
// The image can be of any size with format RGB or RGBA.
|
||||
// TODO: Describes how the input image will be preprocessed
|
||||
// after the yuv support is implemented.
|
||||
absl::StatusOr<components::containers::HandLandmarksDetectionResult> Detect(
|
||||
Image image,
|
||||
std::optional<core::ImageProcessingOptions> image_processing_options =
|
||||
std::nullopt);
|
||||
|
||||
// Performs hand landmarks detection on the provided video frame.
|
||||
// Only use this method when the HandLandmarker is created with the video
|
||||
// running mode.
|
||||
//
|
||||
// The optional 'image_processing_options' parameter can be used to specify
|
||||
// the rotation to apply to the image before performing detection, by setting
|
||||
// its 'rotation_degrees' field. Note that specifying a region-of-interest
|
||||
// using the 'region_of_interest' field is NOT supported and will result in an
|
||||
// invalid argument error being returned.
|
||||
//
|
||||
// The image can be of any size with format RGB or RGBA. It's required to
|
||||
// provide the video frame's timestamp (in milliseconds). The input timestamps
|
||||
// must be monotonically increasing.
|
||||
absl::StatusOr<components::containers::HandLandmarksDetectionResult>
|
||||
DetectForVideo(Image image, int64 timestamp_ms,
|
||||
std::optional<core::ImageProcessingOptions>
|
||||
image_processing_options = std::nullopt);
|
||||
|
||||
// Sends live image data to perform hand landmarks detection, and the results
|
||||
// will be available via the "result_callback" provided in the
|
||||
// HandLandmarkerOptions. Only use this method when the HandLandmarker
|
||||
// is created with the live stream running mode.
|
||||
//
|
||||
// The image can be of any size with format RGB or RGBA. It's required to
|
||||
// provide a timestamp (in milliseconds) to indicate when the input image is
|
||||
// sent to the hand landmarker. The input timestamps must be monotonically
|
||||
// increasing.
|
||||
//
|
||||
// The optional 'image_processing_options' parameter can be used to specify
|
||||
// the rotation to apply to the image before performing detection, by setting
|
||||
// its 'rotation_degrees' field. Note that specifying a region-of-interest
|
||||
// using the 'region_of_interest' field is NOT supported and will result in an
|
||||
// invalid argument error being returned.
|
||||
//
|
||||
// The "result_callback" provides
|
||||
// - A vector of HandLandmarksDetectionResult, each is the detected results
|
||||
// for a input frame.
|
||||
// - The const reference to the corresponding input image that the hand
|
||||
// landmarker runs on. Note that the const reference to the image will no
|
||||
// longer be valid when the callback returns. To access the image data
|
||||
// outside of the callback, callers need to make a copy of the image.
|
||||
// - The input timestamp in milliseconds.
|
||||
absl::Status DetectAsync(Image image, int64 timestamp_ms,
|
||||
std::optional<core::ImageProcessingOptions>
|
||||
image_processing_options = std::nullopt);
|
||||
|
||||
// Shuts down the HandLandmarker when all works are done.
|
||||
absl::Status Close() { return runner_->Close(); }
|
||||
};
|
||||
|
||||
} // namespace hand_landmarker
|
||||
} // namespace vision
|
||||
} // namespace tasks
|
||||
} // namespace mediapipe
|
||||
|
||||
#endif // MEDIAPIPE_TASKS_CC_VISION_HAND_LANDMARKER_HAND_LANDMARKER_H_
|
||||
|
|
@ -0,0 +1,511 @@
|
|||
/* Copyright 2022 The MediaPipe Authors. All Rights Reserved.
|
||||
|
||||
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.
