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mnist-matlab/README.md

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+# MNIST database of handwritten digits in MATLAB format
+
+This repository provides a simple conversion function of the original MNIST dataset into MATLAB `.mat` format for easy usage. Be sure to also pull the submodules containing the [original](https://github.com/sunsided/mnist) MNIST dataset.
+
+In order to convert the data, execute
+
+```matlab
+convertMNIST
+```
+
+once in this directory, which will create `mnist.mat`. After that, you can use
+
+```matlab
+load('mnist.mat')
+```
+
+which will load two variables into your workspace:
+
+- `training`, which contains the training set and
+- `test`, which contains the test set.
+
+Both variables are represented as structures of the following fields:
+
+- `count`: The number `N` of images
+- `width`: The width `W` of each image
+- `height`: The height `H` of each image
+- `images`: A `H` by `W` by `N` array of all images
+- `labels`: An array of `N` values describing the image label
+
+The `images` are encoded as doubles with a range of `0`..`1`, where `0` is background and `1` is foreground. The original MNIST dataset interprets these as `0` for white and `1` for black.
+
+The `labels` field is encoded as categorical double values in the range of `0` through `9` inclusive.

mnist-matlab/convertMNIST.m

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+function [ dataset ] = convertMNIST( image_file, label_file )
+%CONVERTMNIST Converts the original MNIST dataset into MATLAB format.
+
+    if exist('image_file', 'var') && exist('label_file', 'var')
+
+        ifid = fopen(image_file, 'rb');
+        if ifid == -1
+            error('CMNIST:InputFileNotFound', ['No such file: ' image_file])
+        end
+        ic = onCleanup(@() fclose(ifid));
+
+        lfid = fopen(label_file, 'rb');
+        if lfid == -1
+            error('CMNIST:InputFileNotFound', ['No such file: ' label_file])
+        end
+        lc = onCleanup(@() fclose(lfid));
+
+        images = load_images(image_file, ifid);
+        num_images = size(images, 3);
+        width = size(images, 2);
+        height = size(images, 1);
+
+        labels = load_labels(label_file, lfid, num_images);
+
+        dataset = struct('count', num_images, ...
+                         'width', width, 'height', height, ...
+                         'images', images, ...
+                         'labels', labels);
+        return
+
+    end
+
+    training = load_set('train');
+    test     = load_set('t10k');
+
+    save('mnist.mat', 'training', 'test');
+
+    function [set] = load_set(set_name)
+
+        original_path     = 'mnist-matlab/original/';
+        uncompressed_path = '.uncompressed/';
+
+        set_image_file = [set_name '-images-idx3-ubyte'];
+        set_label_file = [set_name '-labels-idx1-ubyte'];
+
+        original_image_file = [original_path set_image_file '.gz'];
+        original_label_file = [original_path set_label_file '.gz'];
+
+        disp(['Unzipping ' original_image_file ' ...']);
+        gunzip(original_image_file, uncompressed_path);
+
+        disp(['Unzipping ' original_label_file ' ...']);
+        gunzip(original_label_file, uncompressed_path);
+
+        set = convertMNIST([uncompressed_path set_image_file], [uncompressed_path set_label_file]);
+
+    end
+
+    function [images] = load_images(image_file, ifid)
+
+        % image magic number is 2051, stored as big-endian
+        magic_number = fread(ifid, 1, 'int32', 0, 'ieee-be');      
+        if magic_number ~= 2051
+            error('CMNIST:InvalidFile', ['Invalid file header in: ' image_file])
+        end
+
+        image_count  = fread(ifid, 1, 'int32', 0, 'ieee-be');
+        rows_count   = fread(ifid, 1, 'int32', 0, 'ieee-be');
+        column_count = fread(ifid, 1, 'int32', 0, 'ieee-be');
+
+        images = fread(ifid, inf, 'unsigned char');
+        if numel(images) ~= (image_count*rows_count*column_count)
+            error('CMNIST:InvalidFile', ['Invalid data header in: ' image_file])
+        end
+
+        images = reshape(images, column_count, rows_count, image_count);
+        images = permute(images, [2 1 3]);
+
+        % scale to 0..1
+        images = double(images) / 255;
+
+    end
+
+    function [labels] = load_labels(label_file, lfid, image_count)
+
+        % label magic number is 2049, stored as big-endian
+        magic_number = fread(lfid, 1, 'int32', 0, 'ieee-be');      
+        if magic_number ~= 2049
+            error('CMNIST:InvalidFile', ['Invalid file header in: ' label_file])
+        end
+
+        label_count  = fread(lfid, 1, 'int32', 0, 'ieee-be');
+        if image_count ~= label_count
+            error('CMNIST:InvalidFile', ['Label count mismatch in: ' label_file])
+        end
+
+        labels = fread(lfid, inf, 'unsigned char');
+        if numel(labels) ~= label_count
+            error('CMNIST:InvalidFile', ['Invalid data header in: ' label_file])
+        end
+
+        labels = double(labels);
+
+    end
+
+end
+