37 lines
1.5 KiB
Protocol Buffer
37 lines
1.5 KiB
Protocol Buffer
/* 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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syntax = "proto2";
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package mediapipe.tasks.components.processors.proto;
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option java_package = "com.google.mediapipe.tasks.components.processors.proto";
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option java_outer_classname = "EmbedderOptionsProto";
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// Shared options used by all embedding extraction tasks.
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message EmbedderOptions {
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// Whether to normalize the returned feature vector with L2 norm. Use this
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// option only if the model does not already contain a native L2_NORMALIZATION
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// TF Lite Op. In most cases, this is already the case and L2 norm is thus
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// achieved through TF Lite inference.
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optional bool l2_normalize = 1;
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// Whether the returned embedding should be quantized to bytes via scalar
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// quantization. Embeddings are implicitly assumed to be unit-norm and
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// therefore any dimension is guaranteed to have a value in [-1.0, 1.0]. Use
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// the l2_normalize option if this is not the case.
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optional bool quantize = 2;
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}
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