|
||||
==============================================================================*/
|
||||
|
||||
#include "mediapipe/tasks/cc/vision/hand_landmarker/hand_landmarker.h"
|
||||
|
||||
#include <cmath>
|
||||
#include <memory>
|
||||
#include <string>
|
||||
#include <utility>
|
||||
|
||||
#include "absl/flags/flag.h"
|
||||
#include "absl/status/status.h"
|
||||
#include "absl/status/statusor.h"
|
||||
#include "absl/strings/string_view.h"
|
||||
#include "mediapipe/framework/deps/file_path.h"
|
||||
#include "mediapipe/framework/formats/classification.pb.h"
|
||||
#include "mediapipe/framework/formats/image.h"
|
||||
#include "mediapipe/framework/formats/landmark.pb.h"
|
||||
#include "mediapipe/framework/port/file_helpers.h"
|
||||
#include "mediapipe/framework/port/gmock.h"
|
||||
#include "mediapipe/framework/port/gtest.h"
|
||||
#include "mediapipe/tasks/cc/common.h"
|
||||
#include "mediapipe/tasks/cc/components/containers/hand_landmarks_detection_result.h"
|
||||
#include "mediapipe/tasks/cc/components/containers/proto/landmarks_detection_result.pb.h"
|
||||
#include "mediapipe/tasks/cc/components/containers/rect.h"
|
||||
#include "mediapipe/tasks/cc/components/processors/proto/classifier_options.pb.h"
|
||||
#include "mediapipe/tasks/cc/core/base_options.h"
|
||||
#include "mediapipe/tasks/cc/vision/core/image_processing_options.h"
|
||||
#include "mediapipe/tasks/cc/vision/utils/image_utils.h"
|
||||
#include "tensorflow/lite/core/shims/cc/shims_test_util.h"
|
||||
|
||||
namespace mediapipe {
|
||||
namespace tasks {
|
||||
namespace vision {
|
||||
namespace hand_landmarker {
|
||||
|
||||
namespace {
|
||||
|
||||
using ::file::Defaults;
|
||||
using ::mediapipe::file::JoinPath;
|
||||
using ::mediapipe::tasks::components::containers::HandLandmarksDetectionResult;
|
||||
using ::mediapipe::tasks::components::containers::Rect;
|
||||
using ::mediapipe::tasks::containers::proto::LandmarksDetectionResult;
|
||||
using ::mediapipe::tasks::vision::core::ImageProcessingOptions;
|
||||
using ::testing::EqualsProto;
|
||||
using ::testing::HasSubstr;
|
||||
using ::testing::Optional;
|
||||
using ::testing::Pointwise;
|
||||
using ::testing::TestParamInfo;
|
||||
using ::testing::TestWithParam;
|
||||
using ::testing::Values;
|
||||
using ::testing::proto::Approximately;
|
||||
using ::testing::proto::Partially;
|
||||
|
||||
constexpr char kTestDataDirectory[] = "/mediapipe/tasks/testdata/vision/";
|
||||
constexpr char kHandLandmarkerBundleAsset[] = "hand_landmarker.task";
|
||||
constexpr char kThumbUpLandmarksFilename[] = "thumb_up_landmarks.pbtxt";
|
||||
constexpr char kPointingUpLandmarksFilename[] = "pointing_up_landmarks.pbtxt";
|
||||
constexpr char kPointingUpRotatedLandmarksFilename[] =
|
||||
"pointing_up_rotated_landmarks.pbtxt";
|
||||
constexpr char kThumbUpImage[] = "thumb_up.jpg";
|
||||
constexpr char kPointingUpImage[] = "pointing_up.jpg";
|
||||
constexpr char kPointingUpRotatedImage[] = "pointing_up_rotated.jpg";
|
||||
constexpr char kNoHandsImage[] = "cats_and_dogs.jpg";
|
||||
|
||||
constexpr float kLandmarksFractionDiff = 0.03; // percentage
|
||||
constexpr float kLandmarksAbsMargin = 0.03;
|
||||
constexpr float kHandednessMargin = 0.05;
|
||||
|
||||
LandmarksDetectionResult GetLandmarksDetectionResult(
|
||||
absl::string_view landmarks_file_name) {
|
||||
LandmarksDetectionResult result;
|
||||
MP_EXPECT_OK(GetTextProto(
|
||||
file::JoinPath("./", kTestDataDirectory, landmarks_file_name), &result,
|
||||
Defaults()));
|
||||
// Remove z position of landmarks, because they are not used in correctness
|
||||
// testing. For video or live stream mode, the z positions varies a lot during
|
||||
// tracking from frame to frame.
