Crates.io | mnist |
lib.rs | mnist |
version | 0.6.0 |
source | src |
created_at | 2017-01-16 13:45:21.285972 |
updated_at | 2023-10-30 03:03:08.338481 |
description | MNIST data set parser. |
homepage | |
repository | https://github.com/davidMcneil/mnist |
max_upload_size | |
id | 8098 |
size | 60,079 |
A crate for parsing the MNIST and Fashion MNIST data set into vectors to be used by Rust programs.
use mnist::*;
use ndarray::prelude::*;
fn main() {
// Deconstruct the returned Mnist struct.
let Mnist {
trn_img,
trn_lbl,
tst_img,
tst_lbl,
..
} = MnistBuilder::new()
.label_format_digit()
.training_set_length(50_000)
.validation_set_length(10_000)
.test_set_length(10_000)
.finalize();
let image_num = 0;
// Can use an Array2 or Array3 here (Array3 for visualization)
let train_data = Array3::from_shape_vec((50_000, 28, 28), trn_img)
.expect("Error converting images to Array3 struct")
.map(|x| *x as f32 / 256.0);
println!("{:#.1?}\n",train_data.slice(s![image_num, .., ..]));
// Convert the returned Mnist struct to Array2 format
let train_labels: Array2<f32> = Array2::from_shape_vec((50_000, 1), trn_lbl)
.expect("Error converting training labels to Array2 struct")
.map(|x| *x as f32);
println!("The first digit is a {:?}",train_labels.slice(s![image_num, ..]) );
let _test_data = Array3::from_shape_vec((10_000, 28, 28), tst_img)
.expect("Error converting images to Array3 struct")
.map(|x| *x as f32 / 256.);
let _test_labels: Array2<f32> = Array2::from_shape_vec((10_000, 1), tst_lbl)
.expect("Error converting testing labels to Array2 struct")
.map(|x| *x as f32);
}
The Fasion MNIST dataset offers a similarly-formatted drop-in replacement dataset for the original MNIST set, but typically poses a more difficult classification challenge that handwritten numbers.
An example of downloading this dataset may be found by running:
$ cargo run --features download --example fashion_mnist