internal change

PiperOrigin-RevId: 493742399

mediapipe/tasks/cc/components/containers/BUILD

@@ -18,6 +18,7 @@ licenses(["notice"])
 
 cc_library(
     name = "rect",
+    srcs = ["rect.cc"],
     hdrs = ["rect.h"],
 )
 
@@ -41,6 +42,18 @@ cc_library(
     ],
 )
 
+cc_library(
+    name = "detection_result",
+    srcs = ["detection_result.cc"],
+    hdrs = ["detection_result.h"],
+    deps = [
+        ":category",
+        ":rect",
+        "//mediapipe/framework/formats:detection_cc_proto",
+        "//mediapipe/framework/formats:location_data_cc_proto",
+    ],
+)
+
 cc_library(
     name = "embedding_result",
     srcs = ["embedding_result.cc"],

mediapipe/tasks/cc/components/containers/detection_result.cc

@@ -0,0 +1,73 @@
+/* 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/components/containers/detection_result.h"
+
+#include <strings.h>
+
+#include <optional>
+#include <string>
+#include <vector>
+
+#include "mediapipe/framework/formats/detection.pb.h"
+#include "mediapipe/framework/formats/location_data.pb.h"
+#include "mediapipe/tasks/cc/components/containers/category.h"
+#include "mediapipe/tasks/cc/components/containers/rect.h"
+
+namespace mediapipe::tasks::components::containers {
+
+constexpr int kDefaultCategoryIndex = -1;
+
+Detection ConvertToDetectionResult(
+    const mediapipe::Detection& detection_proto) {
+  Detection detection;
+  for (int idx = 0; idx < detection_proto.score_size(); ++idx) {
+    detection.categories.push_back(
+        {/* index= */ detection_proto.label_id_size() > idx
+             ? detection_proto.label_id(idx)
+             : kDefaultCategoryIndex,
+         /* score= */ detection_proto.score(idx),
+         /* category_name */ detection_proto.label_size() > idx
+             ? detection_proto.label(idx)
+             : "",
+         /* display_name */ detection_proto.display_name_size() > idx
+             ? detection_proto.display_name(idx)
+             : ""});
+  }
+  Rect bounding_box;
+  if (detection_proto.location_data().has_bounding_box()) {
+    mediapipe::LocationData::BoundingBox bounding_box_proto =
+        detection_proto.location_data().bounding_box();
+    bounding_box.left = bounding_box_proto.xmin();
+    bounding_box.top = bounding_box_proto.ymin();
+    bounding_box.right = bounding_box_proto.xmin() + bounding_box_proto.width();
+    bounding_box.bottom =
+        bounding_box_proto.ymin() + bounding_box_proto.height();
+  }
+  detection.bounding_box = bounding_box;
+  return detection;
+}
+
+DetectionResult ConvertToDetectionResult(
+    std::vector<mediapipe::Detection> detections_proto) {
+  DetectionResult detection_result;
+  detection_result.detections.reserve(detections_proto.size());
+  for (const auto& detection_proto : detections_proto) {
+    detection_result.detections.push_back(
+        ConvertToDetectionResult(detection_proto));
+  }
+  return detection_result;
+}
+}  // namespace mediapipe::tasks::components::containers

mediapipe/tasks/cc/components/containers/detection_result.h

@@ -0,0 +1,52 @@
+/* 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_COMPONENTS_CONTAINERS_DETECTION_RESULT_H_
+#define MEDIAPIPE_TASKS_CC_COMPONENTS_CONTAINERS_DETECTION_RESULT_H_
+
+#include <optional>
+#include <string>
+#include <vector>
+
+#include "mediapipe/framework/formats/detection.pb.h"
+#include "mediapipe/tasks/cc/components/containers/category.h"
+#include "mediapipe/tasks/cc/components/containers/rect.h"
+
+namespace mediapipe::tasks::components::containers {
+
+// Detection for a single bounding box.
+struct Detection {
+  // A vector of detected categories.
+  std::vector<Category> categories;
+  // The bounding box location.
+  Rect bounding_box;
+};
+
+// Detection results of a model.
+struct DetectionResult {
+  // A vector of Detections.
+  std::vector<Detection> detections;
+};
+
+// Utility function to convert from Detection proto to Detection struct.
+Detection ConvertToDetection(const mediapipe::Detection& detection_proto);
+
+// Utility function to convert from list of Detection proto to DetectionResult
+// struct.
+DetectionResult ConvertToDetectionResult(
+    std::vector<mediapipe::Detection> detections_proto);
+
+}  // namespace mediapipe::tasks::components::containers
+#endif  // MEDIAPIPE_TASKS_CC_COMPONENTS_CONTAINERS_DETECTION_RESULT_H_

mediapipe/tasks/cc/components/containers/rect.cc

@@ -0,0 +1,34 @@
+/* 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/components/containers/rect.h"
+
+namespace mediapipe::tasks::components::containers {
+
+RectF ToRectF(const Rect& rect, int image_height, int image_width) {
+  return RectF{static_cast<float>(rect.left) / image_width,
+               static_cast<float>(rect.top) / image_height,
+               static_cast<float>(rect.right) / image_width,
+               static_cast<float>(rect.bottom) / image_height};
+}
+
+Rect ToRect(const RectF& rect, int image_height, int image_width) {
+  return Rect{static_cast<int>(rect.left * image_width),
+              static_cast<int>(rect.top * image_height),
+              static_cast<int>(rect.right * image_width),
+              static_cast<int>(rect.bottom * image_height)};
+}
+
+}  // namespace mediapipe::tasks::components::containers

mediapipe/tasks/cc/components/containers/rect.h

@@ -16,20 +16,47 @@ limitations under the License.
 #ifndef MEDIAPIPE_TASKS_CC_COMPONENTS_CONTAINERS_RECT_H_
 #define MEDIAPIPE_TASKS_CC_COMPONENTS_CONTAINERS_RECT_H_
 