|
||||
for (int i = 0; i < result.landmarks().landmark().size(); i++) {
|
||||
auto& landmark = *result.mutable_landmarks()->mutable_landmark(i);
|
||||
landmark.clear_z();
|
||||
}
|
||||
return result;
|
||||
}
|
||||
|
||||
HandLandmarksDetectionResult GetExpectedHandLandmarksDetectionResult(
|
||||
const std::vector<absl::string_view>& landmarks_file_names) {
|
||||
HandLandmarksDetectionResult expected_results;
|
||||
for (const auto& file_name : landmarks_file_names) {
|
||||
const auto landmarks_detection_result =
|
||||
GetLandmarksDetectionResult(file_name);
|
||||
expected_results.hand_landmarks.push_back(
|
||||
landmarks_detection_result.landmarks());
|
||||
expected_results.handedness.push_back(
|
||||
landmarks_detection_result.classifications());
|
||||
}
|
||||
return expected_results;
|
||||
}
|
||||
|
||||
void ExpectHandLandmarksDetectionResultsCorrect(
|
||||
const HandLandmarksDetectionResult& actual_results,
|
||||
const HandLandmarksDetectionResult& expected_results) {
|
||||
const auto& actual_landmarks = actual_results.hand_landmarks;
|
||||
const auto& actual_handedness = actual_results.handedness;
|
||||
|
||||
const auto& expected_landmarks = expected_results.hand_landmarks;
|
||||
const auto& expected_handedness = expected_results.handedness;
|
||||
|
||||
ASSERT_EQ(actual_landmarks.size(), expected_landmarks.size());
|
||||
ASSERT_EQ(actual_handedness.size(), expected_handedness.size());
|
||||
|
||||
EXPECT_THAT(
|
||||
actual_handedness,
|
||||
Pointwise(Approximately(Partially(EqualsProto()), kHandednessMargin),
|
||||
expected_handedness));
|
||||
EXPECT_THAT(actual_landmarks,
|
||||
Pointwise(Approximately(Partially(EqualsProto()),
|
||||
/*margin=*/kLandmarksAbsMargin,
|
||||
/*fraction=*/kLandmarksFractionDiff),
|
||||
expected_landmarks));
|
||||
}
|
||||
|
||||
} // namespace
|
||||
|
||||
struct TestParams {
|
||||
// The name of this test, for convenience when displaying test results.
|
||||
std::string test_name;
|
||||
// The filename of test image.
|
||||
std::string test_image_name;
|
||||
// The filename of test model.
|
||||
std::string test_model_file;
|
||||
// The rotation to apply to the test image before processing, in degrees
|
||||
// clockwise.
|
||||
int rotation;
|
||||
// Expected results from the hand landmarker model output.
