STT-tensorflow/tensorflow/lite/tools/evaluation/proto/preprocessing_steps.proto
Thai Nguyen 81c88fb3ab Simplify preprocessing steps for image classification
PiperOrigin-RevId: 290878807
Change-Id: I0ea3c7629659f8dac49ee5a4153b9b3e458946d9
2020-01-21 20:23:25 -08:00

112 lines
3.2 KiB
Protocol Buffer

/* Copyright 2019 The TensorFlow 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 tflite.evaluation;
option cc_enable_arenas = true;
option java_multiple_files = true;
option java_package = "tflite.evaluation";
// Defines the preprocesing steps available.
//
// Next ID: 5
message ImagePreprocessingStepParams {
oneof params {
CroppingParams cropping_params = 1;
ResizingParams resizing_params = 2;
PaddingParams padding_params = 3;
NormalizationParams normalization_params = 4;
}
}
// Defines the size of an image.
//
// Next ID: 3
message ImageSize {
// Width of the image.
required uint32 width = 1;
// Height of the image.
required uint32 height = 2;
}
// Defines parameters for central-cropping.
//
// Next ID: 4
message CroppingParams {
oneof params {
// Fraction for central-cropping.
// A central cropping-fraction of 0.875 is considered best for Inception
// models, hence the default value. See:
// https://github.com/tensorflow/tpu/blob/master/models/experimental/inception/inception_preprocessing.py#L296
// Set to 0 to disable cropping.
float cropping_fraction = 1 [default = 0.875];
// The target size after cropping.
ImageSize target_size = 2;
}
// Crops to a square image.
optional bool square_cropping = 3;
}
// Defines parameters for bilinear central-resizing.
//
// Next ID: 3
message ResizingParams {
// Size of the image after resizing.
required ImageSize target_size = 1;
// If this flag is true, the resize function will preserve the image's aspect
// ratio. Note that in this case, the size of output image may not equal to
// the target size defined above.
required bool aspect_preserving = 2;
}
// Defines parameters for central-padding.
//
// Next ID: 4
message PaddingParams {
oneof params {
// Size of the image after padding.
ImageSize target_size = 1;
// Pads to a square image.
bool square_padding = 2;
}
// Padding value.
required int32 padding_value = 3;
}
// Defines parameters for normalization.
// The normalization formula is: output = (input - mean) * scale.
//
// Next ID: 4
message NormalizationParams {
message PerChannelMeanValues {
// The mean values of r channel.
required float r_mean = 1;
// The mean values of g channel.
required float g_mean = 2;
// The mean values of b channel.
required float b_mean = 3;
}
oneof mean {
// Channelwise mean value.
float channelwise_mean = 1;
// Per-Channel mean values.
PerChannelMeanValues means = 2;
}
// Scale value in the normalization.
required float scale = 3 [default = 1.0];
}