Cleanup after migration to new classification output format.

PiperOrigin-RevId: 489921603

mediapipe/tasks/cc/components/calculators/BUILD

@@ -37,7 +37,6 @@ cc_library(
         "//mediapipe/framework/api2:packet",
         "//mediapipe/framework/api2:port",
         "//mediapipe/framework/formats:classification_cc_proto",
-        "//mediapipe/tasks/cc/components/containers/proto:category_cc_proto",
         "//mediapipe/tasks/cc/components/containers/proto:classifications_cc_proto",
         "@com_google_absl//absl/status",
     ],

mediapipe/tasks/cc/components/calculators/classification_aggregation_calculator.cc

@@ -25,14 +25,12 @@
 #include "mediapipe/framework/calculator_framework.h"
 #include "mediapipe/framework/formats/classification.pb.h"
 #include "mediapipe/tasks/cc/components/calculators/classification_aggregation_calculator.pb.h"
-#include "mediapipe/tasks/cc/components/containers/proto/category.pb.h"
 #include "mediapipe/tasks/cc/components/containers/proto/classifications.pb.h"
 
 namespace mediapipe {
 namespace api2 {
 
 using ::mediapipe::tasks::components::containers::proto::ClassificationResult;
-using ::mediapipe::tasks::components::containers::proto::Classifications;
 
 // Aggregates ClassificationLists into either a ClassificationResult object
 // representing the classification results aggregated by classifier head, or
@@ -57,9 +55,6 @@ using ::mediapipe::tasks::components::containers::proto::Classifications;
 //     The classification result aggregated by timestamp, then by head. Must be
 //     connected if the TIMESTAMPS input is connected, as it signals that
 //     timestamp aggregation is required.
-//   // TODO: remove output once migration is over.
-//   CLASSIFICATION_RESULT - (DEPRECATED) ClassificationResult @Optional
-//     The aggregated classification result.
 //
 // Example without timestamp aggregation:
 // node {
@@ -122,9 +117,6 @@ class ClassificationAggregationCalculator : public Node {
   ClassificationResult ConvertToClassificationResult(CalculatorContext* cc);
   std::vector<ClassificationResult> ConvertToTimestampedClassificationResults(
       CalculatorContext* cc);
-  // TODO: deprecate this function once migration is over.
-  ClassificationResult LegacyConvertToClassificationResult(
-      CalculatorContext* cc);
 };
 
 absl::Status ClassificationAggregationCalculator::UpdateContract(
@@ -137,10 +129,11 @@ absl::Status ClassificationAggregationCalculator::UpdateContract(
         << "The size of classifications input streams should match the "
            "size of head names specified in the calculator options";
   }
-  // TODO: enforce connecting TIMESTAMPED_CLASSIFICATIONS if
+  if (kTimestampsIn(cc).IsConnected()) {
-  // TIMESTAMPS is connected, and connecting CLASSIFICATIONS if TIMESTAMPS is
+    RET_CHECK(kTimestampedClassificationsOut(cc).IsConnected());
-  // not connected. All dependent tasks must be updated to use these outputs
+  } else {
-  // first.
+    RET_CHECK(kClassificationsOut(cc).IsConnected());
+  }
   return absl::OkStatus();
 }
 
@@ -170,11 +163,9 @@ absl::Status ClassificationAggregationCalculator::Process(
     if (kTimestampsIn(cc).IsEmpty()) {
       return absl::OkStatus();
     }
-    classification_result = LegacyConvertToClassificationResult(cc);
     kTimestampedClassificationsOut(cc).Send(
         ConvertToTimestampedClassificationResults(cc));
   } else {
-    classification_result = LegacyConvertToClassificationResult(cc);
     kClassificationsOut(cc).Send(ConvertToClassificationResult(cc));
   }
   kClassificationResultOut(cc).Send(classification_result);
@@ -226,55 +217,6 @@ ClassificationAggregationCalculator::ConvertToTimestampedClassificationResults(
   return results;
 }
 
