Update EmbeddingResult format and dependent tasks.

PiperOrigin-RevId: 486186491
2022-11-04 11:20:07 -07:00
parent 66e591d4bc
commit 5e1a2fcdbb
31 changed files with 499 additions and 387 deletions
@@ -34,3 +34,18 @@ mediapipe_proto_library(
        "//mediapipe/tasks/cc/components/calculators:score_calibration_calculator_proto",
    ],
 )
+
+mediapipe_proto_library(
+    name = "embedder_options_proto",
+    srcs = ["embedder_options.proto"],
+)
+
+mediapipe_proto_library(
+    name = "embedding_postprocessing_graph_options_proto",
+    srcs = ["embedding_postprocessing_graph_options.proto"],
+    deps = [
+        "//mediapipe/framework:calculator_options_proto",
+        "//mediapipe/framework:calculator_proto",
+        "//mediapipe/tasks/cc/components/calculators:tensors_to_embeddings_calculator_proto",
+    ],
+)
@@ -0,0 +1,36 @@
+/* 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.processors.proto;
+
+option java_package = "com.google.mediapipe.tasks.components.processors.proto";
+option java_outer_classname = "EmbedderOptionsProto";
+
+// Shared options used by all embedding extraction tasks.
+message EmbedderOptions {
+  // Whether to normalize the returned feature vector with L2 norm. Use this
+  // option only if the model does not already contain a native L2_NORMALIZATION
+  // TF Lite Op. In most cases, this is already the case and L2 norm is thus
+  // achieved through TF Lite inference.
+  optional bool l2_normalize = 1;
+
+  // Whether the returned embedding should be quantized to bytes via scalar
+  // quantization. Embeddings are implicitly assumed to be unit-norm and
+  // therefore any dimension is guaranteed to have a value in [-1.0, 1.0]. Use
+  // the l2_normalize option if this is not the case.
+  optional bool quantize = 2;
+}
@@ -0,0 +1,38 @@
+/* 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.processors.proto;
+
+import "mediapipe/framework/calculator.proto";
+import "mediapipe/tasks/cc/components/calculators/tensors_to_embeddings_calculator.proto";
+
+message EmbeddingPostprocessingGraphOptions {
+  extend mediapipe.CalculatorOptions {
+    optional EmbeddingPostprocessingGraphOptions ext = 476346926;
+  }
+
+  // Options for the TensorsToEmbeddings calculator encapsulated by the
+  // EmbeddingPostprocessingGraph.
+  optional mediapipe.TensorsToEmbeddingsCalculatorOptions
+      tensors_to_embeddings_options = 1;
+
+  // Whether output tensors are quantized (kTfLiteUint8) or not (kFloat32).
+  optional bool has_quantized_outputs = 2;
+
+  // TODO: add options to control whether timestamp aggregation
+  // should be used or not.
+}