Internal change
PiperOrigin-RevId: 479724318
This commit is contained in:
MediaPipe Team
Copybara-Service
parent
65e1d722eb
commit
635dc0a24e
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@ -20,3 +20,12 @@ cc_library(
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name = "landmarks_detection",
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hdrs = ["landmarks_detection.h"],
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)
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cc_library(
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name = "gesture_recognition_result",
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hdrs = ["gesture_recognition_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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@ -0,0 +1,46 @@
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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_GESTURE_RECOGNITION_RESULT_H_
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#define MEDIAPIPE_TASKS_CC_COMPONENTS_CONTAINERS_GESTURE_RECOGNITION_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 gesture recognition result from GestureRecognizer, where each vector
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// element represents a single hand detected in the image.
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struct GestureRecognitionResult {
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// Recognized hand gestures with sorted order such that the winning label is
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// the first item in the list.
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std::vector<mediapipe::ClassificationList> gestures;
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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_GESTURE_RECOGNITION_RESULT_H_
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@ -47,6 +47,7 @@ cc_library(
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"//mediapipe/calculators/core:begin_loop_calculator",
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"//mediapipe/calculators/core:concatenate_vector_calculator",
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"//mediapipe/calculators/core:end_loop_calculator",
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"//mediapipe/calculators/core:get_vector_item_calculator",
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"//mediapipe/calculators/tensor:tensor_converter_calculator",
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"//mediapipe/calculators/tensor:tensors_to_classification_calculator",
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"//mediapipe/calculators/tensor:tensors_to_classification_calculator_cc_proto",
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@ -69,7 +70,8 @@ cc_library(
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"//mediapipe/tasks/cc/vision/gesture_recognizer/calculators:landmarks_to_matrix_calculator_cc_proto",
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"//mediapipe/tasks/cc/vision/gesture_recognizer/proto:hand_gesture_recognizer_graph_options_cc_proto",
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"//mediapipe/tasks/cc/vision/hand_landmarker:hand_landmarks_detector_graph",
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"//mediapipe/tasks/cc/vision/utils:image_tensor_specs",
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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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"//mediapipe/tasks/metadata:metadata_schema_cc",
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"@com_google_absl//absl/status",
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"@com_google_absl//absl/status:statusor",
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@ -90,7 +92,6 @@ cc_library(
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"//mediapipe/framework/formats:image",
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"//mediapipe/framework/formats:landmark_cc_proto",
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"//mediapipe/tasks/cc:common",
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"//mediapipe/tasks/cc/components/containers/proto:classifications_cc_proto",
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"//mediapipe/tasks/cc/components/processors/proto:classifier_options_cc_proto",
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"//mediapipe/tasks/cc/core:model_task_graph",
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"//mediapipe/tasks/cc/core:utils",
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@ -108,3 +109,42 @@ cc_library(
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],
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alwayslink = 1,
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)
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cc_library(
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name = "gesture_recognizer",
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srcs = ["gesture_recognizer.cc"],
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hdrs = ["gesture_recognizer.h"],
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deps = [
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":gesture_recognizer_graph",
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":hand_gesture_recognizer_graph",
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"//mediapipe/framework:packet",
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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/tasks/cc:common",
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"//mediapipe/tasks/cc/components:image_preprocessing",
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"//mediapipe/tasks/cc/components/containers:gesture_recognition_result",
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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:running_mode",
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"//mediapipe/tasks/cc/vision/core:vision_task_api_factory",
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"//mediapipe/tasks/cc/vision/gesture_recognizer/proto:gesture_recognizer_graph_options_cc_proto",
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"//mediapipe/tasks/cc/vision/gesture_recognizer/proto:hand_gesture_recognizer_graph_options_cc_proto",
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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/memory",
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"@com_google_absl//absl/status",
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"@com_google_absl//absl/status:statusor",
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"@org_tensorflow//tensorflow/lite/core/api:op_resolver",
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"@org_tensorflow//tensorflow/lite/kernels:builtin_ops",
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],
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)
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@ -0,0 +1,282 @@
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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/gesture_recognizer/gesture_recognizer.h"
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#include <memory>