+#include <cstdlib>
+
 namespace mediapipe::tasks::components::containers {
 
+constexpr float kRectFTolerance = 1e-4;
+
 // Defines a rectangle, used e.g. as part of detection results or as input
 // region-of-interest.
 //
+struct Rect {
+  int left;
+  int top;
+  int right;
+  int bottom;
+};
+
+inline bool operator==(const Rect& lhs, const Rect& rhs) {
+  return lhs.left == rhs.left && lhs.top == rhs.top && lhs.right == rhs.right &&
+         lhs.bottom == rhs.bottom;
+}
+
 // The coordinates are normalized wrt the image dimensions, i.e. generally in
 // [0,1] but they may exceed these bounds if describing a region overlapping the
 // image. The origin is on the top-left corner of the image.
-struct Rect {
+struct RectF {
   float left;
   float top;
   float right;
   float bottom;
 };
 
+inline bool operator==(const RectF& lhs, const RectF& rhs) {
+  return abs(lhs.left - rhs.left) < kRectFTolerance &&
+         abs(lhs.top - rhs.top) < kRectFTolerance &&
+         abs(lhs.right - rhs.right) < kRectFTolerance &&
+         abs(lhs.bottom - rhs.bottom) < kRectFTolerance;
+}
+
+RectF ToRectF(const Rect& rect, int image_height, int image_width);
+
+Rect ToRect(const RectF& rect, int image_height, int image_width);
+
 }  // namespace mediapipe::tasks::components::containers
 #endif  // MEDIAPIPE_TASKS_CC_COMPONENTS_CONTAINERS_RECT_H_

mediapipe/tasks/cc/vision/core/base_vision_task_api.h

@@ -129,13 +129,13 @@ class BaseVisionTaskApi : public tasks::core::BaseTaskApi {
       if (roi.left >= roi.right || roi.top >= roi.bottom) {
         return CreateStatusWithPayload(
             absl::StatusCode::kInvalidArgument,
-            "Expected Rect with left < right and top < bottom.",
+            "Expected RectF with left < right and top < bottom.",
             MediaPipeTasksStatus::kImageProcessingInvalidArgumentError);
       }
       if (roi.left < 0 || roi.top < 0 || roi.right > 1 || roi.bottom > 1) {
         return CreateStatusWithPayload(
             absl::StatusCode::kInvalidArgument,
-            "Expected Rect values to be in [0,1].",
+            "Expected RectF values to be in [0,1].",
             MediaPipeTasksStatus::kImageProcessingInvalidArgumentError);
       }
       normalized_rect.set_x_center((roi.left + roi.right) / 2.0);

mediapipe/tasks/cc/vision/core/image_processing_options.h

@@ -35,7 +35,8 @@ struct ImageProcessingOptions {
   // the full image is used.
   //
   // Coordinates must be in [0,1] with 'left' < 'right' and 'top' < bottom.
-  std::optional<components::containers::Rect> region_of_interest = std::nullopt;
+  std::optional<components::containers::RectF> region_of_interest =
+      std::nullopt;
 
   // The rotation to apply to the image (or cropped region-of-interest), in
   // degrees clockwise.

mediapipe/tasks/cc/vision/hand_landmarker/calculators/hand_landmarks_deduplication_calculator.cc

@@ -44,7 +44,7 @@ namespace {
 using ::mediapipe::api2::Input;
 using ::mediapipe::api2::Output;
 using ::mediapipe::api2::builder::Source;
-using ::mediapipe::tasks::components::containers::Rect;
+using ::mediapipe::tasks::components::containers::RectF;
 using ::mediapipe::tasks::vision::utils::CalculateIOU;
 using ::mediapipe::tasks::vision::utils::DuplicatesFinder;
 
@@ -126,7 +126,7 @@ absl::StatusOr<float> HandBaselineDistance(
   return distance;
 }
 
-Rect CalculateBound(const NormalizedLandmarkList& list) {
+RectF CalculateBound(const NormalizedLandmarkList& list) {
   constexpr float kMinInitialValue = std::numeric_limits<float>::max();
   constexpr float kMaxInitialValue = std::numeric_limits<float>::lowest();
 
@@ -144,10 +144,10 @@ Rect CalculateBound(const NormalizedLandmarkList& list) {
   }
 
   // Populate normalized non rotated face bounding box
-  return Rect{/*left=*/bounding_box_left,
+  return RectF{/*left=*/bounding_box_left,
-              /*top=*/bounding_box_top,
+               /*top=*/bounding_box_top,
-              /*right=*/bounding_box_right,
+               /*right=*/bounding_box_right,
-              /*bottom=*/bounding_box_bottom};
+               /*bottom=*/bounding_box_bottom};
 }
 
 // Uses IoU and distance of some corresponding hand landmarks to detect
@@ -172,7 +172,7 @@ class HandDuplicatesFinder : public DuplicatesFinder {
     const int num = multi_landmarks.size();
     std::vector<float> baseline_distances;
     baseline_distances.reserve(num);
-    std::vector<Rect> bounds;
+    std::vector<RectF> bounds;
     bounds.reserve(num);
     for (const NormalizedLandmarkList& list : multi_landmarks) {
       ASSIGN_OR_RETURN(const float baseline_distance,

mediapipe/tasks/cc/vision/hand_landmarker/hand_landmarker_test.cc

@@ -50,7 +50,7 @@ namespace {
 
 using ::file::Defaults;
 using ::mediapipe::file::JoinPath;
-using ::mediapipe::tasks::components::containers::Rect;
+using ::mediapipe::tasks::components::containers::RectF;
 using ::mediapipe::tasks::containers::proto::LandmarksDetectionResult;
 using ::mediapipe::tasks::vision::core::ImageProcessingOptions;
 using ::testing::EqualsProto;
@@ -188,7 +188,7 @@ TEST_F(ImageModeTest, FailsWithRegionOfInterest) {
   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};
+  RectF 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);

mediapipe/tasks/cc/vision/image_classifier/image_classifier_test.cc

@@ -52,7 +52,7 @@ namespace {
 using ::mediapipe::file::JoinPath;
 using ::mediapipe::tasks::components::containers::Category;
 using ::mediapipe::tasks::components::containers::Classifications;
-using ::mediapipe::tasks::components::containers::Rect;
+using ::mediapipe::tasks::components::containers::RectF;
 using ::mediapipe::tasks::vision::core::ImageProcessingOptions;
 using ::testing::HasSubstr;
 using ::testing::Optional;
@@ -472,7 +472,7 @@ TEST_F(ImageModeTest, SucceedsWithRegionOfInterest) {
   MP_ASSERT_OK_AND_ASSIGN(std::unique_ptr<ImageClassifier> image_classifier,
                           ImageClassifier::Create(std::move(options)));
   // Region-of-interest around the soccer ball.
-  Rect roi{/*left=*/0.45, /*top=*/0.3075, /*right=*/0.614, /*bottom=*/0.7345};
+  RectF roi{/*left=*/0.45, /*top=*/0.3075, /*right=*/0.614, /*bottom=*/0.7345};
   ImageProcessingOptions image_processing_options{roi, /*rotation_degrees=*/0};
 
