visionner 0.0.4

Visionner is a image dataset toolkit

visionner

Visionner is a image dataset toolkit

Purpose of the package

• The purpose of this package is to provide machine learning engineer a image dataset toolkit

Warning

Since Visionner still in alpha and under heavy development , expect to see many changes in the near futures.

Features

• Convert image folder into numpy array
• Import a dataset for unsupervised learning tasks
• Import a dataset for supervised learning tasks
• Normalize the dataset
• Split the trainset and the testset
• Save your dataset
• Open your dataset

Getting Started

The package can be found on pypi hence you can install it using pip

Installation

pip install visionner

Usage

### import your dataset (more suitable for dataset without labels)

>>> from visionner.Dataset.DatasetManager import DatasetImporter

>>> your_dataset=DatasetImporter("path/to/your/dataset/", size=(28, 28))

### import your supervised dataset (more suitable for dataset with labels)

>>> from visionner.Dataset.DatasetManager import SupervisedImporter

>>> features, labels= SupervisedImporter("path/to/your/dataset", categories=["cat", "dog"], size=(28,28))

### normalize your dataset

>>> from visionner.Dataset.DatasetManager import DatasetNormalizer

>>> your_normalized_dataset=DatasetNormalizer(your_dataset)

### create a trainset and a testset

>>> from visionner.Dataset.DatasetManager import TrainTestSpliter

>>> x_train, x_test=TrainTestSpliter(dataset, test_size=0.2)

### visualize the first image of your dataset

>>> import matplotlib.pyplot as plt 

>>> plt.imshow(your_dataset[0])
>>> plt.show()

### save your dataset

>>> from visionner.Dataset.DatasetManager import DatasetSaver

>>> DatasetSaver("my_saved_dataset", your_dataset)

### open your dataset

>>> from visionner.Dataset.DatasetManager import DatasetOpener

>>> my_saved_dataset=DatasetOpener("my_saved_dataset.npy") 

Contribution

Contribution are welcome. Notice a bug ? let us know. Thanks you

Author

• Main Maitainer : Charles TCHANAKE
• email : [e-mail]

Note

If you get an unicode error like this :

SyntaxError: (unicode error) 'unicodeescape' codec can't decode bytes in position 2-3: truncated \UXXXXXXXX escape

add r at the begining of your path like this:

>>> your_dataset=Vision(r"path/to/your/dataset/", size=(28, 28), normalize=True)

Warning

Since Visionner still in alpha and under heavy development , expect to see many changes in the near futures.