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#include <type_traits>
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#include <vector>
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#include "absl/memory/memory.h"
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#include "absl/status/status.h"
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#include "absl/status/statusor.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/packet.h"
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#include "mediapipe/tasks/cc/common.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/vision_task_api_factory.h"
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#include "mediapipe/tasks/cc/vision/gesture_recognizer/proto/gesture_recognizer_graph_options.pb.h"
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#include "mediapipe/tasks/cc/vision/gesture_recognizer/proto/hand_gesture_recognizer_graph_options.pb.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 gesture_recognizer {
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namespace {
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using GestureRecognizerGraphOptionsProto = ::mediapipe::tasks::vision::
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gesture_recognizer::proto::GestureRecognizerGraphOptions;
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using ::mediapipe::tasks::components::containers::GestureRecognitionResult;
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constexpr char kHandGestureSubgraphTypeName[] =
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"mediapipe.tasks.vision.gesture_recognizer.GestureRecognizerGraph";
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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 kHandGesturesTag[] = "HAND_GESTURES";
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constexpr char kHandGesturesStreamName[] = "hand_gestures";
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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.GestureRecognizerGraph". If the task is running
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// in the live stream mode, a "FlowLimiterCalculator" will be added to limit the
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// number of frames in flight.
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CalculatorGraphConfig CreateGraphConfig(
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std::unique_ptr<GestureRecognizerGraphOptionsProto> 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(kHandGestureSubgraphTypeName);
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subgraph.GetOptions<GestureRecognizerGraphOptionsProto>().Swap(options.get());
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graph.In(kImageTag).SetName(kImageInStreamName);
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subgraph.Out(kHandGesturesTag).SetName(kHandGesturesStreamName) >>
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graph.Out(kHandGesturesTag);
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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(graph, subgraph, {kImageTag},
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kHandGesturesTag);
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}
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graph.In(kImageTag) >> subgraph.In(kImageTag);
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return graph.GetConfig();
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}
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// Converts the user-facing GestureRecognizerOptions struct to the internal
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// GestureRecognizerGraphOptions proto.
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std::unique_ptr<GestureRecognizerGraphOptionsProto>
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ConvertGestureRecognizerGraphOptionsProto(GestureRecognizerOptions* options) {
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auto options_proto = std::make_unique<GestureRecognizerGraphOptionsProto>();
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bool use_stream_mode = options->running_mode != core::RunningMode::IMAGE;
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// TODO remove these workarounds for base options of subgraphs.
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// Configure hand detector options.
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auto base_options_proto_for_hand_detector =
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std::make_unique<tasks::core::proto::BaseOptions>(
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tasks::core::ConvertBaseOptionsToProto(
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&(options->base_options_for_hand_detector)));
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base_options_proto_for_hand_detector->set_use_stream_mode(use_stream_mode);
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auto* hand_detector_graph_options =
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options_proto->mutable_hand_landmarker_graph_options()
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->mutable_hand_detector_graph_options();
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hand_detector_graph_options->mutable_base_options()->Swap(
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base_options_proto_for_hand_detector.get());
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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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auto base_options_proto_for_hand_landmarker =
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std::make_unique<tasks::core::proto::BaseOptions>(
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tasks::core::ConvertBaseOptionsToProto(
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&(options->base_options_for_hand_landmarker)));
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base_options_proto_for_hand_landmarker->set_use_stream_mode(use_stream_mode);
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auto* hand_landmarks_detector_graph_options =
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options_proto->mutable_hand_landmarker_graph_options()
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->mutable_hand_landmarks_detector_graph_options();
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hand_landmarks_detector_graph_options->mutable_base_options()->Swap(
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base_options_proto_for_hand_landmarker.get());
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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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auto* hand_landmarker_graph_options =
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options_proto->mutable_hand_landmarker_graph_options();
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hand_landmarker_graph_options->set_min_tracking_confidence(
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options->min_tracking_confidence);
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// Configure hand gesture recognizer options.
