src.classification.plant package

Submodules

src.classification.plant.dense_classifier module

This file implements a Fully Connected classifier for the plant data.

class src.classification.plant.dense_classifier.PlantDenseClassifier(parameters: Optional[Dict] = None)

Bases: PlantNNBaseClassifier

Classifier consisting of Dense layers only.

initialize_model(parameters: Dict) → None

Initializes a new and pretrained version of the Plant-Dense model

Parameters:

parameters – Parameters for initializing the model.

src.classification.plant.lstm_classifier module

This file implements an LSTM based classifier for the plant data.

class src.classification.plant.lstm_classifier.PlantLSTMClassifier(parameters: Optional[Dict] = None)

Bases: PlantNNBaseClassifier

Classifier that uses LSTM layers and a Dense head for classification.

initialize_model(parameters: Dict) → None

Initializes a new and pretrained version of the Plant-LSTM model

Parameters:

parameters – Parameters for initializing the model.

src.classification.plant.mfcc_cnn_classifier module

This file implements a CNN classifier for the MFCC features derived from the plant data.

class src.classification.plant.mfcc_cnn_classifier.PlantMFCCCNNClassifier(parameters: Optional[Dict] = None)

Bases: PlantNNBaseClassifier

Model that uses MFCC features and Conv layers for classification.

static init_parameters(parameters: Optional[Dict] = None, **kwargs) → Dict

Function that merges the parameters and kwargs

Parameters:

• parameters – Parameter dictionary

• kwargs – Additional parameters in kwargs

Returns:

Combined dictionary with parameters

initialize_model(parameters: Dict) → None

Initializes a new and pretrained version of the Plant-MFCC-CNN model

Parameters:

parameters – Parameters for initializing the model

src.classification.plant.mfcc_resnet_classifier module

This file implements a Resnet classifier for the MFCC features derived from the plant data.

class src.classification.plant.mfcc_resnet_classifier.PlantMFCCResnetClassifier(parameters: Optional[Dict] = None)

Bases: PlantNNBaseClassifier

Model that uses MFCC features and a resnet50 classifier.

static init_parameters(parameters: Optional[Dict] = None, **kwargs) → Dict

Function that merges the parameters and kwargs

Parameters:

• parameters – Parameter dictionary

• kwargs – Additional parameters in kwargs

Returns:

Combined dictionary with parameters

initialize_model(parameters: Dict) → None

Initializes a new and pretrained version of the Plant-MFCC-Resnet model

Parameters:

parameters – Parameters for initializing the model

src.classification.plant.nn_classifier module

This file defines an interface for classifiers for the plant data.

class src.classification.plant.nn_classifier.PlantNNBaseClassifier(name: str, parameters: Optional[Dict] = None)

Bases: PlantEmotionClassifier

Base class for all NN classifiers in tensorflow for plant data.

classify(parameters: Optional[Dict] = None, **kwargs) → array

Classification method used to classify emotions from plant data

Parameters:

• parameters – Parameter dictionary used for classification

• kwargs – Additional kwargs parameters

Returns:

An array with predicted emotion indices

abstract initialize_model(parameters: Dict) → None

Abstract method that creates self.model, a tf Model instance

Parameters:

parameters – Parameters for initializing the model

load(parameters: Optional[Dict] = None, **kwargs) → None

Loading method that loads a previously trained model from disk.

Parameters:

• parameters – Parameters required for loading the model

• kwargs – Additional kwargs parameters

save(parameters: Optional[Dict] = None, **kwargs) → None

Saving method that saves a previously trained model on disk.

Parameters:

• parameters – Parameters required for storing the model

• kwargs – Additional kwargs parameters

train(parameters: Optional[Dict] = None, **kwargs) → None

Training method for plant models

Parameters:

• parameters – Parameter dictionary used for training

• kwargs – Additional kwargs parameters

src.classification.plant.plant_emotion_classifier module

Base class for all plant emotion classifiers

class src.classification.plant.plant_emotion_classifier.PlantEmotionClassifier(name: str = 'plant', parameters: Optional[Dict] = None)

Bases: EmotionClassifier

Base class for all plant emotion classifiers. Contains common functions that concerns all plant classifiers.

abstract classify(parameters: Optional[Dict] = None, **kwargs) → array

The virtual classification method for interfacing

Parameters:

• parameters – Parameter dictionary used for classification

• kwargs – Additional kwargs parameters

Returns:

An array with predicted emotion indices

static compute_mfccs(audio_tensor: Tensor, parameters: Optional[Dict] = None) → Tensor

Function that computes MFCC features from the input tensor.

Parameters:

• audio_tensor – The tensor containing raw time series data.

• parameters – Parameters for the MFCC computation.

Returns:

Tensor with MFCC features.

abstract load(parameters: Optional[Dict] = None, **kwargs) → None

Loading method that loads a previously trained model from disk.

Parameters:

• parameters – Parameters required for loading the model

• kwargs – Additional kwargs parameters

prepare_data(parameters: Dict) → None

Function that prepares speech datasets for training and stores them inside the class.

Parameters:

parameters – Parameter dictionary that contains important params. including: which_set, batch_size, weighted

prepare_training(parameters: Dict) → None

Function that prepares the training by initializing optimizer, loss, metrics and callbacks for training.

Parameters:

parameters – Training parameters

abstract save(parameters: Optional[Dict] = None, **kwargs) → None

Saving method that saves a previously trained model on disk.

Parameters:

• parameters – Parameters required for storing the model

• kwargs – Additional kwargs parameters

abstract train(parameters: Optional[Dict] = None, **kwargs) → None

Virtual training method for interfacing

Parameters:

• parameters – Parameter dictionary used for training

• kwargs – Additional kwargs parameters

Module contents

Package for plant sensor emotion classifiers