|
||||
HandLandmarksDetectionResult expected_results;
|
||||
};
|
||||
|
||||
class ImageModeTest : public testing::TestWithParam<TestParams> {};
|
||||
|
||||
TEST_F(ImageModeTest, FailsWithCallingWrongMethod) {
|
||||
MP_ASSERT_OK_AND_ASSIGN(
|
||||
Image image,
|
||||
DecodeImageFromFile(JoinPath("./", kTestDataDirectory, kThumbUpImage)));
|
||||
auto options = std::make_unique<HandLandmarkerOptions>();
|
||||
options->base_options.model_asset_path =
|
||||
JoinPath("./", kTestDataDirectory, kHandLandmarkerBundleAsset);
|
||||
options->running_mode = core::RunningMode::IMAGE;
|
||||
|
||||
MP_ASSERT_OK_AND_ASSIGN(std::unique_ptr<HandLandmarker> hand_landmarker,
|
||||
HandLandmarker::Create(std::move(options)));
|
||||
auto results = hand_landmarker->DetectForVideo(image, 0);
|
||||
EXPECT_EQ(results.status().code(), absl::StatusCode::kInvalidArgument);
|
||||
EXPECT_THAT(results.status().message(),
|
||||
HasSubstr("not initialized with the video mode"));
|
||||
EXPECT_THAT(results.status().GetPayload(kMediaPipeTasksPayload),
|
||||
Optional(absl::Cord(absl::StrCat(
|
||||
MediaPipeTasksStatus::kRunnerApiCalledInWrongModeError))));
|
||||
|
||||
results = hand_landmarker->DetectAsync(image, 0);
|
||||
EXPECT_EQ(results.status().code(), absl::StatusCode::kInvalidArgument);
|
||||
EXPECT_THAT(results.status().message(),
|
||||
HasSubstr("not initialized with the live stream mode"));
|
||||
EXPECT_THAT(results.status().GetPayload(kMediaPipeTasksPayload),
|
||||
Optional(absl::Cord(absl::StrCat(
|
||||
MediaPipeTasksStatus::kRunnerApiCalledInWrongModeError))));
|
||||
MP_ASSERT_OK(hand_landmarker->Close());
|
||||
}
|
||||
|
||||
TEST_F(ImageModeTest, FailsWithRegionOfInterest) {
|
||||
MP_ASSERT_OK_AND_ASSIGN(
|
||||
Image image,
|
||||
DecodeImageFromFile(JoinPath("./", kTestDataDirectory, kThumbUpImage)));
|
||||
auto options = std::make_unique<HandLandmarkerOptions>();
|
||||
options->base_options.model_asset_path =
|
||||
JoinPath("./", kTestDataDirectory, kHandLandmarkerBundleAsset);
|
||||
options->running_mode = core::RunningMode::IMAGE;
|
||||
MP_ASSERT_OK_AND_ASSIGN(std::unique_ptr<HandLandmarker> hand_landmarker,
|
||||
HandLandmarker::Create(std::move(options)));
|
||||
Rect roi{/*left=*/0.1, /*top=*/0, /*right=*/0.9, /*bottom=*/1};
|
||||
ImageProcessingOptions image_processing_options{roi, /*rotation_degrees=*/0};
|
||||
|
||||
auto results = hand_landmarker->Detect(image, image_processing_options);
|
||||
EXPECT_EQ(results.status().code(), absl::StatusCode::kInvalidArgument);
|
||||
EXPECT_THAT(results.status().message(),
|
||||
HasSubstr("This task doesn't support region-of-interest"));
|
||||
EXPECT_THAT(
|
||||
results.status().GetPayload(kMediaPipeTasksPayload),
|
||||
Optional(absl::Cord(absl::StrCat(
|
||||
MediaPipeTasksStatus::kImageProcessingInvalidArgumentError))));
|
||||
}
|
||||
|
||||
TEST_P(ImageModeTest, Succeeds) {
|
||||
MP_ASSERT_OK_AND_ASSIGN(
|
||||
Image image, DecodeImageFromFile(JoinPath("./", kTestDataDirectory,
|
||||
GetParam().test_image_name)));
|
||||
auto options = std::make_unique<HandLandmarkerOptions>();
|
||||
options->base_options.model_asset_path =
|
||||
JoinPath("./", kTestDataDirectory, GetParam().test_model_file);
|
||||
options->running_mode = core::RunningMode::IMAGE;
|
||||
|
||||
MP_ASSERT_OK_AND_ASSIGN(std::unique_ptr<HandLandmarker> hand_landmarker,
