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wvabrinskas/NeuronDatasets 1.0.16
Machine learning datasets to be used with Neuron package
⭐️ 1
🕓 19 weeks ago
iOS macOS watchOS tvOS
.package(url: "https://github.com/wvabrinskas/NeuronDatasets.git", from: "1.0.16")


Package contains machine learning datasets that are supported the Neuron package.

Supported Datasets

Dataset Origin
CIFAR-10 Local
QuickDraw Remote

Importing image datasets

You can import images from a directory to create a Dataset that Neuron can use. Useful for datasets you can download from Kaggle. Mostly useful for GAN and other generative networks.

Create an ImageDataset object

  let dataset = ImageDataset(imagesDirectory: URL(string: "/Users/williamvabrinskas/Desktop/ImageDataset")!,
                             imageSize: CGSize(width: 64, height: 64),
                             label: [1.0],
                             imageDepth: .rgb,
                             maxCount: 10000)
  • imagesDirectory: The directory of the images to load. All images should be the same size.
  • imageSize: The expected size of the images
  • label: The label to apply to every image.
  • imageDepth: ImageDepth that describes the expected depth of the images.
  • maxCount: Max count to add to the dataset. Could be useful to save memory. Setting it to 0 will use the whole dataset.
  • validationSplitPercent: Number between 0 and 1. The lower the number the more likely it is the image will be added to the training dataset otherwise it'll be added to the validation dataset.
  • zeroCentered: Format image RGB values between -1 and 1. Otherwise it'll be normalized to between 0 and 1.

To build the dataset just call .build() on the dataset object.

Importing a CSV dataset

You can import a CSV dataset from a directory to create a Dataset that Neuron can use using CSVDataset.

// specifies the headers in the CSV files
enum TestHeaders: String, CSVSupporting {
  case id = "Id"
  case name = "Name"
  func order() -> [TestHeaders] {
  func maxLengthOfItem() -> Int {
    switch self {
    case .name:
      return 10
      return 1

let path = Bundle.module.path(forResource: "smallBabyNamesTest", ofType: "csv") // test csv provided in the bundle

guard let path, let pathUrl = URL(string: path) else { return }

let splitPercentage: Float = 0.2

let csvDataset = CSVDataset<TestHeaders>.init(csvUrl: pathUrl,
                                              headerToFetch: .name,
                                              validationSplitPercentage: splitPercentage,
                                              parameters: .init(oneHot: true))

let build = await csvDataset.build()

  • csvUrl: the url of the CSV file
  • headerToFetch: the K: Header value you want to fetch
  • maxCount: the max number of objects you want. 0 = unlimited
  • validationSplitPercentage: The validation split percentage to generate. min: 0.1, max: 0.9
  • overrideLabel: the label to apply to each object. Otherwise the label will be set to the data. eg. data: [0,1,0], label: [0,1,0]
  • parameters: The configuration parameters


In the bin folder there are some helpful scripts to help format image databases.

Script Description Usage
resize.py will automatically resize images in a given directory to a specified size python3 ./bin/resize.py --width 64 --height 64 --path PATH_TO_IMAGES_DIR


Stars: 1
Last commit: 19 weeks ago
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Release Notes

19 weeks ago

Updated Neuron to 2.0.7

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