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auto base_options_proto_for_gesture_recognizer =
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std::make_unique<tasks::core::proto::BaseOptions>(
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tasks::core::ConvertBaseOptionsToProto(
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&(options->base_options_for_gesture_recognizer)));
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base_options_proto_for_gesture_recognizer->set_use_stream_mode(
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use_stream_mode);
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auto* hand_gesture_recognizer_graph_options =
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options_proto->mutable_hand_gesture_recognizer_graph_options();
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hand_gesture_recognizer_graph_options->mutable_base_options()->Swap(
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base_options_proto_for_gesture_recognizer.get());
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if (options->min_gesture_confidence >= 0) {
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hand_gesture_recognizer_graph_options->mutable_classifier_options()
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->set_score_threshold(options->min_gesture_confidence);
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}
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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<GestureRecognizer>> GestureRecognizer::Create(
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std::unique_ptr<GestureRecognizerOptions> options) {
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auto options_proto = ConvertGestureRecognizerGraphOptionsProto(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 gesture_packet =
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status_or_packets.value()[kHandGesturesStreamName];
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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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Packet image_packet = status_or_packets.value()[kImageOutStreamName];
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result_callback(
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{{gesture_packet.Get<std::vector<ClassificationList>>(),
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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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gesture_packet.Timestamp().Value() / kMicroSecondsPerMilliSecond);
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};
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}
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return core::VisionTaskApiFactory::Create<GestureRecognizer,
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GestureRecognizerGraphOptionsProto>(
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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<GestureRecognitionResult> GestureRecognizer::Recognize(
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mediapipe::Image image) {
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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(auto output_packets,
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ProcessImageData({{kImageInStreamName,
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MakePacket<Image>(std::move(image))}}));
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return {
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{/* gestures= */ {output_packets[kHandGesturesStreamName]
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.Get<std::vector<ClassificationList>>()},
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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::StatusOr<GestureRecognitionResult> GestureRecognizer::RecognizeForVideo(
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mediapipe::Image image, int64 timestamp_ms) {
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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);
|
||||
}
|
||||
ASSIGN_OR_RETURN(
|
||||
auto output_packets,
|
||||
ProcessVideoData(
|
||||
{{kImageInStreamName,
|
||||
MakePacket<Image>(std::move(image))
|
||||
.At(Timestamp(timestamp_ms * kMicroSecondsPerMilliSecond))}}));
|
||||
return {
|
||||
{/* gestures= */ {output_packets[kHandGesturesStreamName]
|
||||
.Get<std::vector<ClassificationList>>()},
|
||||
/* handedness= */
|
||||
{output_packets[kHandednessStreamName]
|
||||
.Get<std::vector<mediapipe::ClassificationList>>()},
|
||||
/* hand_landmarks= */
|
||||
{output_packets[kHandLandmarksStreamName]
|
||||
.Get<std::vector<mediapipe::NormalizedLandmarkList>>()},
|
||||
/* hand_world_landmarks */
|
||||
{output_packets[kHandWorldLandmarksStreamName]
|
||||
.Get<std::vector<mediapipe::LandmarkList>>()}},
|
||||
};
|
||||
}
|
||||
|
||||
absl::Status GestureRecognizer::RecognizeAsync(mediapipe::Image image,
|
||||
int64 timestamp_ms) {
|
||||
if (image.UsesGpu()) {
|
||||
return CreateStatusWithPayload(
|
||||
absl::StatusCode::kInvalidArgument,
|
||||
absl::StrCat("GPU input images are currently not supported."),
|
||||
MediaPipeTasksStatus::kRunnerUnexpectedInputError);
|
||||
}
|
||||
return SendLiveStreamData(
|
||||
{{kImageInStreamName,
|
||||
MakePacket<Image>(std::move(image))
|
||||
.At(Timestamp(timestamp_ms * kMicroSecondsPerMilliSecond))}});
|
||||
}
|
||||
|
||||
} // namespace gesture_recognizer
|
||||
} // namespace vision
|
||||
} // namespace tasks
|
||||
} // namespace mediapipe
|
||||
|
|
@ -0,0 +1,172 @@
|
|||
/* 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.