   MP_ASSERT_OK_AND_ASSIGN(auto results, image_classifier->Classify(
@@ -526,7 +526,8 @@ TEST_F(ImageModeTest, SucceedsWithRegionOfInterestAndRotation) {
   MP_ASSERT_OK_AND_ASSIGN(std::unique_ptr<ImageClassifier> image_classifier,
                           ImageClassifier::Create(std::move(options)));
   // Region-of-interest around the chair, with 90° anti-clockwise rotation.
-  Rect roi{/*left=*/0.006, /*top=*/0.1763, /*right=*/0.5702, /*bottom=*/0.3049};
+  RectF roi{/*left=*/0.006, /*top=*/0.1763, /*right=*/0.5702,
+            /*bottom=*/0.3049};
   ImageProcessingOptions image_processing_options{roi,
                                                   /*rotation_degrees=*/-90};
 
@@ -554,13 +555,13 @@ TEST_F(ImageModeTest, FailsWithInvalidImageProcessingOptions) {
                           ImageClassifier::Create(std::move(options)));
 
   // Invalid: left > right.
-  Rect roi{/*left=*/0.9, /*top=*/0, /*right=*/0.1, /*bottom=*/1};
+  RectF roi{/*left=*/0.9, /*top=*/0, /*right=*/0.1, /*bottom=*/1};
   ImageProcessingOptions image_processing_options{roi,
                                                   /*rotation_degrees=*/0};
   auto results = image_classifier->Classify(image, image_processing_options);
   EXPECT_EQ(results.status().code(), absl::StatusCode::kInvalidArgument);
   EXPECT_THAT(results.status().message(),
-              HasSubstr("Expected Rect with left < right and top < bottom"));
+              HasSubstr("Expected RectF with left < right and top < bottom"));
   EXPECT_THAT(
       results.status().GetPayload(kMediaPipeTasksPayload),
       Optional(absl::Cord(absl::StrCat(
@@ -573,7 +574,7 @@ TEST_F(ImageModeTest, FailsWithInvalidImageProcessingOptions) {
   results = image_classifier->Classify(image, image_processing_options);
   EXPECT_EQ(results.status().code(), absl::StatusCode::kInvalidArgument);
   EXPECT_THAT(results.status().message(),
-              HasSubstr("Expected Rect with left < right and top < bottom"));
+              HasSubstr("Expected RectF with left < right and top < bottom"));
   EXPECT_THAT(
       results.status().GetPayload(kMediaPipeTasksPayload),
       Optional(absl::Cord(absl::StrCat(
@@ -586,7 +587,7 @@ TEST_F(ImageModeTest, FailsWithInvalidImageProcessingOptions) {
   results = image_classifier->Classify(image, image_processing_options);
   EXPECT_EQ(results.status().code(), absl::StatusCode::kInvalidArgument);
   EXPECT_THAT(results.status().message(),
-              HasSubstr("Expected Rect values to be in [0,1]"));
+              HasSubstr("Expected RectF values to be in [0,1]"));
   EXPECT_THAT(
       results.status().GetPayload(kMediaPipeTasksPayload),
       Optional(absl::Cord(absl::StrCat(
@@ -695,7 +696,7 @@ TEST_F(VideoModeTest, SucceedsWithRegionOfInterest) {
                           ImageClassifier::Create(std::move(options)));
   // Crop around the soccer ball.
   // Region-of-interest around the soccer ball.
-  Rect roi{/*left=*/0.45, /*top=*/0.3075, /*right=*/0.614, /*bottom=*/0.7345};
+  RectF roi{/*left=*/0.45, /*top=*/0.3075, /*right=*/0.614, /*bottom=*/0.7345};
   ImageProcessingOptions image_processing_options{roi, /*rotation_degrees=*/0};
 
   for (int i = 0; i < iterations; ++i) {
@@ -837,7 +838,7 @@ TEST_F(LiveStreamModeTest, SucceedsWithRegionOfInterest) {
   MP_ASSERT_OK_AND_ASSIGN(std::unique_ptr<ImageClassifier> image_classifier,
                           ImageClassifier::Create(std::move(options)));
   // Crop around the soccer ball.
-  Rect roi{/*left=*/0.45, /*top=*/0.3075, /*right=*/0.614, /*bottom=*/0.7345};
+  RectF roi{/*left=*/0.45, /*top=*/0.3075, /*right=*/0.614, /*bottom=*/0.7345};
   ImageProcessingOptions image_processing_options{roi, /*rotation_degrees=*/0};
 
   for (int i = 0; i < iterations; ++i) {

mediapipe/tasks/cc/vision/image_embedder/image_embedder_test.cc

@@ -41,7 +41,7 @@ namespace image_embedder {
 namespace {
 
 using ::mediapipe::file::JoinPath;
-using ::mediapipe::tasks::components::containers::Rect;
+using ::mediapipe::tasks::components::containers::RectF;
 using ::mediapipe::tasks::vision::core::ImageProcessingOptions;
 using ::testing::HasSubstr;
 using ::testing::Optional;
@@ -320,7 +320,7 @@ TEST_F(ImageModeTest, SucceedsWithRegionOfInterest) {
       Image crop, DecodeImageFromFile(
                       JoinPath("./", kTestDataDirectory, "burger_crop.jpg")));
   // Region-of-interest in "burger.jpg" corresponding to "burger_crop.jpg".
-  Rect roi{/*left=*/0, /*top=*/0, /*right=*/0.833333, /*bottom=*/1};
+  RectF roi{/*left=*/0, /*top=*/0, /*right=*/0.833333, /*bottom=*/1};
   ImageProcessingOptions image_processing_options{roi, /*rotation_degrees=*/0};
 