-ClassificationResult
-ClassificationAggregationCalculator::LegacyConvertToClassificationResult(
-    CalculatorContext* cc) {
-  ClassificationResult result;
-  Timestamp first_timestamp(0);
-  std::vector<Timestamp> timestamps;
-  if (time_aggregation_enabled_) {
-    timestamps = kTimestampsIn(cc).Get();
-    first_timestamp = timestamps[0];
-  } else {
-    timestamps = {cc->InputTimestamp()};
-  }
-  for (Timestamp timestamp : timestamps) {
-    int count = cached_classifications_[timestamp.Value()].size();
-    for (int i = 0; i < count; ++i) {
-      Classifications* c;
-      if (result.classifications_size() <= i) {
-        c = result.add_classifications();
-        if (!head_names_.empty()) {
-          c->set_head_index(i);
-          c->set_head_name(head_names_[i]);
-        }
-      } else {
-        c = result.mutable_classifications(i);
-      }
-      auto* entry = c->add_entries();
-      for (const auto& elem :
-           cached_classifications_[timestamp.Value()][i].classification()) {
-        auto* category = entry->add_categories();
-        if (elem.has_index()) {
-          category->set_index(elem.index());
-        }
-        if (elem.has_score()) {
-          category->set_score(elem.score());
-        }
-        if (elem.has_label()) {
-          category->set_category_name(elem.label());
-        }
-        if (elem.has_display_name()) {
-          category->set_display_name(elem.display_name());
-        }
-      }
-      entry->set_timestamp_ms((timestamp.Value() - first_timestamp.Value()) /
-                              1000);
-    }
-  }
-  return result;
-}
-
 MEDIAPIPE_REGISTER_NODE(ClassificationAggregationCalculator);
 
 }  // namespace api2

mediapipe/tasks/cc/components/containers/proto/BUILD

@@ -18,16 +18,10 @@ package(default_visibility = ["//mediapipe/tasks:internal"])
 
 licenses(["notice"])
 
-mediapipe_proto_library(
-    name = "category_proto",
-    srcs = ["category.proto"],
-)
-
 mediapipe_proto_library(
     name = "classifications_proto",
     srcs = ["classifications.proto"],
     deps = [
-        ":category_proto",
         "//mediapipe/framework/formats:classification_proto",
     ],
 )

mediapipe/tasks/cc/components/containers/proto/category.proto

@@ -1,41 +0,0 @@
-/* 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.
-==============================================================================*/
-
-syntax = "proto2";
-
-package mediapipe.tasks.components.containers.proto;
-
-option java_package = "com.google.mediapipe.tasks.components.containers.proto";
-option java_outer_classname = "CategoryProto";
-
-// TODO: deprecate this message once migration is over.
-// A single classification result.
-message Category {
-  // The index of the category in the corresponding label map, usually packed in
-  // the TFLite Model Metadata [1].
-  //
-  // [1]: https://www.tensorflow.org/lite/convert/metadata
-  optional int32 index = 1;
-  // The score for this category, e.g. (but not necessarily) a probability in
-  // [0,1].
-  optional float score = 2;
-  // A human readable name of the category filled from the label map.
-  optional string display_name = 3;
-  // An ID for the category, not necessarily human-readable, e.g. a Google
-  // Knowledge Graph ID [1], filled from the label map.
-  //
-  // [1]: https://developers.google.com/knowledge-graph
-  optional string category_name = 4;
-}

mediapipe/tasks/cc/components/containers/proto/classifications.proto

@@ -18,27 +18,12 @@ syntax = "proto2";
 package mediapipe.tasks.components.containers.proto;
 
 import "mediapipe/framework/formats/classification.proto";
-import "mediapipe/tasks/cc/components/containers/proto/category.proto";
 
 option java_package = "com.google.mediapipe.tasks.components.containers.proto";
 option java_outer_classname = "ClassificationsProto";
 
-// TODO: deprecate this message once migration is over.
-// List of predicted categories with an optional timestamp.
-message ClassificationEntry {
-  // The array of predicted categories, usually sorted by descending scores,
-  // e.g., from high to low probability.
-  repeated Category categories = 1;
-  // The optional timestamp (in milliseconds) associated to the classifcation
-  // entry. This is useful for time series use cases, e.g., audio
-  // classification.
-  optional int64 timestamp_ms = 2;
-}
-
 // Classifications for a given classifier head, i.e. for a given output tensor.
 message Classifications {
-  // TODO: deprecate this field once migration is over.
-  repeated ClassificationEntry entries = 1;
   // The classification results for this head.
   optional mediapipe.ClassificationList classification_list = 4;
   // The index of the classifier head these categories refer to. This is useful
@@ -48,6 +33,8 @@ message Classifications {
   // name.
   // TODO: Add github link to metadata_schema.fbs.
   optional string head_name = 3;
+  // Reserved fields.
+  reserved 1;
 }
 
 // Classifications for a given classifier model.

