Package contains machine learning datasets that are supported the Neuron package.
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.
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.
bin folder there are some helpful scripts to help format image databases.
|resize.py||will automatically resize images in a given directory to a specified size||
|Last commit: 5 weeks ago|
Updated Neuron version
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