|
||||
==============================================================================*/
|
||||
|
||||
#ifndef MEDIAPIPE_TASKS_CC_VISION_GESTURE_RECOGNIZRER_GESTURE_RECOGNIZER_H_
|
||||
#define MEDIAPIPE_TASKS_CC_VISION_GESTURE_RECOGNIZRER_GESTURE_RECOGNIZER_H_
|
||||
|
||||
#include <memory>
|
||||
|
||||
#include "absl/status/statusor.h"
|
||||
#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/gesture_recognition_result.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/running_mode.h"
|
||||
|
||||
namespace mediapipe {
|
||||
namespace tasks {
|
||||
namespace vision {
|
||||
namespace gesture_recognizer {
|
||||
|
||||
struct GestureRecognizerOptions {
|
||||
// Base options for configuring Task library, such as specifying the TfLite
|
||||
// model file with metadata, accelerator options, op resolver, etc.
|
||||
tasks::core::BaseOptions base_options;
|
||||
|
||||
// TODO: remove these. Temporary solutions before bundle asset is
|
||||
// ready.
|
||||
tasks::core::BaseOptions base_options_for_hand_landmarker;
|
||||
tasks::core::BaseOptions base_options_for_hand_detector;
|
||||
tasks::core::BaseOptions base_options_for_gesture_recognizer;
|
||||
|
||||
// The running mode of the task. Default to the image mode.
|
||||
// GestureRecognizer has three running modes:
|
||||
// 1) The image mode for recognizing hand gestures on single image inputs.
|
||||
// 2) The video mode for recognizing hand gestures on the decoded frames of a
|
||||
// video.
|
||||
// 3) The live stream mode for recognizing hand gestures 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 GestureRecognizer.
|
||||
int num_hands = 1;
|
||||
|
||||
// The minimum confidence score for the hand detection to be considered
|
||||
// successfully.
|
||||
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
|
||||
// successfully.
|
||||
float min_tracking_confidence = 0.5;
|
||||
|
||||
// The minimum confidence score for the gestures to be considered
|
||||
// successfully. If < 0, the gesture confidence thresholds in the model
|
||||
// metadata are used.
|
||||
// TODO Note this option is subject to change, after scoring
|
||||
// merging calculator is implemented.
|
||||
float min_gesture_confidence = -1;
|
||||
|
||||
// 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::GestureRecognitionResult>,
|
||||
const Image&, int64)>
|
||||
result_callback = nullptr;
|
||||
};
|
||||
|
||||
// Performs hand gesture recognition on the given image.
|
||||
//
|
||||
// TODO add the link to DevSite.
|
||||
// This API expects expects a pre-trained hand gesture model asset bundle, or a
|
||||
// custom one created using Model Maker. See <link to the DevSite documentation
|
||||
// page>.
|
||||
//
|
||||
// Inputs:
|
||||
// Image
|
||||
// - The image that gesture recognition runs on.
|
||||
// Outputs:
|
||||
// GestureRecognitionResult
|
||||
// - The hand gesture recognition results.
|
||||
class GestureRecognizer : tasks::vision::core::BaseVisionTaskApi {
|
||||
public:
|
||||
using BaseVisionTaskApi::BaseVisionTaskApi;
|
||||
|
||||
// Creates a GestureRecognizer from a GestureRecognizerhOptions to process
|
||||
// image data or streaming data. Gesture recognizer can be created with one of
|
||||
// the following three running modes:
|
||||
// 1) Image mode for recognizing gestures on single image inputs.
|
||||
// Users provide mediapipe::Image to the `Recognize` method, and will
|
||||
// receive the recognized hand gesture results as the return value.
|
||||
// 2) Video mode for recognizing gestures on the decoded frames of a video.
