# Installation
- step 1
```bash
git clone https://github.com/charleslf2/visionner
```
- step 2
```bash
cd visionner
```
- step 3
```bash
py setup.py install
```
# Usage
```python3
>>> from visionner.core import DatasetImporter
>>> your_dataset=DatasetImporter("path/to/your/dataset/", size=(28, 28))
```
```python3
>>> from visionner.core import SupervisedImporter
>>> features, labels= SupervisedImporter("path/to/your/dataset", categories=["cat", "dog"], size=(28,28))
```
```python3
### normalize your dataset
>>> from visionner.core import DatasetNormalizer
>>> your_normalized_dataset=DatasetNormalizer(your_dataset)
```
```python3
### create a trainset and a testset
>>> from visionner.core import TrainTestSpliter
>>> x_train, x_test=TrainTestSpliter(dataset, test_size=0.2)
```
```python3
### visualize the first image of your dataset
>>> import matplotlib.pyplot as plt
>>> plt.imshow(your_dataset[0])
>>> plt.show()
```
```python3
### save your dataset
>>> from visionner.core import DatasetSaver
>>> DatasetSaver("my_saved_dataset", your_dataset)
```
```python3
### open your dataset
>>> from visionner.core import DatasetOpener
>>> my_saved_dataset=DatasetOpener("my_saved_dataset.npy")
```
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