This comprehensive library for Xircuits encompasses a wide range of functionalities involving Keras datasets, model management, model instantiation, prediction, and transfer learning. It's designed to facilitate various machine learning tasks within the Xircuits visual programming interface.
- Python 3.8 or higher
- TensorFlow 2.x
xircuits install tensorflow_keras
You may also install it manually via
pip install -r requirements.txt
For tasks from dataset preparation to model training and evaluation.
ReadKerasDataSet
: Loads Keras datasets or creates datasets from directories. Supports MNIST, CIFAR-10/100, and custom datasets.FlattenImageData
: Converts 2D dataset tuples to 1D, suitable for 1D neural networks.TrainTestSplit
: Splits datasets into training and testing sets with configurable parameters.KerasCreate1DInputModel
: Creates 1D Keras models for 1D input datasets.KerasCreate2DInputModel
: Assembles 2D Keras models, perfect for image-based datasets.KerasTrainImageClassifier
: Trains Keras models for image classification.KerasEvaluateAccuracy
: Evaluates Keras models against datasets for accuracy and loss.ShouldStop
: Decides if training should stop based on accuracy targets or max retries.SaveKerasModel
: Saves Keras models as.h5
files for later use.
These components support a range of model architectures for image classification.
LoadKerasModel
: Loads Keras models with customizable configurations.KerasPredict
: Performs predictions with Keras models on images.ResNet50
,ResNet101
,ResNet152
: Instantiates various ResNet models with customizable configurations.VGG16
,VGG19
: Provides VGG model architectures for image classification.Xception
: Implements the Xception architecture for image classification.MobileNet
: Offers MobileNet architecture with adjustable parameters.
Designed for easy integration into Xircuits workflows for transfer learning scenarios, suitable for both beginners and experienced ML practitioners.
KerasTransferLearningModel
: Fetches TensorFlow Keras Models for transfer learning.TFDataset
: Retrieves datasets from TensorFlow Datasets.TrainKerasModel
: Trains compiled Keras models with training data.TFDSEvaluateAccuracy
: Evaluates Keras models' accuracy using TensorFlow Datasets.KerasModelCompiler
: Compiles TensorFlow Keras models with custom configurations.SaveKerasModel
: Saves TensorFlow Keras models for future use.