mediapipe/tasks/cc/components/processors/classification_postprocessing_graph.cc

@@ -73,7 +73,6 @@ using TensorsSource = mediapipe::tasks::SourceOrNodeOutput<std::vector<Tensor>>;
 constexpr float kDefaultScoreThreshold = std::numeric_limits<float>::lowest();
 
 constexpr char kCalibratedScoresTag[] = "CALIBRATED_SCORES";
-constexpr char kClassificationResultTag[] = "CLASSIFICATION_RESULT";
 constexpr char kClassificationsTag[] = "CLASSIFICATIONS";
 constexpr char kScoresTag[] = "SCORES";
 constexpr char kTensorsTag[] = "TENSORS";
@@ -82,7 +81,6 @@ constexpr char kTimestampedClassificationsTag[] = "TIMESTAMPED_CLASSIFICATIONS";
 
 // Struct holding the different output streams produced by the graph.
 struct ClassificationPostprocessingOutputStreams {
-  Source<ClassificationResult> classification_result;
   Source<ClassificationResult> classifications;
   Source<std::vector<ClassificationResult>> timestamped_classifications;
 };
@@ -400,9 +398,6 @@ absl::Status ConfigureClassificationPostprocessingGraph(
 //     The classification result aggregated by timestamp, then by head. Must be
 //     connected if the TIMESTAMPS input is connected, as it signals that
 //     timestamp aggregation is required.
-//   // TODO: remove output once migration is over.
-//   CLASSIFICATION_RESULT - (DEPRECATED) ClassificationResult @Optional
-//     The aggregated classification result.
 //
 // The recommended way of using this graph is through the GraphBuilder API
 // using the 'ConfigureClassificationPostprocessingGraph()' function. See header
@@ -418,8 +413,6 @@ class ClassificationPostprocessingGraph : public mediapipe::Subgraph {
             sc->Options<proto::ClassificationPostprocessingGraphOptions>(),
             graph[Input<std::vector<Tensor>>(kTensorsTag)],
             graph[Input<std::vector<Timestamp>>(kTimestampsTag)], graph));
-    output_streams.classification_result >>
-        graph[Output<ClassificationResult>(kClassificationResultTag)];
     output_streams.classifications >>
         graph[Output<ClassificationResult>(kClassificationsTag)];
     output_streams.timestamped_classifications >>
@@ -536,8 +529,6 @@ class ClassificationPostprocessingGraph : public mediapipe::Subgraph {
 
     // Connects output.
     ClassificationPostprocessingOutputStreams output_streams{
-        /*classification_result=*/result_aggregation
-            [Output<ClassificationResult>(kClassificationResultTag)],
         /*classifications=*/
         result_aggregation[Output<ClassificationResult>(kClassificationsTag)],
         /*timestamped_classifications=*/

mediapipe/tasks/cc/components/processors/classification_postprocessing_graph.h

@@ -58,9 +58,6 @@ namespace processors {
 //     The classification result aggregated by timestamp, then by head. Must be
 //     connected if the TIMESTAMPS input is connected, as it signals that
 //     timestamp aggregation is required.
-//   // TODO: remove output once migration is over.
-//   CLASSIFICATION_RESULT - (DEPRECATED) ClassificationResult @Optional
-//     The aggregated classification result.
 absl::Status ConfigureClassificationPostprocessingGraph(
     const tasks::core::ModelResources& model_resources,
     const proto::ClassifierOptions& classifier_options,

mediapipe/tasks/cc/components/processors/classification_postprocessing_graph_test.cc

@@ -86,8 +86,6 @@ constexpr char kTensorsTag[] = "TENSORS";
 constexpr char kTensorsName[] = "tensors";
 constexpr char kTimestampsTag[] = "TIMESTAMPS";
 constexpr char kTimestampsName[] = "timestamps";
-constexpr char kClassificationResultTag[] = "CLASSIFICATION_RESULT";
-constexpr char kClassificationResultName[] = "classification_result";
 constexpr char kClassificationsTag[] = "CLASSIFICATIONS";
 constexpr char kClassificationsName[] = "classifications";
 constexpr char kTimestampedClassificationsTag[] = "TIMESTAMPED_CLASSIFICATIONS";
@@ -728,326 +726,6 @@ TEST_F(PostprocessingTest, SucceedsWithTimestamps) {
              })pb")}));
 }
 