|
||||
// 3) Live stream mode for recognizing gestures on the live stream of the
|
||||
// input data, such as from camera. Users call `RecognizeAsync` to push the
|
||||
// image data into the GestureRecognizer, the recognized results along with
|
||||
// the input timestamp and the image that gesture recognizer runs on will
|
||||
// be available in the result callback when the gesture recognizer finishes
|
||||
// the work.
|
||||
static absl::StatusOr<std::unique_ptr<GestureRecognizer>> Create(
|
||||
std::unique_ptr<GestureRecognizerOptions> options);
|
||||
|
||||
// Performs hand gesture recognition on the given image.
|
||||
// Only use this method when the GestureRecognizer is created with the image
|
||||
// running mode.
|
||||
//
|
||||
// image - mediapipe::Image
|
||||
// Image to perform hand gesture recognition on.
|
||||
//
|
||||
// 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::GestureRecognitionResult> Recognize(
|
||||
Image image);
|
||||
|
||||
// Performs gesture recognition on the provided video frame.
|
||||
// Only use this method when the GestureRecognizer is created with the video
|
||||
// running mode.
|
||||
//
|
||||
// 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::GestureRecognitionResult>
|
||||
RecognizeForVideo(Image image, int64 timestamp_ms);
|
||||
|
||||
// Sends live image data to perform gesture recognition, and the results will
|
||||
// be available via the "result_callback" provided in the
|
||||
// GestureRecognizerOptions. Only use this method when the GestureRecognizer
|
||||
// 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 gesture recognizer. The input timestamps must be monotonically
|
||||
// increasing.
|
||||
//
|
||||
// The "result_callback" provides
|
||||
// - A vector of GestureRecognitionResult, each is the recognized results
|
||||
// for a input frame.
|
||||
// - The const reference to the corresponding input image that the gesture
|
||||
// recognizer 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 RecognizeAsync(Image image, int64 timestamp_ms);
|
||||
|
||||
// Shuts down the GestureRecognizer when all works are done.
|
||||
absl::Status Close() { return runner_->Close(); }
|
||||
};
|
||||
|
||||
} // namespace gesture_recognizer
|
||||
} // namespace vision
|
||||
} // namespace tasks
|
||||
} // namespace mediapipe
|
||||
|
||||
#endif // MEDIAPIPE_TASKS_CC_VISION_GESTURE_RECOGNIZRER_GESTURE_RECOGNIZER_H_
|
||||
|
|
@ -25,7 +25,6 @@ limitations under the License.
|
|||
#include "mediapipe/framework/formats/image.h"
|
||||
#include "mediapipe/framework/formats/landmark.pb.h"
|
||||
#include "mediapipe/tasks/cc/common.h"
|
||||
#include "mediapipe/tasks/cc/components/containers/proto/classifications.pb.h"
|
||||
#include "mediapipe/tasks/cc/core/model_task_graph.h"
|
||||
#include "mediapipe/tasks/cc/core/utils.h"
|
||||
#include "mediapipe/tasks/cc/vision/gesture_recognizer/proto/gesture_recognizer_graph_options.pb.h"
|
||||
|
|
@ -46,7 +45,6 @@ using ::mediapipe::api2::Input;
|
|||
using ::mediapipe::api2::Output;
|
||||
using ::mediapipe::api2::builder::Graph;
|
||||
using ::mediapipe::api2::builder::Source;
|
||||
using ::mediapipe::tasks::components::containers::proto::ClassificationResult;
|
||||
using ::mediapipe::tasks::vision::gesture_recognizer::proto::
|
||||
GestureRecognizerGraphOptions;
|
||||
using ::mediapipe::tasks::vision::gesture_recognizer::proto::
|
||||
|
|
@ -63,10 +61,10 @@ constexpr char kHandGesturesTag[] = "HAND_GESTURES";
|
|||
constexpr char kHandTrackingIdsTag[] = "HAND_TRACKING_IDS";
|
||||
|
||||
struct GestureRecognizerOutputs {
|
||||
Source<std::vector<ClassificationResult>> gesture;
|
||||
Source<std::vector<mediapipe::ClassificationList>> handedness;
|
||||
Source<std::vector<mediapipe::NormalizedLandmarkList>> hand_landmarks;
|
||||
Source<std::vector<mediapipe::LandmarkList>> hand_world_landmarks;
|
||||
Source<std::vector<ClassificationList>> gesture;
|
||||
Source<std::vector<ClassificationList>> handedness;
|
||||
Source<std::vector<NormalizedLandmarkList>> hand_landmarks;
|
||||
Source<std::vector<LandmarkList>> hand_world_landmarks;
|
||||
Source<Image> image;
|
||||
};
|
||||
|
||||
|
|
@ -80,7 +78,7 @@ struct GestureRecognizerOutputs {
|
|||
// Image to perform hand gesture recognition on.