   // Extract both embeddings.
@@ -388,7 +388,7 @@ TEST_F(ImageModeTest, SucceedsWithRegionOfInterestAndRotation) {
                           DecodeImageFromFile(JoinPath("./", kTestDataDirectory,
                                                        "burger_rotated.jpg")));
   // Region-of-interest corresponding to burger_crop.jpg.
-  Rect roi{/*left=*/0, /*top=*/0, /*right=*/1, /*bottom=*/0.8333333};
+  RectF roi{/*left=*/0, /*top=*/0, /*right=*/1, /*bottom=*/0.8333333};
   ImageProcessingOptions image_processing_options{roi,
                                                   /*rotation_degrees=*/-90};
 

mediapipe/tasks/cc/vision/image_segmenter/image_segmenter_test.cc

@@ -47,7 +47,7 @@ namespace {
 
 using ::mediapipe::Image;
 using ::mediapipe::file::JoinPath;
-using ::mediapipe::tasks::components::containers::Rect;
+using ::mediapipe::tasks::components::containers::RectF;
 using ::mediapipe::tasks::vision::core::ImageProcessingOptions;
 using ::testing::HasSubstr;
 using ::testing::Optional;
@@ -299,7 +299,7 @@ TEST_F(ImageModeTest, FailsWithRegionOfInterest) {
 
   MP_ASSERT_OK_AND_ASSIGN(std::unique_ptr<ImageSegmenter> segmenter,
                           ImageSegmenter::Create(std::move(options)));
-  Rect roi{/*left=*/0.1, /*top=*/0, /*right=*/0.9, /*bottom=*/1};
+  RectF roi{/*left=*/0.1, /*top=*/0, /*right=*/0.9, /*bottom=*/1};
   ImageProcessingOptions image_processing_options{roi, /*rotation_degrees=*/0};
 
   auto results = segmenter->Segment(image, image_processing_options);

mediapipe/tasks/cc/vision/object_detector/BUILD

@@ -33,6 +33,7 @@ cc_library(
         "//mediapipe/framework/formats:rect_cc_proto",
         "//mediapipe/tasks/cc:common",
         "//mediapipe/tasks/cc/components/calculators:score_calibration_calculator",
+        "//mediapipe/tasks/cc/components/containers:detection_result",
         "//mediapipe/tasks/cc/core:base_options",
         "//mediapipe/tasks/cc/core:utils",
         "//mediapipe/tasks/cc/core/proto:base_options_cc_proto",

mediapipe/tasks/cc/vision/object_detector/object_detector.cc

@@ -30,6 +30,7 @@ limitations under the License.
 #include "mediapipe/framework/formats/image.h"
 #include "mediapipe/framework/formats/rect.pb.h"
 #include "mediapipe/tasks/cc/common.h"
+#include "mediapipe/tasks/cc/components/containers/detection_result.h"
 #include "mediapipe/tasks/cc/core/base_options.h"
 #include "mediapipe/tasks/cc/core/proto/base_options.pb.h"
 #include "mediapipe/tasks/cc/core/proto/inference_subgraph.pb.h"
@@ -56,6 +57,7 @@ constexpr char kSubgraphTypeName[] =
     "mediapipe.tasks.vision.ObjectDetectorGraph";
 constexpr int kMicroSecondsPerMilliSecond = 1000;
 
+using ::mediapipe::tasks::components::containers::ConvertToDetectionResult;
 using ObjectDetectorOptionsProto =
     object_detector::proto::ObjectDetectorOptions;
 
@@ -129,7 +131,8 @@ absl::StatusOr<std::unique_ptr<ObjectDetector>> ObjectDetector::Create(
           Packet detections_packet =
               status_or_packets.value()[kDetectionsOutStreamName];
           Packet image_packet = status_or_packets.value()[kImageOutStreamName];
-          result_callback(detections_packet.Get<std::vector<Detection>>(),
+          result_callback(ConvertToDetectionResult(
+                              detections_packet.Get<std::vector<Detection>>()),
                           image_packet.Get<Image>(),
                           detections_packet.Timestamp().Value() /
                               kMicroSecondsPerMilliSecond);
@@ -144,7 +147,7 @@ absl::StatusOr<std::unique_ptr<ObjectDetector>> ObjectDetector::Create(
       std::move(packets_callback));
 }
 
-absl::StatusOr<std::vector<Detection>> ObjectDetector::Detect(
+absl::StatusOr<ObjectDetectorResult> ObjectDetector::Detect(
     mediapipe::Image image,
     std::optional<core::ImageProcessingOptions> image_processing_options) {
   if (image.UsesGpu()) {
@@ -161,10 +164,11 @@ absl::StatusOr<std::vector<Detection>> ObjectDetector::Detect(
       ProcessImageData(
           {{kImageInStreamName, MakePacket<Image>(std::move(image))},
            {kNormRectName, MakePacket<NormalizedRect>(std::move(norm_rect))}}));
-  return output_packets[kDetectionsOutStreamName].Get<std::vector<Detection>>();
+  return ConvertToDetectionResult(
+      output_packets[kDetectionsOutStreamName].Get<std::vector<Detection>>());
 }
 
-absl::StatusOr<std::vector<Detection>> ObjectDetector::DetectForVideo(
+absl::StatusOr<ObjectDetectorResult> ObjectDetector::DetectForVideo(
     mediapipe::Image image, int64 timestamp_ms,
     std::optional<core::ImageProcessingOptions> image_processing_options) {
   if (image.UsesGpu()) {
@@ -185,7 +189,8 @@ absl::StatusOr<std::vector<Detection>> ObjectDetector::DetectForVideo(
            {kNormRectName,
             MakePacket<NormalizedRect>(std::move(norm_rect))
                 .At(Timestamp(timestamp_ms * kMicroSecondsPerMilliSecond))}}));
-  return output_packets[kDetectionsOutStreamName].Get<std::vector<Detection>>();
+  return ConvertToDetectionResult(
+      output_packets[kDetectionsOutStreamName].Get<std::vector<Detection>>());
 }
 
 absl::Status ObjectDetector::DetectAsync(

mediapipe/tasks/cc/vision/object_detector/object_detector.h

@@ -27,6 +27,7 @@ limitations under the License.
 #include "absl/status/statusor.h"
 #include "mediapipe/framework/formats/detection.pb.h"
 #include "mediapipe/framework/formats/image.h"
+#include "mediapipe/tasks/cc/components/containers/detection_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/image_processing_options.h"
@@ -36,6 +37,10 @@ namespace mediapipe {
 namespace tasks {
 namespace vision {
 