-// TODO: remove these tests once migration is over.
-class LegacyPostprocessingTest : public tflite_shims::testing::Test {
- protected:
-  absl::StatusOr<OutputStreamPoller> BuildGraph(
-      absl::string_view model_name, const proto::ClassifierOptions& options,
-      bool connect_timestamps = false) {
-    ASSIGN_OR_RETURN(auto model_resources,
-                     CreateModelResourcesForModel(model_name));
-
-    Graph graph;
-    auto& postprocessing = graph.AddNode(
-        "mediapipe.tasks.components.processors."
-        "ClassificationPostprocessingGraph");
-    MP_RETURN_IF_ERROR(ConfigureClassificationPostprocessingGraph(
-        *model_resources, options,
-        &postprocessing
-             .GetOptions<proto::ClassificationPostprocessingGraphOptions>()));
-    graph[Input<std::vector<Tensor>>(kTensorsTag)].SetName(kTensorsName) >>
-        postprocessing.In(kTensorsTag);
-    if (connect_timestamps) {
-      graph[Input<std::vector<Timestamp>>(kTimestampsTag)].SetName(
-          kTimestampsName) >>
-          postprocessing.In(kTimestampsTag);
-    }
-    postprocessing.Out(kClassificationResultTag)
-            .SetName(kClassificationResultName) >>
-        graph[Output<ClassificationResult>(kClassificationResultTag)];
-
-    MP_RETURN_IF_ERROR(calculator_graph_.Initialize(graph.GetConfig()));
-    ASSIGN_OR_RETURN(auto poller, calculator_graph_.AddOutputStreamPoller(
-                                      kClassificationResultName));
-    MP_RETURN_IF_ERROR(calculator_graph_.StartRun(/*extra_side_packets=*/{}));
-    return poller;
-  }
-
-  template <typename T>
-  void AddTensor(
-      const std::vector<T>& tensor, const Tensor::ElementType& element_type,
-      const Tensor::QuantizationParameters& quantization_parameters = {}) {
-    tensors_->emplace_back(element_type,
-                           Tensor::Shape{1, static_cast<int>(tensor.size())},
-                           quantization_parameters);
-    auto view = tensors_->back().GetCpuWriteView();
-    T* buffer = view.buffer<T>();
-    std::copy(tensor.begin(), tensor.end(), buffer);
-  }
-
-  absl::Status Run(
-      std::optional<std::vector<int>> aggregation_timestamps = std::nullopt,
-      int timestamp = 0) {
-    MP_RETURN_IF_ERROR(calculator_graph_.AddPacketToInputStream(
-        kTensorsName, Adopt(tensors_.release()).At(Timestamp(timestamp))));
-    // Reset tensors for future calls.
-    tensors_ = absl::make_unique<std::vector<Tensor>>();
-    if (aggregation_timestamps.has_value()) {
-      auto packet = absl::make_unique<std::vector<Timestamp>>();
-      for (const auto& timestamp : *aggregation_timestamps) {
-        packet->emplace_back(Timestamp(timestamp));
-      }
-      MP_RETURN_IF_ERROR(calculator_graph_.AddPacketToInputStream(
-          kTimestampsName, Adopt(packet.release()).At(Timestamp(timestamp))));
-    }
-    return absl::OkStatus();
-  }
-
-  absl::StatusOr<ClassificationResult> GetClassificationResult(
-      OutputStreamPoller& poller) {
-    MP_RETURN_IF_ERROR(calculator_graph_.WaitUntilIdle());
-    MP_RETURN_IF_ERROR(calculator_graph_.CloseAllInputStreams());
-
-    Packet packet;
-    if (!poller.Next(&packet)) {
-      return absl::InternalError("Unable to get output packet");
-    }
-    auto result = packet.Get<ClassificationResult>();
-    MP_RETURN_IF_ERROR(calculator_graph_.WaitUntilDone());
-    return result;
-  }
-
- private:
-  CalculatorGraph calculator_graph_;
-  std::unique_ptr<std::vector<Tensor>> tensors_ =
-      absl::make_unique<std::vector<Tensor>>();
-};
-
-TEST_F(LegacyPostprocessingTest, SucceedsWithoutMetadata) {
-  // Build graph.
-  proto::ClassifierOptions options;
-  options.set_max_results(3);
-  options.set_score_threshold(0.5);
-  MP_ASSERT_OK_AND_ASSIGN(
-      auto poller,
-      BuildGraph(kQuantizedImageClassifierWithoutMetadata, options));
-  // Build input tensors.
-  std::vector<uint8> tensor(kMobileNetNumClasses, 0);
-  tensor[1] = 18;
-  tensor[2] = 16;
-
-  // Send tensors and get results.
-  AddTensor(tensor, Tensor::ElementType::kUInt8,
-            /*quantization_parameters=*/{0.1, 10});
-  MP_ASSERT_OK(Run());