|
||||
HandLandmarker::Create(std::move(options)));
|
||||
HandLandmarksDetectionResult hand_landmarker_results;
|
||||
if (GetParam().rotation != 0) {
|
||||
ImageProcessingOptions image_processing_options;
|
||||
image_processing_options.rotation_degrees = GetParam().rotation;
|
||||
MP_ASSERT_OK_AND_ASSIGN(
|
||||
hand_landmarker_results,
|
||||
hand_landmarker->Detect(image, image_processing_options));
|
||||
} else {
|
||||
MP_ASSERT_OK_AND_ASSIGN(hand_landmarker_results,
|
||||
hand_landmarker->Detect(image));
|
||||
}
|
||||
ExpectHandLandmarksDetectionResultsCorrect(hand_landmarker_results,
|
||||
GetParam().expected_results);
|
||||
MP_ASSERT_OK(hand_landmarker->Close());
|
||||
}
|
||||
|
||||
INSTANTIATE_TEST_SUITE_P(
|
||||
HandGestureTest, ImageModeTest,
|
||||
Values(TestParams{
|
||||
/* test_name= */ "LandmarksThumbUp",
|
||||
/* test_image_name= */ kThumbUpImage,
|
||||
/* test_model_file= */ kHandLandmarkerBundleAsset,
|
||||
/* rotation= */ 0,
|
||||
/* expected_results = */
|
||||
GetExpectedHandLandmarksDetectionResult(
|
||||
{kThumbUpLandmarksFilename}),
|
||||
},
|
||||
TestParams{
|
||||
/* test_name= */ "LandmarksPointingUp",
|
||||
/* test_image_name= */ kPointingUpImage,
|
||||
/* test_model_file= */ kHandLandmarkerBundleAsset,
|
||||
/* rotation= */ 0,
|
||||
/* expected_results = */
|
||||
GetExpectedHandLandmarksDetectionResult(
|
||||
{kPointingUpLandmarksFilename}),
|
||||
},
|
||||
TestParams{
|
||||
/* test_name= */ "LandmarksPointingUpRotated",
|
||||
/* test_image_name= */ kPointingUpRotatedImage,
|
||||
/* test_model_file= */ kHandLandmarkerBundleAsset,
|
||||
/* rotation= */ -90,
|
||||
/* expected_results = */
|
||||
GetExpectedHandLandmarksDetectionResult(
|
||||
{kPointingUpRotatedLandmarksFilename}),
|
||||
},
|
||||
TestParams{
|
||||
/* test_name= */ "NoHands",
|
||||
/* test_image_name= */ kNoHandsImage,
|
||||
/* test_model_file= */ kHandLandmarkerBundleAsset,
|
||||
/* rotation= */ 0,
|
||||
/* expected_results = */
|
||||
{{}, {}, {}},
|
||||
}),
|
||||
[](const TestParamInfo<ImageModeTest::ParamType>& info) {
|
||||
return info.param.test_name;
|
||||
});
|
||||
|
||||
class VideoModeTest : public testing::TestWithParam<TestParams> {};
|
||||
|
||||
TEST_F(VideoModeTest, FailsWithCallingWrongMethod) {
|
||||
MP_ASSERT_OK_AND_ASSIGN(
|
||||
Image image,
|
||||
DecodeImageFromFile(JoinPath("./", kTestDataDirectory, kThumbUpImage)));
|
||||
auto options = std::make_unique<HandLandmarkerOptions>();
|
||||
options->base_options.model_asset_path =
|
||||
JoinPath("./", kTestDataDirectory, kHandLandmarkerBundleAsset);
|
||||
options->running_mode = core::RunningMode::VIDEO;
|
||||
|
||||
MP_ASSERT_OK_AND_ASSIGN(std::unique_ptr<HandLandmarker> hand_landmarker,
|
||||
HandLandmarker::Create(std::move(options)));
|
||||
auto results = hand_landmarker->Detect(image);
|
||||
EXPECT_EQ(results.status().code(), absl::StatusCode::kInvalidArgument);
|
||||
EXPECT_THAT(results.status().message(),
|
||||
HasSubstr("not initialized with the image mode"));
|
||||
EXPECT_THAT(results.status().GetPayload(kMediaPipeTasksPayload),
|
||||
Optional(absl::Cord(absl::StrCat(
|
||||
MediaPipeTasksStatus::kRunnerApiCalledInWrongModeError))));
|
||||
|
||||
results = hand_landmarker->DetectAsync(image, 0);
|
||||
EXPECT_EQ(results.status().code(), absl::StatusCode::kInvalidArgument);
|