+// Alias the shared DetectionResult struct as result typo.
+using ObjectDetectorResult =
+    ::mediapipe::tasks::components::containers::DetectionResult;
+
 // The options for configuring a mediapipe object detector task.
 struct ObjectDetectorOptions {
   // Base options for configuring MediaPipe Tasks, such as specifying the TfLite
@@ -79,8 +84,7 @@ struct ObjectDetectorOptions {
   // 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<std::vector<mediapipe::Detection>>,
+  std::function<void(absl::StatusOr<ObjectDetectorResult>, const Image&, int64)>
-                     const Image&, int64)>
       result_callback = nullptr;
 };
 
@@ -165,7 +169,7 @@ class ObjectDetector : tasks::vision::core::BaseVisionTaskApi {
   // underlying image data.
   // TODO: Describes the output bounding boxes for gpu input
   // images after enabling the gpu support in MediaPipe Tasks.
-  absl::StatusOr<std::vector<mediapipe::Detection>> Detect(
+  absl::StatusOr<ObjectDetectorResult> Detect(
       mediapipe::Image image,
       std::optional<core::ImageProcessingOptions> image_processing_options =
           std::nullopt);
@@ -188,7 +192,7 @@ class ObjectDetector : tasks::vision::core::BaseVisionTaskApi {
   // unrotated input frame of reference coordinates system, i.e. in `[0,
   // image_width) x [0, image_height)`, which are the dimensions of the
   // underlying image data.
-  absl::StatusOr<std::vector<mediapipe::Detection>> DetectForVideo(
+  absl::StatusOr<ObjectDetectorResult> DetectForVideo(
       mediapipe::Image image, int64 timestamp_ms,
       std::optional<core::ImageProcessingOptions> image_processing_options =
           std::nullopt);

mediapipe/tasks/cc/vision/object_detector/object_detector_test.cc

@@ -35,6 +35,7 @@ limitations under the License.
 #include "mediapipe/framework/port/gtest.h"
 #include "mediapipe/framework/port/parse_text_proto.h"
 #include "mediapipe/framework/port/status_matchers.h"
+#include "mediapipe/tasks/cc/components/containers/detection_result.h"
 #include "mediapipe/tasks/cc/components/containers/rect.h"
 #include "mediapipe/tasks/cc/vision/core/image_processing_options.h"
 #include "mediapipe/tasks/cc/vision/core/running_mode.h"
@@ -65,10 +66,14 @@ namespace vision {
 namespace {
 
 using ::mediapipe::file::JoinPath;
-using ::mediapipe::tasks::components::containers::Rect;
+using ::mediapipe::tasks::components::containers::ConvertToDetectionResult;
+using ::mediapipe::tasks::components::containers::Detection;
+using ::mediapipe::tasks::components::containers::DetectionResult;
+using ::mediapipe::tasks::components::containers::RectF;
 using ::mediapipe::tasks::vision::core::ImageProcessingOptions;
 using ::testing::HasSubstr;
 using ::testing::Optional;
+using DetectionProto = mediapipe::Detection;
 
 constexpr char kTestDataDirectory[] = "/mediapipe/tasks/testdata/vision/";
 constexpr char kMobileSsdWithMetadata[] =
@@ -83,47 +88,45 @@ constexpr char kEfficientDetWithMetadata[] =
 // Checks that the two provided `Detection` proto vectors are equal, with a
 // tolerancy on floating-point scores to account for numerical instabilities.
 // If the proto definition changes, please also change this function.
-void ExpectApproximatelyEqual(const std::vector<Detection>& actual,
+void ExpectApproximatelyEqual(const ObjectDetectorResult& actual,
-                              const std::vector<Detection>& expected) {
+                              const ObjectDetectorResult& expected) {
   const float kPrecision = 1e-6;
-  EXPECT_EQ(actual.size(), expected.size());
+  EXPECT_EQ(actual.detections.size(), expected.detections.size());
-  for (int i = 0; i < actual.size(); ++i) {
+  for (int i = 0; i < actual.detections.size(); ++i) {
-    const Detection& a = actual[i];
+    const Detection& a = actual.detections[i];
-    const Detection& b = expected[i];
+    const Detection& b = expected.detections[i];
-    EXPECT_THAT(a.location_data().bounding_box(),
+    EXPECT_EQ(a.bounding_box, b.bounding_box);
-                EqualsProto(b.location_data().bounding_box()));
+    EXPECT_EQ(a.categories.size(), 1);
-    EXPECT_EQ(a.label_size(), 1);
+    EXPECT_EQ(b.categories.size(), 1);
-    EXPECT_EQ(b.label_size(), 1);
+    EXPECT_EQ(a.categories[0].category_name, b.categories[0].category_name);
-    EXPECT_EQ(a.label(0), b.label(0));
+    EXPECT_NEAR(a.categories[0].score, b.categories[0].score, kPrecision);
-    EXPECT_EQ(a.score_size(), 1);
-    EXPECT_EQ(b.score_size(), 1);
-    EXPECT_NEAR(a.score(0), b.score(0), kPrecision);
   }
 }
 
