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model.template
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model.template
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# - 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}