||||
EXPECT_THAT(results.status().message(),
|
||||
HasSubstr("not initialized with the live stream mode"));
|
||||
EXPECT_THAT(results.status().GetPayload(kMediaPipeTasksPayload),
|
||||
Optional(absl::Cord(absl::StrCat(
|
||||
MediaPipeTasksStatus::kRunnerApiCalledInWrongModeError))));
|
||||
MP_ASSERT_OK(hand_landmarker->Close());
|
||||
}
|
||||
|
||||
TEST_P(VideoModeTest, Succeeds) {
|
||||
const int iterations = 100;
|
||||
MP_ASSERT_OK_AND_ASSIGN(
|
||||
Image image, DecodeImageFromFile(JoinPath("./", kTestDataDirectory,
|
||||
GetParam().test_image_name)));
|
||||
auto options = std::make_unique<HandLandmarkerOptions>();
|
||||
options->base_options.model_asset_path =
|
||||
JoinPath("./", kTestDataDirectory, GetParam().test_model_file);
|
||||
options->running_mode = core::RunningMode::VIDEO;
|
||||
|
||||
MP_ASSERT_OK_AND_ASSIGN(std::unique_ptr<HandLandmarker> hand_landmarker,
|
||||
HandLandmarker::Create(std::move(options)));
|
||||
const auto expected_results = GetParam().expected_results;
|
||||
for (int i = 0; i < iterations; ++i) {
|
||||
HandLandmarksDetectionResult hand_landmarker_results;
|
||||
if (GetParam().rotation != 0) {
|
||||
ImageProcessingOptions image_processing_options;
|
||||
image_processing_options.rotation_degrees = GetParam().rotation;
|
||||
MP_ASSERT_OK_AND_ASSIGN(
|
||||
hand_landmarker_results,
|
||||
hand_landmarker->DetectForVideo(image, i, image_processing_options));
|
||||
} else {
|
||||
MP_ASSERT_OK_AND_ASSIGN(hand_landmarker_results,
|
||||
hand_landmarker->DetectForVideo(image, i));
|
||||
}
|
||||
ExpectHandLandmarksDetectionResultsCorrect(hand_landmarker_results,
|
||||
expected_results);
|
||||
}
|
||||
MP_ASSERT_OK(hand_landmarker->Close());
|
||||
}
|
||||
|
||||
INSTANTIATE_TEST_SUITE_P(
|
||||
HandGestureTest, VideoModeTest,
|
||||
Values(TestParams{
|
||||
/* test_name= */ "LandmarksThumbUp",
|
||||
/* test_image_name= */ kThumbUpImage,
|
||||
/* test_model_file= */ kHandLandmarkerBundleAsset,
|
||||
/* rotation= */ 0,
|
||||
/* expected_results = */
|
||||
GetExpectedHandLandmarksDetectionResult(
|
||||
{kThumbUpLandmarksFilename}),
|
||||
},
|
||||
TestParams{
|
||||
/* test_name= */ "LandmarksPointingUp",
|
||||
/* test_image_name= */ kPointingUpImage,
|
||||
/* test_model_file= */ kHandLandmarkerBundleAsset,
|
||||
/* rotation= */ 0,
|
||||
/* expected_results = */
|
||||
GetExpectedHandLandmarksDetectionResult(
|
||||
{kPointingUpLandmarksFilename}),
|
||||
},
|
||||
TestParams{
|
||||
/* test_name= */ "LandmarksPointingUpRotated",
|
||||
/* test_image_name= */ kPointingUpRotatedImage,
|
||||
/* test_model_file= */ kHandLandmarkerBundleAsset,
|
||||
/* rotation= */ -90,
|
||||
/* expected_results = */
|
||||
GetExpectedHandLandmarksDetectionResult(
|
||||
{kPointingUpRotatedLandmarksFilename}),
|
||||
},
|
||||
TestParams{
|
||||
/* test_name= */ "NoHands",
|
||||
/* test_image_name= */ kNoHandsImage,
|
||||
/* test_model_file= */ kHandLandmarkerBundleAsset,
|
||||
/* rotation= */ 0,
|
||||
/* expected_results = */
|
||||
{{}, {}, {}},
|
||||
}),
|
||||
[](const TestParamInfo<ImageModeTest::ParamType>& info) {
|
||||
return info.param.test_name;
|
||||
});
|
||||
|
||||
class LiveStreamModeTest : public testing::TestWithParam<TestParams> {};
|
||||
|
||||
TEST_F(LiveStreamModeTest, FailsWithCallingWrongMethod) {
|
||||
MP_ASSERT_OK_AND_ASSIGN(
|