-std::vector<Detection> GenerateMobileSsdNoImageResizingFullExpectedResults() {
+std::vector<DetectionProto>
-  return {ParseTextProtoOrDie<Detection>(R"pb(
+GenerateMobileSsdNoImageResizingFullExpectedResults() {
+  return {ParseTextProtoOrDie<DetectionProto>(R"pb(
             label: "cat"
             score: 0.6328125
             location_data {
               format: BOUNDING_BOX
               bounding_box { xmin: 14 ymin: 197 width: 98 height: 99 }
             })pb"),
-          ParseTextProtoOrDie<Detection>(R"pb(
+          ParseTextProtoOrDie<DetectionProto>(R"pb(
             label: "cat"
             score: 0.59765625
             location_data {
               format: BOUNDING_BOX
               bounding_box { xmin: 151 ymin: 78 width: 104 height: 223 }
             })pb"),
-          ParseTextProtoOrDie<Detection>(R"pb(
+          ParseTextProtoOrDie<DetectionProto>(R"pb(
             label: "cat"
             score: 0.5
             location_data {
               format: BOUNDING_BOX
               bounding_box { xmin: 65 ymin: 199 width: 41 height: 101 }
             })pb"),
-          ParseTextProtoOrDie<Detection>(R"pb(
+          ParseTextProtoOrDie<DetectionProto>(R"pb(
             label: "dog"
             score: 0.48828125
             location_data {
@@ -263,8 +266,8 @@ TEST_F(CreateFromOptionsTest, FailsWithIllegalCallbackInImageOrVideoMode) {
         JoinPath("./", kTestDataDirectory, kMobileSsdWithMetadata);
     options->running_mode = running_mode;
     options->result_callback =
-        [](absl::StatusOr<std::vector<Detection>> detections,
+        [](absl::StatusOr<ObjectDetectorResult> detections, const Image& image,
-           const Image& image, int64 timestamp_ms) {};
+           int64 timestamp_ms) {};
     absl::StatusOr<std::unique_ptr<ObjectDetector>> object_detector =
         ObjectDetector::Create(std::move(options));
     EXPECT_EQ(object_detector.status().code(),
@@ -340,34 +343,36 @@ TEST_F(ImageModeTest, Succeeds) {
   MP_ASSERT_OK_AND_ASSIGN(auto results, object_detector->Detect(image));
   MP_ASSERT_OK(object_detector->Close());
   ExpectApproximatelyEqual(
-      results, {ParseTextProtoOrDie<Detection>(R"pb(
+      results,
-                  label: "cat"
+      ConvertToDetectionResult(
-                  score: 0.69921875
+          {ParseTextProtoOrDie<DetectionProto>(R"pb(
-                  location_data {
+             label: "cat"
-                    format: BOUNDING_BOX
+             score: 0.69921875
-                    bounding_box { xmin: 608 ymin: 161 width: 381 height: 439 }
+             location_data {
-                  })pb"),
+               format: BOUNDING_BOX
-                ParseTextProtoOrDie<Detection>(R"pb(
+               bounding_box { xmin: 608 ymin: 161 width: 381 height: 439 }
-                  label: "cat"
+             })pb"),
-                  score: 0.64453125
+           ParseTextProtoOrDie<DetectionProto>(R"pb(
-                  location_data {
+             label: "cat"
-                    format: BOUNDING_BOX
+             score: 0.64453125
-                    bounding_box { xmin: 60 ymin: 398 width: 386 height: 196 }
+             location_data {
-                  })pb"),
+               format: BOUNDING_BOX
-                ParseTextProtoOrDie<Detection>(R"pb(
+               bounding_box { xmin: 60 ymin: 398 width: 386 height: 196 }
-                  label: "cat"
+             })pb"),
-                  score: 0.51171875
+           ParseTextProtoOrDie<DetectionProto>(R"pb(
-                  location_data {
+             label: "cat"
-                    format: BOUNDING_BOX
+             score: 0.51171875
-                    bounding_box { xmin: 256 ymin: 395 width: 173 height: 202 }
+             location_data {
-                  })pb"),
+               format: BOUNDING_BOX
-                ParseTextProtoOrDie<Detection>(R"pb(
+               bounding_box { xmin: 256 ymin: 395 width: 173 height: 202 }
-                  label: "cat"
+             })pb"),
-                  score: 0.48828125
+           ParseTextProtoOrDie<DetectionProto>(R"pb(
-                  location_data {
+             label: "cat"
-                    format: BOUNDING_BOX
+             score: 0.48828125
-                    bounding_box { xmin: 362 ymin: 191 width: 325 height: 419 }
+             location_data {
-                  })pb")});
+               format: BOUNDING_BOX
+               bounding_box { xmin: 362 ymin: 191 width: 325 height: 419 }
+             })pb")}));
 }
 
 TEST_F(ImageModeTest, SucceedsEfficientDetModel) {
@@ -383,34 +388,36 @@ TEST_F(ImageModeTest, SucceedsEfficientDetModel) {
   MP_ASSERT_OK_AND_ASSIGN(auto results, object_detector->Detect(image));
   MP_ASSERT_OK(object_detector->Close());
   ExpectApproximatelyEqual(
-      results, {ParseTextProtoOrDie<Detection>(R"pb(
+      results,
-                  label: "cat"
+      ConvertToDetectionResult(
-                  score: 0.7578125
+          {ParseTextProtoOrDie<DetectionProto>(R"pb(
-                  location_data {
+             label: "cat"
-                    format: BOUNDING_BOX
+             score: 0.7578125
-                    bounding_box { xmin: 858 ymin: 408 width: 225 height: 187 }
+             location_data {
-                  })pb"),
+               format: BOUNDING_BOX
-                ParseTextProtoOrDie<Detection>(R"pb(
+               bounding_box { xmin: 858 ymin: 408 width: 225 height: 187 }
-                  label: "cat"
+             })pb"),
-                  score: 0.72265625
+           ParseTextProtoOrDie<DetectionProto>(R"pb(
-                  location_data {
+             label: "cat"
-                    format: BOUNDING_BOX
+             score: 0.72265625
-                    bounding_box { xmin: 67 ymin: 401 width: 399 height: 192 }
+             location_data {
-                  })pb"),
+               format: BOUNDING_BOX
-                ParseTextProtoOrDie<Detection>(R"pb(
+               bounding_box { xmin: 67 ymin: 401 width: 399 height: 192 }
-                  label: "cat"
+             })pb"),
-                  score: 0.6289063
+           ParseTextProtoOrDie<DetectionProto>(R"pb(
-                  location_data {
+             label: "cat"
-                    format: BOUNDING_BOX
+             score: 0.6289063
-                    bounding_box { xmin: 368 ymin: 210 width: 272 height: 385 }
+             location_data {
-                  })pb"),
+               format: BOUNDING_BOX
-                ParseTextProtoOrDie<Detection>(R"pb(
+               bounding_box { xmin: 368 ymin: 210 width: 272 height: 385 }
-                  label: "cat"
+             })pb"),
-                  score: 0.5859375
+           ParseTextProtoOrDie<DetectionProto>(R"pb(
-                  location_data {
+             label: "cat"
-                    format: BOUNDING_BOX
+             score: 0.5859375
-                    bounding_box { xmin: 601 ymin: 166 width: 298 height: 437 }
+             location_data {
-                  })pb")});
+               format: BOUNDING_BOX
+               bounding_box { xmin: 601 ymin: 166 width: 298 height: 437 }
+             })pb")}));
 }
 