|
||||
//
|
||||
// Outputs:
|
||||
// HAND_GESTURES - std::vector<ClassificationResult>
|
||||
// HAND_GESTURES - std::vector<ClassificationList>
|
||||
// Recognized hand gestures with sorted order such that the winning label is
|
||||
// the first item in the list.
|
||||
// LANDMARKS: - std::vector<NormalizedLandmarkList>
|
||||
|
|
@ -136,15 +134,13 @@ class GestureRecognizerGraph : public core::ModelTaskGraph {
|
|||
*sc->MutableOptions<GestureRecognizerGraphOptions>(),
|
||||
graph[Input<Image>(kImageTag)], graph));
|
||||
hand_gesture_recognition_output.gesture >>
|
||||
graph[Output<std::vector<ClassificationResult>>(kHandGesturesTag)];
|
||||
graph[Output<std::vector<ClassificationList>>(kHandGesturesTag)];
|
||||
hand_gesture_recognition_output.handedness >>
|
||||
graph[Output<std::vector<mediapipe::ClassificationList>>(
|
||||
kHandednessTag)];
|
||||
graph[Output<std::vector<ClassificationList>>(kHandednessTag)];
|
||||
hand_gesture_recognition_output.hand_landmarks >>
|
||||
graph[Output<std::vector<mediapipe::NormalizedLandmarkList>>(
|
||||
kLandmarksTag)];
|
||||
graph[Output<std::vector<NormalizedLandmarkList>>(kLandmarksTag)];
|
||||
hand_gesture_recognition_output.hand_world_landmarks >>
|
||||
graph[Output<std::vector<mediapipe::LandmarkList>>(kWorldLandmarksTag)];
|
||||
graph[Output<std::vector<LandmarkList>>(kWorldLandmarksTag)];
|
||||
hand_gesture_recognition_output.image >> graph[Output<Image>(kImageTag)];
|
||||
return graph.GetConfig();
|
||||
}
|
||||
|
|
@ -193,7 +189,7 @@ class GestureRecognizerGraph : public core::ModelTaskGraph {
|
|||
image_size >> hand_gesture_subgraph.In(kImageSizeTag);
|
||||
hand_landmarks_id >> hand_gesture_subgraph.In(kHandTrackingIdsTag);
|
||||
auto hand_gestures =
|
||||
hand_gesture_subgraph[Output<std::vector<ClassificationResult>>(
|
||||
hand_gesture_subgraph[Output<std::vector<ClassificationList>>(
|
||||
kHandGesturesTag)];
|
||||
|
||||
return {{.gesture = hand_gestures,
|
||||
|
|
|
|||
4
mediapipe/tasks/testdata/vision/BUILD
vendored
4
mediapipe/tasks/testdata/vision/BUILD
vendored
|
|
@ -47,6 +47,7 @@ mediapipe_files(srcs = [
|
|||
"mozart_square.jpg",
|
||||
"multi_objects.jpg",
|
||||
"palm_detection_full.tflite",
|
||||
"pointing_up.jpg",
|
||||
"right_hands.jpg",
|
||||
"segmentation_golden_rotation0.png",
|
||||
"segmentation_input_rotation0.jpg",
|
||||
|
|
@ -54,6 +55,7 @@ mediapipe_files(srcs = [
|
|||
"selfie_segm_128_128_3_expected_mask.jpg",
|
||||
"selfie_segm_144_256_3.tflite",
