wojtekmach/scidata

Datasets related to science

Scidata

Usage

Scidata currently supports the following training and test datasets:

• MNIST
• FashionMNIST
• CIFAR10

Download or fetch datasets locally:

{train_images, train_labels} = Scidata.MNIST.download()
{test_images, test_labels} = Scidata.MNIST.download_test()

# Unpack train_images like...
{images_binary, tensor_type, shape} = train_images

You can also pass transform functions to download/1:

transform_images = fn {binary, type, shape} ->
  binary
  |> Nx.from_binary(type)
  |> Nx.reshape(shape)
  |> Nx.divide(255)
  |> Nx.to_batched_list(32)
end

{train_images, train_labels} =
  Scidata.MNIST.download(transform_images: transform_images)

# Transform labels as well, e.g. get one-hot encoding
transform_labels = fn {labels_binary, type, _} ->
  labels_binary
  |> Nx.from_binary(type)
  |> Nx.new_axis(-1)
  |> Nx.equal(Nx.tensor(Enum.to_list(0..9)))
  |> Nx.to_batched_list(32)
end

{images, labels} =
  Scidata.MNIST.download(
    transform_images: transform_images,
    transform_labels: transform_labels
  )

Installation

def deps do
  [
    {:scidata, "~> 0.1.0"}
  ]
end

License

Copyright (c) 2021 Tom Rutten

Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0

Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions and limitations under the License.