-  MP_ASSERT_OK_AND_ASSIGN(auto results, GetClassificationResult(poller));
-
-  // Validate results.
-  EXPECT_THAT(results, EqualsProto(R"pb(classifications {
-                                          entries {
-                                            categories { index: 1 score: 0.8 }
-                                            categories { index: 2 score: 0.6 }
-                                            timestamp_ms: 0
-                                          }
-                                        })pb"));
-}
-
-TEST_F(LegacyPostprocessingTest, SucceedsWithMetadata) {
-  // Build graph.
-  proto::ClassifierOptions options;
-  options.set_max_results(3);
-  MP_ASSERT_OK_AND_ASSIGN(
-      auto poller, BuildGraph(kQuantizedImageClassifierWithMetadata, options));
-  // Build input tensors.
-  std::vector<uint8> tensor(kMobileNetNumClasses, 0);
-  tensor[1] = 12;
-  tensor[2] = 14;
-  tensor[3] = 16;
-  tensor[4] = 18;
-
-  // Send tensors and get results.
-  AddTensor(tensor, Tensor::ElementType::kUInt8,
-            /*quantization_parameters=*/{0.1, 10});
-  MP_ASSERT_OK(Run());
-  MP_ASSERT_OK_AND_ASSIGN(auto results, GetClassificationResult(poller));
-
-  // Validate results.
-  EXPECT_THAT(
-      results,
-      EqualsProto(
-          R"pb(classifications {
-                 entries {
-                   categories {
-                     index: 4
-                     score: 0.8
-                     category_name: "tiger shark"
-                   }
-                   categories {
-                     index: 3
-                     score: 0.6
-                     category_name: "great white shark"
-                   }
-                   categories { index: 2 score: 0.4 category_name: "goldfish" }
-                   timestamp_ms: 0
-                 }
-                 head_index: 0
-                 head_name: "probability"
-               })pb"));
-}
-
-TEST_F(LegacyPostprocessingTest, SucceedsWithScoreCalibration) {
-  // Build graph.
-  proto::ClassifierOptions options;
-  options.set_max_results(3);
-  MP_ASSERT_OK_AND_ASSIGN(
-      auto poller,
-      BuildGraph(kQuantizedImageClassifierWithDummyScoreCalibration, options));
-  // Build input tensors.
-  std::vector<uint8> tensor(kMobileNetNumClasses, 0);
-  tensor[1] = 12;
-  tensor[2] = 14;
-  tensor[3] = 16;
-  tensor[4] = 18;
-
-  // Send tensors and get results.
-  AddTensor(tensor, Tensor::ElementType::kUInt8,
-            /*quantization_parameters=*/{0.1, 10});
-  MP_ASSERT_OK(Run());
-  MP_ASSERT_OK_AND_ASSIGN(auto results, GetClassificationResult(poller));
-
-  // Validate results.
-  EXPECT_THAT(results, EqualsProto(
-                           R"pb(classifications {
-                                  entries {
-                                    categories {
-                                      index: 4
-                                      score: 0.6899744811
-                                      category_name: "tiger shark"
-                                    }
-                                    categories {
-                                      index: 3
-                                      score: 0.6456563062
-                                      category_name: "great white shark"
-                                    }
-                                    categories {
-                                      index: 2
-                                      score: 0.5986876601
-                                      category_name: "goldfish"
-                                    }
-                                    timestamp_ms: 0
-                                  }
-                                  head_index: 0
-                                  head_name: "probability"
-                                })pb"));
-}
-
-TEST_F(LegacyPostprocessingTest, SucceedsWithMultipleHeads) {
-  // Build graph.
-  proto::ClassifierOptions options;
-  options.set_max_results(2);
-  MP_ASSERT_OK_AND_ASSIGN(
-      auto poller,
-      BuildGraph(kFloatTwoHeadsAudioClassifierWithMetadata, options));
-  // Build input tensors.
-  std::vector<float> tensor_0(kTwoHeadsNumClasses[0], 0);
-  tensor_0[1] = 0.2;
-  tensor_0[2] = 0.4;