 TEST_F(ImageModeTest, SucceedsWithoutImageResizing) {
@@ -426,7 +433,8 @@ TEST_F(ImageModeTest, SucceedsWithoutImageResizing) {
   MP_ASSERT_OK_AND_ASSIGN(auto results, object_detector->Detect(image));
   MP_ASSERT_OK(object_detector->Close());
   ExpectApproximatelyEqual(
-      results, GenerateMobileSsdNoImageResizingFullExpectedResults());
+      results, ConvertToDetectionResult(
+                   GenerateMobileSsdNoImageResizingFullExpectedResults()));
 }
 
 TEST_F(ImageModeTest, SucceedsWithScoreCalibration) {
@@ -442,13 +450,14 @@ TEST_F(ImageModeTest, SucceedsWithScoreCalibration) {
   MP_ASSERT_OK_AND_ASSIGN(auto results, object_detector->Detect(image));
   MP_ASSERT_OK(object_detector->Close());
   ExpectApproximatelyEqual(
-      results, {ParseTextProtoOrDie<Detection>(R"pb(
+      results,
+      ConvertToDetectionResult({ParseTextProtoOrDie<DetectionProto>(R"pb(
         label: "cat"
         score: 0.6531269142
         location_data {
           format: BOUNDING_BOX
           bounding_box { xmin: 14 ymin: 197 width: 98 height: 99 }
-        })pb")});
+        })pb")}));
 }
 
 TEST_F(ImageModeTest, SucceedsWithScoreThresholdOption) {
@@ -463,11 +472,13 @@ TEST_F(ImageModeTest, SucceedsWithScoreThresholdOption) {
                           ObjectDetector::Create(std::move(options)));
   MP_ASSERT_OK_AND_ASSIGN(auto results, object_detector->Detect(image));
   MP_ASSERT_OK(object_detector->Close());
-  std::vector<Detection> full_expected_results =
+  std::vector<DetectionProto> full_expected_results =
       GenerateMobileSsdNoImageResizingFullExpectedResults();
-  ExpectApproximatelyEqual(results,
+
-                           {full_expected_results[0], full_expected_results[1],
+  ExpectApproximatelyEqual(
-                            full_expected_results[2]});
+      results, ConvertToDetectionResult({full_expected_results[0],
+                                         full_expected_results[1],
+                                         full_expected_results[2]}));
 }
 
 TEST_F(ImageModeTest, SucceedsWithMaxResultsOption) {
@@ -482,10 +493,11 @@ TEST_F(ImageModeTest, SucceedsWithMaxResultsOption) {
                           ObjectDetector::Create(std::move(options)));
   MP_ASSERT_OK_AND_ASSIGN(auto results, object_detector->Detect(image));
   MP_ASSERT_OK(object_detector->Close());
-  std::vector<Detection> full_expected_results =
+  std::vector<DetectionProto> full_expected_results =
       GenerateMobileSsdNoImageResizingFullExpectedResults();
   ExpectApproximatelyEqual(
-      results, {full_expected_results[0], full_expected_results[1]});
+      results, ConvertToDetectionResult(
+                   {full_expected_results[0], full_expected_results[1]}));
 }
 
 TEST_F(ImageModeTest, SucceedsWithAllowlistOption) {
@@ -501,9 +513,10 @@ TEST_F(ImageModeTest, SucceedsWithAllowlistOption) {
                           ObjectDetector::Create(std::move(options)));
   MP_ASSERT_OK_AND_ASSIGN(auto results, object_detector->Detect(image));
   MP_ASSERT_OK(object_detector->Close());
-  std::vector<Detection> full_expected_results =
+  std::vector<DetectionProto> full_expected_results =
       GenerateMobileSsdNoImageResizingFullExpectedResults();
-  ExpectApproximatelyEqual(results, {full_expected_results[3]});
+  ExpectApproximatelyEqual(
+      results, ConvertToDetectionResult({full_expected_results[3]}));
 }
 
 TEST_F(ImageModeTest, SucceedsWithDenylistOption) {
@@ -519,9 +532,10 @@ TEST_F(ImageModeTest, SucceedsWithDenylistOption) {
                           ObjectDetector::Create(std::move(options)));
   MP_ASSERT_OK_AND_ASSIGN(auto results, object_detector->Detect(image));
   MP_ASSERT_OK(object_detector->Close());
-  std::vector<Detection> full_expected_results =
+  std::vector<DetectionProto> full_expected_results =
       GenerateMobileSsdNoImageResizingFullExpectedResults();
-  ExpectApproximatelyEqual(results, {full_expected_results[3]});
+  ExpectApproximatelyEqual(
+      results, ConvertToDetectionResult({full_expected_results[3]}));
 }
 
 TEST_F(ImageModeTest, SucceedsWithRotation) {
@@ -541,13 +555,14 @@ TEST_F(ImageModeTest, SucceedsWithRotation) {
       auto results, object_detector->Detect(image, image_processing_options));
   MP_ASSERT_OK(object_detector->Close());
   ExpectApproximatelyEqual(
-      results, {ParseTextProtoOrDie<Detection>(R"pb(
+      results,
+      ConvertToDetectionResult({ParseTextProtoOrDie<DetectionProto>(R"pb(
         label: "cat"
         score: 0.7109375
         location_data {
           format: BOUNDING_BOX
           bounding_box { xmin: 0 ymin: 622 width: 436 height: 276 }
-        })pb")});
+        })pb")}));
 }
 
 TEST_F(ImageModeTest, FailsWithRegionOfInterest) {
@@ -560,7 +575,7 @@ TEST_F(ImageModeTest, FailsWithRegionOfInterest) {
       JoinPath("./", kTestDataDirectory, kMobileSsdWithMetadata);
   MP_ASSERT_OK_AND_ASSIGN(std::unique_ptr<ObjectDetector> object_detector,
                           ObjectDetector::Create(std::move(options)));
-  Rect roi{/*left=*/0.1, /*top=*/0, /*right=*/0.9, /*bottom=*/1};
+  RectF roi{/*left=*/0.1, /*top=*/0, /*right=*/0.9, /*bottom=*/1};
   ImageProcessingOptions image_processing_options{roi, /*rotation_degrees=*/0};
 