|
||||
"selfie_segm_144_256_3_expected_mask.jpg",
|
||||
"thumb_up.jpg",
|
||||
])
|
||||
|
||||
exports_files(
|
||||
|
|
@ -79,11 +81,13 @@ filegroup(
|
|||
"left_hands.jpg",
|
||||
"mozart_square.jpg",
|
||||
"multi_objects.jpg",
|
||||
"pointing_up.jpg",
|
||||
"right_hands.jpg",
|
||||
"segmentation_golden_rotation0.png",
|
||||
"segmentation_input_rotation0.jpg",
|
||||
"selfie_segm_128_128_3_expected_mask.jpg",
|
||||
"selfie_segm_144_256_3_expected_mask.jpg",
|
||||
"thumb_up.jpg",
|
||||
],
|
||||
visibility = [
|
||||
"//mediapipe/python:__subpackages__",
|
||||
|
|
|
|||
|
|
@ -8,216 +8,216 @@ classifications {
|
|||
|
||||
landmarks {
|
||||
landmark {
|
||||
x: 0.4749803
|
||||
y: 0.76872
|
||||
z: 9.286178e-08
|
||||
x: 0.47923622
|
||||
y: 0.7426044
|
||||
z: 2.3221878e-07
|
||||
}
|
||||
landmark {
|
||||
x: 0.5466898
|
||||
y: 0.6706463
|
||||
z: -0.03454024
|
||||
x: 0.5403745
|
||||
y: 0.66178805
|
||||
z: -0.044572093
|
||||
}
|
||||
landmark {
|
||||
x: 0.5890165
|
||||
y: 0.5604909
|
||||
z: -0.055142127
|
||||
x: 0.5774534
|
||||
y: 0.5608346
|
||||
z: -0.07581605
|
||||
}
|
||||
landmark {
|
||||
x: 0.52780133
|
||||
y: 0.49855334
|
||||
z: -0.07846409
|
||||
x: 0.52648556
|
||||
y: 0.50247055
|
||||
z: -0.105467044
|
||||
}
|
||||
landmark {
|
||||
x: 0.44487286
|
||||
y: 0.49801928
|
||||
z: -0.10188004
|
||||
x: 0.44289914
|
||||
y: 0.49489295
|
||||
z: -0.13422011
|
||||
}
|
||||
landmark {
|
||||
x: 0.47572923
|
||||
y: 0.44477755
|
||||
z: -0.028345175
|
||||
x: 0.4728853
|
||||
y: 0.43925008
|
||||
z: -0.058122505
|
||||
}
|
||||
landmark {
|
||||
x: 0.48013464
|
||||
y: 0.32467923
|
||||
z: -0.06513901
|
||||
x: 0.4803168
|
||||
y: 0.32889345
|
||||
z: -0.101187326
|
||||
}
|
||||
landmark {
|
||||
x: 0.48351905
|
||||
y: 0.25804192
|
||||
z: -0.086756624
|
||||
x: 0.48436823
|
||||
y: 0.25876504
|
||||
z: -0.12840955
|
||||
}
|
||||
landmark {
|
||||
x: 0.47760454
|
||||
y: 0.19289327
|
||||
z: -0.10468461
|
||||
x: 0.47388697
|
||||
y: 0.19592366
|
||||
z: -0.15085006
|
||||
}
|
||||
landmark {
|
||||
x: 0.3993108
|
||||
y: 0.47566867
|
||||
z: -0.040357687
|
||||
x: 0.39129356
|
||||
y: 0.47211456
|
||||
z: -0.06835801
|
||||
}
|
||||
landmark {
|
||||
x: 0.42361537
|
||||
y: 0.42491958
|
||||
z: -0.103545874
|
||||
x: 0.41798547
|
||||
y: 0.42218646
|
||||
z: -0.12954563
|
||||
}
|
||||
landmark {
|
||||
x: 0.46059948
|
||||
y: 0.51723665
|
||||
z: -0.1214961
|
||||
x: 0.45758423
|
||||
y: 0.5232461
|
||||
z: -0.14131334
|
||||