-  tensor_0[3] = 0.6;
-  std::vector<float> tensor_1(kTwoHeadsNumClasses[1], 0);
-  tensor_1[1] = 0.2;
-  tensor_1[2] = 0.4;
-  tensor_1[3] = 0.6;
-
-  // Send tensors and get results.
-  AddTensor(tensor_0, Tensor::ElementType::kFloat32);
-  AddTensor(tensor_1, Tensor::ElementType::kFloat32);
-  MP_ASSERT_OK(Run());
-  MP_ASSERT_OK_AND_ASSIGN(auto results, GetClassificationResult(poller));
-
-  EXPECT_THAT(results, EqualsProto(
-                           R"pb(classifications {
-                                  entries {
-                                    categories {
-                                      index: 3
-                                      score: 0.6
-                                      category_name: "Narration, monologue"
-                                    }
-                                    categories {
-                                      index: 2
-                                      score: 0.4
-                                      category_name: "Conversation"
-                                    }
-                                    timestamp_ms: 0
-                                  }
-                                  head_index: 0
-                                  head_name: "yamnet_classification"
-                                }
-                                classifications {
-                                  entries {
-                                    categories {
-                                      index: 3
-                                      score: 0.6
-                                      category_name: "Azara\'s Spinetail"
-                                    }
-                                    categories {
-                                      index: 2
-                                      score: 0.4
-                                      category_name: "House Sparrow"
-                                    }
-                                    timestamp_ms: 0
-                                  }
-                                  head_index: 1
-                                  head_name: "bird_classification"
-                                })pb"));
-}
-
-TEST_F(LegacyPostprocessingTest, SucceedsWithTimestamps) {
-  // Build graph.
-  proto::ClassifierOptions options;
-  options.set_max_results(2);
-  MP_ASSERT_OK_AND_ASSIGN(
-      auto poller, BuildGraph(kQuantizedImageClassifierWithMetadata, options,
-                              /*connect_timestamps=*/true));
-  // Build input tensors.
-  std::vector<uint8> tensor_0(kMobileNetNumClasses, 0);
-  tensor_0[1] = 12;
-  tensor_0[2] = 14;
-  tensor_0[3] = 16;
-  std::vector<uint8> tensor_1(kMobileNetNumClasses, 0);
-  tensor_1[5] = 12;
-  tensor_1[6] = 14;
-  tensor_1[7] = 16;
-
-  // Send tensors and get results.
-  AddTensor(tensor_0, Tensor::ElementType::kUInt8,
-            /*quantization_parameters=*/{0.1, 10});
-  MP_ASSERT_OK(Run());
-  AddTensor(tensor_1, Tensor::ElementType::kUInt8,
-            /*quantization_parameters=*/{0.1, 10});
-  MP_ASSERT_OK(Run(
-      /*aggregation_timestamps=*/std::optional<std::vector<int>>({0, 1000}),
-      /*timestamp=*/1000));
-
-  MP_ASSERT_OK_AND_ASSIGN(auto results, GetClassificationResult(poller));
-
-  // Validate results.
-  EXPECT_THAT(
-      results,
-      EqualsProto(
-          R"pb(classifications {
-                 entries {
-                   categories {
-                     index: 3
-                     score: 0.6
-                     category_name: "great white shark"
-                   }
-                   categories { index: 2 score: 0.4 category_name: "goldfish" }
-                   timestamp_ms: 0
-                 }
-                 entries {
-                   categories { index: 7 score: 0.6 category_name: "stingray" }
-                   categories {
-                     index: 6
-                     score: 0.4
-                     category_name: "electric ray"
-                   }
-                   timestamp_ms: 1
-                 }
-                 head_index: 0
-                 head_name: "probability"
-               })pb"));
-}
-
 }  // namespace
 }  // namespace processors
 }  // namespace components