||||
Image image,
|
||||
DecodeImageFromFile(JoinPath("./", kTestDataDirectory, kThumbUpImage)));
|
||||
auto options = std::make_unique<HandLandmarkerOptions>();
|
||||
options->base_options.model_asset_path =
|
||||
JoinPath("./", kTestDataDirectory, kHandLandmarkerBundleAsset);
|
||||
options->running_mode = core::RunningMode::LIVE_STREAM;
|
||||
options->result_callback =
|
||||
[](absl::StatusOr<HandLandmarksDetectionResult> results,
|
||||
const Image& image, int64 timestamp_ms) {};
|
||||
|
||||
MP_ASSERT_OK_AND_ASSIGN(std::unique_ptr<HandLandmarker> hand_landmarker,
|
||||
HandLandmarker::Create(std::move(options)));
|
||||
auto results = hand_landmarker->Detect(image);
|
||||
EXPECT_EQ(results.status().code(), absl::StatusCode::kInvalidArgument);
|
||||
EXPECT_THAT(results.status().message(),
|
||||
HasSubstr("not initialized with the image mode"));
|
||||
EXPECT_THAT(results.status().GetPayload(kMediaPipeTasksPayload),
|
||||
Optional(absl::Cord(absl::StrCat(
|
||||
MediaPipeTasksStatus::kRunnerApiCalledInWrongModeError))));
|
||||
|
||||
results = hand_landmarker->DetectForVideo(image, 0);
|
||||
EXPECT_EQ(results.status().code(), absl::StatusCode::kInvalidArgument);
|
||||
EXPECT_THAT(results.status().message(),
|
||||
HasSubstr("not initialized with the video mode"));
|
||||
EXPECT_THAT(results.status().GetPayload(kMediaPipeTasksPayload),
|
||||
Optional(absl::Cord(absl::StrCat(
|
||||
MediaPipeTasksStatus::kRunnerApiCalledInWrongModeError))));
|
||||
MP_ASSERT_OK(hand_landmarker->Close());
|
||||
}
|
||||
|
||||
TEST_P(LiveStreamModeTest, Succeeds) {
|
||||
const int iterations = 100;
|
||||
MP_ASSERT_OK_AND_ASSIGN(
|
||||
Image image, DecodeImageFromFile(JoinPath("./", kTestDataDirectory,
|
||||
GetParam().test_image_name)));
|
||||
auto options = std::make_unique<HandLandmarkerOptions>();
|
||||
options->base_options.model_asset_path =
|
||||
JoinPath("./", kTestDataDirectory, GetParam().test_model_file);
|
||||
options->running_mode = core::RunningMode::LIVE_STREAM;
|
||||
std::vector<HandLandmarksDetectionResult> hand_landmarker_results;
|
||||
std::vector<std::pair<int, int>> image_sizes;
|
||||
std::vector<int64> timestamps;
|
||||
options->result_callback =
|
||||
[&hand_landmarker_results, &image_sizes, ×tamps](
|
||||
absl::StatusOr<HandLandmarksDetectionResult> results,
|
||||
const Image& image, int64 timestamp_ms) {
|
||||
MP_ASSERT_OK(results.status());
|
||||
hand_landmarker_results.push_back(std::move(results.value()));
|
||||
image_sizes.push_back({image.width(), image.height()});
|
||||
timestamps.push_back(timestamp_ms);
|
||||
};
|
||||
|
||||
MP_ASSERT_OK_AND_ASSIGN(std::unique_ptr<HandLandmarker> hand_landmarker,
|
||||
HandLandmarker::Create(std::move(options)));
|
||||
for (int i = 0; i < iterations; ++i) {
|
||||
HandLandmarksDetectionResult hand_landmarker_results;
|
||||
if (GetParam().rotation != 0) {
|
||||
ImageProcessingOptions image_processing_options;
|
||||
image_processing_options.rotation_degrees = GetParam().rotation;
|
||||
MP_ASSERT_OK(
|
||||
hand_landmarker->DetectAsync(image, i, image_processing_options));
|
||||
} else {
|
||||
MP_ASSERT_OK(hand_landmarker->DetectAsync(image, i));
|
||||
}
|
||||
}
|
||||
MP_ASSERT_OK(hand_landmarker->Close());
|
||||
// Due to the flow limiter, the total of outputs will be smaller than the
|
||||
// number of iterations.
