stouputils.data_science.models.keras.xception module#

Xception model implementation.

This module provides a wrapper class for the Xception model, a deep convolutional neural network designed for efficient image classification. Xception uses depthwise separable convolutions, which significantly reduce the number of parameters and computational complexity compared to standard convolutional layers.

Available models: - Xception: The standard Xception model

The model supports transfer learning from ImageNet pre-trained weights.

class Xception(num_classes: int, kfold: int = 0, transfer_learning: str = 'imagenet', **override_params: Any)[source]#

Bases: BaseKeras

Xception implementation using advanced model class with common functionality. For information, refer to the ModelInterface class.

class_routine(kfold: int = 0, transfer_learning: str = 'imagenet', verbose: int = 0, **override_params: Any) → ModelInterface#

Run the full routine for Xception model.

Parameters:

  • dataset (Dataset) – Dataset to use for training and evaluation.

  • kfold (int) – K-fold cross validation index.

  • transfer_learning (str) – Pre-trained weights to use, can be “imagenet” or a dataset path like ‘data/pizza_not_pizza’.

  • verbose (int) – Verbosity level.

  • **kwargs (Any) – Additional arguments.

Returns:

Trained model instance.

Return type:

Xception

model#

alias of Xception