mediapipe/tasks/cc/text/text_classifier/text_classifier_graph.cc

@@ -46,19 +46,11 @@ using ::mediapipe::api2::builder::Source;
 using ::mediapipe::tasks::components::containers::proto::ClassificationResult;
 using ::mediapipe::tasks::core::ModelResources;
 
-constexpr char kClassificationResultTag[] = "CLASSIFICATION_RESULT";
 constexpr char kClassificationsTag[] = "CLASSIFICATIONS";
 constexpr char kTextTag[] = "TEXT";
 constexpr char kMetadataExtractorTag[] = "METADATA_EXTRACTOR";
 constexpr char kTensorsTag[] = "TENSORS";
 
-// TODO: remove once Java API migration is over.
-// Struct holding the different output streams produced by the text classifier.
-struct TextClassifierOutputStreams {
-  Source<ClassificationResult> classification_result;
-  Source<ClassificationResult> classifications;
-};
-
 }  // namespace
 
 // A "TextClassifierGraph" performs Natural Language classification (including
@@ -72,10 +64,6 @@ struct TextClassifierOutputStreams {
 // Outputs:
 //   CLASSIFICATIONS - ClassificationResult @Optional
 //     The classification results aggregated by classifier head.
-// TODO: remove once Java API migration is over.
-//   CLASSIFICATION_RESULT - (DEPRECATED) ClassificationResult @Optional
-//     The aggregated classification result object that has 3 dimensions:
-//     (classification head, classification timestamp, classification category).
 //
 // Example:
 // node {
@@ -102,14 +90,11 @@ class TextClassifierGraph : public core::ModelTaskGraph {
         CreateModelResources<proto::TextClassifierGraphOptions>(sc));
     Graph graph;
     ASSIGN_OR_RETURN(
-        auto output_streams,
+        auto classifications,
         BuildTextClassifierTask(
             sc->Options<proto::TextClassifierGraphOptions>(), *model_resources,
             graph[Input<std::string>(kTextTag)], graph));
-    output_streams.classification_result >>
+    classifications >> graph[Output<ClassificationResult>(kClassificationsTag)];
-        graph[Output<ClassificationResult>(kClassificationResultTag)];
-    output_streams.classifications >>
-        graph[Output<ClassificationResult>(kClassificationsTag)];
     return graph.GetConfig();
   }
 
@@ -124,7 +109,7 @@ class TextClassifierGraph : public core::ModelTaskGraph {
   //   TextClassifier model file with model metadata.
   // text_in: (std::string) stream to run text classification on.
   // graph: the mediapipe builder::Graph instance to be updated.
-  absl::StatusOr<TextClassifierOutputStreams> BuildTextClassifierTask(
+  absl::StatusOr<Source<ClassificationResult>> BuildTextClassifierTask(
       const proto::TextClassifierGraphOptions& task_options,
       const ModelResources& model_resources, Source<std::string> text_in,
       Graph& graph) {
@@ -161,11 +146,7 @@ class TextClassifierGraph : public core::ModelTaskGraph {
 
     // Outputs the aggregated classification result as the subgraph output
     // stream.
-    return TextClassifierOutputStreams{
+    return postprocessing[Output<ClassificationResult>(kClassificationsTag)];
-        /*classification_result=*/postprocessing[Output<ClassificationResult>(
-            kClassificationResultTag)],
-        /*classifications=*/postprocessing[Output<ClassificationResult>(
-            kClassificationsTag)]};
   }
 };
 

mediapipe/tasks/cc/vision/image_classifier/image_classifier_graph.cc

@@ -47,7 +47,6 @@ using ::mediapipe::tasks::components::containers::proto::ClassificationResult;
 
 constexpr float kDefaultScoreThreshold = std::numeric_limits<float>::lowest();
 
-constexpr char kClassificationResultTag[] = "CLASSIFICATION_RESULT";
 constexpr char kClassificationsTag[] = "CLASSIFICATIONS";
 constexpr char kImageTag[] = "IMAGE";
 constexpr char kNormRectTag[] = "NORM_RECT";
@@ -56,7 +55,6 @@ constexpr char kTensorsTag[] = "TENSORS";
 // Struct holding the different output streams produced by the image classifier
 // subgraph.
 struct ImageClassifierOutputStreams {
-  Source<ClassificationResult> classification_result;
   Source<ClassificationResult> classifications;
   Source<Image> image;
 };
@@ -77,9 +75,6 @@ struct ImageClassifierOutputStreams {
 //     The classification results aggregated by classifier head.
 //   IMAGE - Image
 //     The image that object detection runs on.
-// TODO: remove this output once Java API migration is over.
-//   CLASSIFICATION_RESULT - (DEPRECATED) ClassificationResult @Optional
-//     The aggregated classification result.
 //
 // Example:
 // node {
@@ -117,8 +112,6 @@ class ImageClassifierGraph : public core::ModelTaskGraph {
             sc->Options<proto::ImageClassifierGraphOptions>(), *model_resources,
             graph[Input<Image>(kImageTag)],
             graph[Input<NormalizedRect>::Optional(kNormRectTag)], graph));
-    output_streams.classification_result >>
-        graph[Output<ClassificationResult>(kClassificationResultTag)];
     output_streams.classifications >>
         graph[Output<ClassificationResult>(kClassificationsTag)];
     output_streams.image >> graph[Output<Image>(kImageTag)];
@@ -174,8 +167,6 @@ class ImageClassifierGraph : public core::ModelTaskGraph {
     // Outputs the aggregated classification result as the subgraph output
     // stream.
     return ImageClassifierOutputStreams{
-        /*classification_result=*/postprocessing[Output<ClassificationResult>(
-            kClassificationResultTag)],
         /*classifications=*/
         postprocessing[Output<ClassificationResult>(kClassificationsTag)],
         /*image=*/preprocessing[Output<Image>(kImageTag)]};