   auto results = object_detector->Detect(image, image_processing_options);
@@ -619,10 +634,11 @@ TEST_F(VideoModeTest, Succeeds) {
   for (int i = 0; i < iterations; ++i) {
     MP_ASSERT_OK_AND_ASSIGN(auto results,
                             object_detector->DetectForVideo(image, i));
-    std::vector<Detection> full_expected_results =
+    std::vector<DetectionProto> full_expected_results =
         GenerateMobileSsdNoImageResizingFullExpectedResults();
     ExpectApproximatelyEqual(
-        results, {full_expected_results[0], full_expected_results[1]});
+        results, ConvertToDetectionResult(
+                     {full_expected_results[0], full_expected_results[1]}));
   }
   MP_ASSERT_OK(object_detector->Close());
 }
@@ -637,9 +653,8 @@ TEST_F(LiveStreamModeTest, FailsWithCallingWrongMethod) {
   options->base_options.model_asset_path =
       JoinPath("./", kTestDataDirectory, kMobileSsdWithMetadata);
   options->running_mode = core::RunningMode::LIVE_STREAM;
-  options->result_callback =
+  options->result_callback = [](absl::StatusOr<ObjectDetectorResult> detections,
-      [](absl::StatusOr<std::vector<Detection>> detections, const Image& image,
+                                const Image& image, int64 timestamp_ms) {};
-         int64 timestamp_ms) {};
 
   MP_ASSERT_OK_AND_ASSIGN(std::unique_ptr<ObjectDetector> object_detector,
                           ObjectDetector::Create(std::move(options)));
@@ -669,9 +684,8 @@ TEST_F(LiveStreamModeTest, FailsWithOutOfOrderInputTimestamps) {
   options->running_mode = core::RunningMode::LIVE_STREAM;
   options->base_options.model_asset_path =
       JoinPath("./", kTestDataDirectory, kMobileSsdWithMetadata);
-  options->result_callback =
+  options->result_callback = [](absl::StatusOr<ObjectDetectorResult> detections,
-      [](absl::StatusOr<std::vector<Detection>> detections, const Image& image,
+                                const Image& image, int64 timestamp_ms) {};
-         int64 timestamp_ms) {};
   MP_ASSERT_OK_AND_ASSIGN(std::unique_ptr<ObjectDetector> object_detector,
                           ObjectDetector::Create(std::move(options)));
   MP_ASSERT_OK(object_detector->DetectAsync(image, 1));
@@ -695,14 +709,14 @@ TEST_F(LiveStreamModeTest, Succeeds) {
   auto options = std::make_unique<ObjectDetectorOptions>();
   options->max_results = 2;
   options->running_mode = core::RunningMode::LIVE_STREAM;
-  std::vector<std::vector<Detection>> detection_results;
+  std::vector<ObjectDetectorResult> detection_results;
   std::vector<std::pair<int, int>> image_sizes;
   std::vector<int64> timestamps;
   options->base_options.model_asset_path =
       JoinPath("./", kTestDataDirectory, kMobileSsdWithMetadata);
   options->result_callback =
       [&detection_results, &image_sizes, &timestamps](
-          absl::StatusOr<std::vector<Detection>> detections, const Image& image,
+          absl::StatusOr<ObjectDetectorResult> detections, const Image& image,
           int64 timestamp_ms) {
         MP_ASSERT_OK(detections.status());
         detection_results.push_back(std::move(detections).value());
@@ -719,11 +733,12 @@ TEST_F(LiveStreamModeTest, Succeeds) {
   // number of iterations.
   ASSERT_LE(detection_results.size(), iterations);
   ASSERT_GT(detection_results.size(), 0);
-  std::vector<Detection> full_expected_results =
+  std::vector<DetectionProto> full_expected_results =
       GenerateMobileSsdNoImageResizingFullExpectedResults();
   for (const auto& detection_result : detection_results) {
     ExpectApproximatelyEqual(
-        detection_result, {full_expected_results[0], full_expected_results[1]});
+        detection_result, ConvertToDetectionResult({full_expected_results[0],
+                                                    full_expected_results[1]}));
   }
   for (const auto& image_size : image_sizes) {
     EXPECT_EQ(image_size.first, image.width());

mediapipe/tasks/cc/vision/utils/landmarks_utils.cc

@@ -22,13 +22,13 @@ limitations under the License.
 
 namespace mediapipe::tasks::vision::utils {
 
-using ::mediapipe::tasks::components::containers::Rect;
+using ::mediapipe::tasks::components::containers::RectF;
 
-float CalculateArea(const Rect& rect) {
+float CalculateArea(const RectF& rect) {
   return (rect.right - rect.left) * (rect.bottom - rect.top);
 }
 
-float CalculateIntersectionArea(const Rect& a, const Rect& b) {
+float CalculateIntersectionArea(const RectF& a, const RectF& b) {
   const float intersection_left = std::max<float>(a.left, b.left);
   const float intersection_top = std::max<float>(a.top, b.top);
   const float intersection_right = std::min<float>(a.right, b.right);
@@ -38,7 +38,7 @@ float CalculateIntersectionArea(const Rect& a, const Rect& b) {
          std::max<float>(intersection_right - intersection_left, 0.0);
 }
 
-float CalculateIOU(const Rect& a, const Rect& b) {
+float CalculateIOU(const RectF& a, const RectF& b) {
   const float area_a = CalculateArea(a);
   const float area_b = CalculateArea(b);
   if (area_a <= 0 || area_b <= 0) return 0.0;

mediapipe/tasks/cc/vision/utils/landmarks_utils.h

@@ -27,15 +27,15 @@ limitations under the License.
 namespace mediapipe::tasks::vision::utils {
 
 // Calculates intersection over union for two bounds.
-float CalculateIOU(const components::containers::Rect& a,
+float CalculateIOU(const components::containers::RectF& a,
-                   const components::containers::Rect& b);
+                   const components::containers::RectF& b);
 
 // Calculates area for face bound
-float CalculateArea(const components::containers::Rect& rect);
+float CalculateArea(const components::containers::RectF& rect);
 
 // Calucates intersection area of two face bounds
-float CalculateIntersectionArea(const components::containers::Rect& a,
+float CalculateIntersectionArea(const components::containers::RectF& a,
-                                const components::containers::Rect& b);
+                                const components::containers::RectF& b);
 }  // namespace mediapipe::tasks::vision::utils
 
 #endif  // MEDIAPIPE_TASKS_CC_VISION_UTILS_LANDMARKS_UTILS_H_