|
||||
ASSERT_LE(hand_landmarker_results.size(), iterations);
|
||||
ASSERT_GT(hand_landmarker_results.size(), 0);
|
||||
|
||||
const auto expected_results = GetParam().expected_results;
|
||||
for (int i = 0; i < hand_landmarker_results.size(); ++i) {
|
||||
ExpectHandLandmarksDetectionResultsCorrect(hand_landmarker_results[i],
|
||||
expected_results);
|
||||
}
|
||||
for (const auto& image_size : image_sizes) {
|
||||
EXPECT_EQ(image_size.first, image.width());
|
||||
EXPECT_EQ(image_size.second, image.height());
|
||||
}
|
||||
int64 timestamp_ms = -1;
|
||||
for (const auto& timestamp : timestamps) {
|
||||
EXPECT_GT(timestamp, timestamp_ms);
|
||||
timestamp_ms = timestamp;
|
||||
}
|
||||
}
|
||||
|
||||
INSTANTIATE_TEST_SUITE_P(
|
||||
HandGestureTest, LiveStreamModeTest,
|
||||
Values(TestParams{
|
||||
/* test_name= */ "LandmarksThumbUp",
|
||||
/* test_image_name= */ kThumbUpImage,
|
||||
/* test_model_file= */ kHandLandmarkerBundleAsset,
|
||||
/* rotation= */ 0,
|
||||
/* expected_results = */
|
||||
GetExpectedHandLandmarksDetectionResult(
|
||||
{kThumbUpLandmarksFilename}),
|
||||
},
|
||||
TestParams{
|
||||
/* test_name= */ "LandmarksPointingUp",
|
||||
/* test_image_name= */ kPointingUpImage,
|
||||
/* test_model_file= */ kHandLandmarkerBundleAsset,
|
||||
/* rotation= */ 0,
|
||||
/* expected_results = */
|
||||
GetExpectedHandLandmarksDetectionResult(
|
||||
{kPointingUpLandmarksFilename}),
|
||||
},
|
||||
TestParams{
|
||||
/* test_name= */ "LandmarksPointingUpRotated",
|
||||
/* test_image_name= */ kPointingUpRotatedImage,
|
||||
/* test_model_file= */ kHandLandmarkerBundleAsset,
|
||||
/* rotation= */ -90,
|
||||
/* expected_results = */
|
||||
GetExpectedHandLandmarksDetectionResult(
|
||||
{kPointingUpRotatedLandmarksFilename}),
|
||||
},
|
||||
TestParams{
|
||||
/* test_name= */ "NoHands",
|
||||
/* test_image_name= */ kNoHandsImage,
|
||||
/* test_model_file= */ kHandLandmarkerBundleAsset,
|
||||
/* rotation= */ 0,
|
||||
/* expected_results = */
|
||||
{{}, {}, {}},
|
||||
}),
|
||||
[](const TestParamInfo<ImageModeTest::ParamType>& info) {
|
||||
return info.param.test_name;
|
||||
});
|
||||
|
||||
} // namespace hand_landmarker
|
||||
} // namespace vision
|
||||
} // namespace tasks
|
||||
} // namespace mediapipe
|
||||
Loading…
Reference in New Issue
Block a user