mediapipe/tasks/java/com/google/mediapipe/tasks/text/BUILD

@@ -48,7 +48,6 @@ android_library(
     deps = [
         "//mediapipe/framework:calculator_options_java_proto_lite",
         "//mediapipe/java/com/google/mediapipe/framework:android_framework",
-        "//mediapipe/tasks/cc/components/containers/proto:category_java_proto_lite",
         "//mediapipe/tasks/cc/components/containers/proto:classifications_java_proto_lite",
         "//mediapipe/tasks/cc/core/proto:base_options_java_proto_lite",
         "//mediapipe/tasks/cc/text/text_classifier/proto:text_classifier_graph_options_java_proto_lite",

mediapipe/tasks/java/com/google/mediapipe/tasks/vision/BUILD

@@ -97,7 +97,6 @@ android_library(
         "//mediapipe/framework:calculator_options_java_proto_lite",
         "//mediapipe/java/com/google/mediapipe/framework:android_framework",
         "//mediapipe/java/com/google/mediapipe/framework/image",
-        "//mediapipe/tasks/cc/components/containers/proto:category_java_proto_lite",
         "//mediapipe/tasks/cc/components/containers/proto:classifications_java_proto_lite",
         "//mediapipe/tasks/cc/core/proto:base_options_java_proto_lite",
         "//mediapipe/tasks/cc/vision/image_classifier/proto:image_classifier_graph_options_java_proto_lite",

mediapipe/tasks/python/components/containers/BUILD

@@ -68,7 +68,7 @@ py_library(
     name = "category",
     srcs = ["category.py"],
     deps = [
-        "//mediapipe/tasks/cc/components/containers/proto:category_py_pb2",
+        "//mediapipe/framework/formats:classification_py_pb2",
         "//mediapipe/tasks/python/core:optional_dependencies",
     ],
 )

mediapipe/tasks/python/components/containers/category.py

@@ -16,10 +16,10 @@
 import dataclasses
 from typing import Any, Optional
 
-from mediapipe.tasks.cc.components.containers.proto import category_pb2
+from mediapipe.framework.formats import classification_pb2
 from mediapipe.tasks.python.core.optional_dependencies import doc_controls
 
-_CategoryProto = category_pb2.Category
+_ClassificationProto = classification_pb2.Classification
 
 
 @dataclasses.dataclass
@@ -45,23 +45,23 @@ class Category:
   category_name: Optional[str] = None
 
   @doc_controls.do_not_generate_docs
-  def to_pb2(self) -> _CategoryProto:
+  def to_pb2(self) -> _ClassificationProto:
     """Generates a Category protobuf object."""
-    return _CategoryProto(
+    return _ClassificationProto(
         index=self.index,
         score=self.score,
-        display_name=self.display_name,
+        label=self.category_name,
-        category_name=self.category_name)
+        display_name=self.display_name)
 
   @classmethod
   @doc_controls.do_not_generate_docs
-  def create_from_pb2(cls, pb2_obj: _CategoryProto) -> 'Category':
+  def create_from_pb2(cls, pb2_obj: _ClassificationProto) -> 'Category':
     """Creates a `Category` object from the given protobuf object."""
     return Category(
         index=pb2_obj.index,
         score=pb2_obj.score,
         display_name=pb2_obj.display_name,
-        category_name=pb2_obj.category_name)
+        category_name=pb2_obj.label)
 
   def __eq__(self, other: Any) -> bool:
     """Checks if this object is equal to the given object.

mediapipe/tasks/python/components/containers/classification_result.py

@@ -49,11 +49,7 @@ class Classifications:
     """Generates a Classifications protobuf object."""
     classification_list_proto = _ClassificationListProto()
     for category in self.categories:
-      classification_proto = _ClassificationProto(
+      classification_proto = category.to_pb2()
-          index=category.index,
-          score=category.score,
-          label=category.category_name,
-          display_name=category.display_name)
       classification_list_proto.classification.append(classification_proto)
     return _ClassificationsProto(
         classification_list=classification_list_proto,
@@ -65,14 +61,9 @@ class Classifications:
   def create_from_pb2(cls, pb2_obj: _ClassificationsProto) -> 'Classifications':
     """Creates a `Classifications` object from the given protobuf object."""
     categories = []
-    for entry in pb2_obj.classification_list.classification:
+    for classification in pb2_obj.classification_list.classification:
       categories.append(
-          category_module.Category(
+          category_module.Category.create_from_pb2(classification))
-              index=entry.index,
-              score=entry.score,
-              display_name=entry.display_name,
-              category_name=entry.label))
-
     return Classifications(
         categories=categories,
         head_index=pb2_obj.head_index,