# - requirement.txt  -  GPU: tensorflow-gpu, CPU: tensorflow
# - If you use the GPU version, you need to install some additional applications.
System:
  MemoryUsage: {MemoryUsage}
  Version: 2

# CNNNetwork: [CNN5, ResNet, DenseNet]
# RecurrentNetwork: [CuDNNBiLSTM, CuDNNLSTM, CuDNNGRU, BiLSTM, LSTM, GRU, BiGRU, NoRecurrent]
# - The recommended configuration is CNN5+GRU
# UnitsNum: [16, 64, 128, 256, 512]
# - This parameter indicates the number of nodes used to remember and store past states.
# Optimizer: Loss function algorithm for calculating gradient.
# - [AdaBound, Adam, Momentum]
# OutputLayer: [LossFunction, Decoder]
# - LossFunction: [CTC, CrossEntropy]
# - Decoder: [CTC, CrossEntropy]
NeuralNet:
  CNNNetwork: {CNNNetwork}
  RecurrentNetwork: {RecurrentNetwork}
  UnitsNum: {UnitsNum}
  Optimizer: {Optimizer}
  OutputLayer:
    LossFunction: {LossFunction}
    Decoder: {Decoder}


# ModelName: Corresponding to the model file in the model directory
# ModelField: [Image, Text]
# ModelScene: [Classification]
# - Currently only Image-Classification is supported.
Model:
  ModelName: {ModelName}
  ModelField: {ModelField}
  ModelScene: {ModelScene}

# FieldParam contains the Image, Text.
# When you filed to Image:
# - Category: Provides a default optional built-in solution:
# -- [ALPHANUMERIC, ALPHANUMERIC_LOWER, ALPHANUMERIC_UPPER,
# -- NUMERIC, ALPHABET_LOWER, ALPHABET_UPPER, ALPHABET, ALPHANUMERIC_CHS_3500_LOWER]
# - or can be customized by:
# -- ['Cat', 'Lion', 'Tiger', 'Fish', 'BigCat']
# - Resize: [ImageWidth, ImageHeight/-1, ImageChannel]
# - ImageChannel: [1, 3]
# - In order to automatically select models using image size, when multiple models are deployed at the same time:
# -- ImageWidth: The width of the image.
# -- ImageHeight: The height of the image.
# - MaxLabelNum: You can fill in -1, or any integer, where -1 means not defining the value.
# -- Used when the number of label is fixed
# When you filed to Text:
# This type is temporarily not supported.
FieldParam:
  Category: {Category}
  Resize: {Resize}
  ImageChannel: {ImageChannel}
  ImageWidth: {ImageWidth}
  ImageHeight: {ImageHeight}
  MaxLabelNum: {MaxLabelNum}
  OutputSplit: {OutputSplit}
  AutoPadding: {AutoPadding}


# The configuration is applied to the label of the data source.
# LabelFrom: [FileName, XML, LMDB]
# ExtractRegex: Only for methods extracted from FileName:
# - Default matching apple_20181010121212.jpg file.
# - The Default is .*?(?=_.*\.)
# LabelSplit: Only for methods extracted from FileName:
# - The split symbol in the file name is like: cat&big cat&lion_20181010121212.png
# - The Default is null.
Label:
  LabelFrom: {LabelFrom}
  ExtractRegex: {ExtractRegex}
  LabelSplit: {LabelSplit}


# DatasetPath: [Training/Validation], The local absolute path of a packed training or validation set.
# SourcePath:  [Training/Validation], The local absolute path to the source folder of the training or validation set.
# ValidationSetNum: This is an optional parameter that is used when you want to extract some of the validation set
# - from the training set when you are not preparing the validation set separately.
# SavedSteps: A Session.run() execution is called a Step,
# - Used to save training progress, Default value is 100.
# ValidationSteps: Used to calculate accuracy, Default value is 500.
# EndAcc: Finish the training when the accuracy reaches [EndAcc*100]% and other conditions.
# EndCost: Finish the training when the cost reaches EndCost and other conditions.
# EndEpochs: Finish the training when the epoch is greater than the defined epoch and other conditions.
# BatchSize: Number of samples selected for one training step.
# ValidationBatchSize: Number of samples selected for one validation step.
# LearningRate: [0.1, 0.01, 0.001, 0.0001]
# - Use a smaller learning rate for fine-tuning.
Trains:
  DatasetPath:
    Training: {DatasetTrainsPath}
    Validation: {DatasetValidationPath}
  SourcePath:
    Training: {SourceTrainPath}
    Validation: {SourceValidationPath}
  ValidationSetNum: {ValidationSetNum}
  SavedSteps: {SavedSteps}
  ValidationSteps: {ValidationSteps}
  EndAcc: {EndAcc}
  EndCost: {EndCost}
  EndEpochs: {EndEpochs}
  BatchSize: {BatchSize}
  ValidationBatchSize: {ValidationBatchSize}
  LearningRate: {LearningRate}

# Binaryzation: The argument is of type list and contains the range of int values, -1 is not enabled.
# MedianBlur: The parameter is an int value, -1 is not enabled.
# GaussianBlur: The parameter is an int value, -1 is not enabled.
# EqualizeHist: The parameter is an bool value.
# Laplace: The parameter is an bool value.
# WarpPerspective: The parameter is an bool value.
# Rotate: The parameter is a positive integer int type greater than 0, -1 is not enabled.
# PepperNoise: This parameter is a float type less than 1, -1 is not enabled.
# Brightness: The parameter is an bool value.
# Saturation: The parameter is an bool value.
# Hue: The parameter is an bool value.
# Gamma: The parameter is an bool value.
# ChannelSwap: The parameter is an bool value.
# RandomBlank: The parameter is a positive integer int type greater than 0, -1 is not enabled.
# RandomTransition: The parameter is a positive integer int type greater than 0, -1 is not enabled.
DataAugmentation:
  Binaryzation: {DA_Binaryzation}
  MedianBlur: {DA_MedianBlur}
  GaussianBlur: {DA_GaussianBlur}
  EqualizeHist: {DA_EqualizeHist}
  Laplace: {DA_Laplace}
  WarpPerspective: {DA_WarpPerspective}
  Rotate: {DA_Rotate}
  PepperNoise: {DA_PepperNoise}
  Brightness: {DA_Brightness}
  Saturation: {DA_Saturation}
  Hue: {DA_Hue}
  Gamma: {DA_Gamma}
  ChannelSwap: {DA_ChannelSwap}
  RandomBlank: {DA_RandomBlank}
  RandomTransition: {DA_RandomTransition}
  RandomCaptcha: {DA_RandomCaptcha}

# Binaryzation: The parameter is an integer number between 0 and 255, -1 is not enabled.
# ReplaceTransparent: Transparent background replacement, bool type.
# HorizontalStitching: Horizontal stitching, bool type.
# ConcatFrames: Horizontally merge two frames according to the provided frame index list, -1 is not enabled.
# BlendFrames: Fusion corresponding frames according to the provided frame index list, -1 is not enabled.
# - [-1] means all frames
Pretreatment:
  Binaryzation: {Pre_Binaryzation}
  ReplaceTransparent: {Pre_ReplaceTransparent}
  HorizontalStitching: {Pre_HorizontalStitching}
  ConcatFrames: {Pre_ConcatFrames}
  BlendFrames: {Pre_BlendFrames}
  ExecuteMap: {Pre_ExecuteMap}