}
|
||||
landmark {
|
||||
x: 0.4580545
|
||||
y: 0.55640894
|
||||
z: -0.12272568
|
||||
x: 0.45100626
|
||||
y: 0.5554065
|
||||
z: -0.13883406
|
||||
}
|
||||
landmark {
|
||||
x: 0.34109607
|
||||
y: 0.5184511
|
||||
z: -0.056422118
|
||||
x: 0.33133638
|
||||
y: 0.51777464
|
||||
z: -0.08227023
|
||||
}
|
||||
landmark {
|
||||
x: 0.36177525
|
||||
y: 0.48427337
|
||||
z: -0.12584248
|
||||
x: 0.35698116
|
||||
y: 0.48688585
|
||||
z: -0.14713185
|
||||
}
|
||||
landmark {
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landmark {
|
||||
x: -0.01082343
|
||||
y: 0.03213215
|
||||
z: -0.00069864903
|
||||
x: 0.0011399705
|
||||
y: 0.043651186
|
||||
z: 0.0068390737
|
||||
}
|
||||
landmark {
|
||||
x: -0.0199164
|
||||
y: 0.028296603
|
||||
z: -0.01447433
|
||||
x: -0.010388309
|
||||
y: 0.03904784
|
||||
z: -0.015677728
|
||||
}
|
||||
landmark {
|
||||
x: -0.00960456
|
||||
y: 0.026734762
|
||||
z: -0.019243335
|
||||
x: 0.006957108
|
||||
y: 0.03613425
|
||||
z: -0.028704688
|
||||
}
|
||||
landmark {
|
||||
x: 0.0040425956
|
||||
y: 0.025051914
|
||||
z: -0.014775545
|
||||
x: 0.012793289
|
||||
y: 0.03930679
|
||||
z: -0.012465539
|
||||
}
|
||||
}
|
||||
|
|
|
|||
8
third_party/external_files.bzl
vendored
8
third_party/external_files.bzl
vendored
|
|
@ -432,8 +432,8 @@ def external_files():
|
|||
|
||||
http_file(
|
||||
name = "com_google_mediapipe_pointing_up_landmarks_pbtxt",
|
||||
sha256 = "1255b6ba17b4ef7a9b3ce92c0a139e74fbcec272dc251b049b2f06732f9fed83",
|
||||
urls = ["https://storage.googleapis.com/mediapipe-assets/pointing_up_landmarks.pbtxt?generation=1662650664573638"],
|
||||
sha256 = "a3cd7f088a9e997dbb8f00d91dbf3faaacbdb262c8f2fde3c07a9d0656488065",
|
||||
urls = ["https://storage.googleapis.com/mediapipe-assets/pointing_up_landmarks.pbtxt?generation=1665174976408451"],
|
||||
)
|
||||
|
||||
http_file(
|
||||
|
|
@ -588,8 +588,8 @@ def external_files():
|
|||
|
||||
http_file(
|
||||
name = "com_google_mediapipe_thumb_up_landmarks_pbtxt",
|
||||
sha256 = "bf1913df6ac7cc14b492c10411c827832839985c057b112789e04ce7c1fdd0fa",
|
||||
urls = ["https://storage.googleapis.com/mediapipe-assets/thumb_up_landmarks.pbtxt?generation=1662650669387278"],
|
||||
sha256 = "b129ae0536be4e25d6cdee74aabe9dedf1bcfe87430a40b68be4079db3a4d926",
|
||||
urls = ["https://storage.googleapis.com/mediapipe-assets/thumb_up_landmarks.pbtxt?generation=1665174979747784"],
|
||||
)
|
||||
|
||||
http_file(
|
||||
|
|
|
|||
Loading…
Reference in New Issue
Block a user