MATLAB读取mnist数据库

以下是MATLAB读取mnist数据库的示例代码：

% 读取训练集
train_images_file = 'train-images-idx3-ubyte';
train_labels_file = 'train-labels-idx1-ubyte';

% 读取图像数据
fp = fopen(train_images_file, 'rb');
magic = fread(fp, 1, 'int32', 0, 'ieee-be');
num_images = fread(fp, 1, 'int32', 0, 'ieee-be');
num_rows = fread(fp, 1, 'int32', 0, 'ieee-be');
num_cols = fread(fp, 1, 'int32', 0, 'ieee-be');
images = fread(fp, inf, 'unsigned char');
images = reshape(images, num_rows, num_cols, num_images);
images = permute(images, [2 1 3]);
fclose(fp);

% 读取标签数据
fp = fopen(train_labels_file, 'rb');
magic = fread(fp, 1, 'int32', 0, 'ieee-be');
num_labels = fread(fp, 1, 'int32', 0, 'ieee-be');
labels = fread(fp, inf, 'unsigned char');
fclose(fp);

% 显示图像和标签
index = 1;
imshow(images(:,:,index));
title(num2str(labels(index)));

% 读取测试集
test_images_file = 't10k-images-idx3-ubyte';
test_labels_file = 't10k-labels-idx1-ubyte';

% 读取图像数据
fp = fopen(test_images_file, 'rb');
magic = fread(fp, 1, 'int32', 0, 'ieee-be');
num_images = fread(fp, 1, 'int32', 0, 'ieee-be');
num_rows = fread(fp, 1, 'int32', 0, 'ieee-be');
num_cols = fread(fp, 1, 'int32', 0, 'ieee-be');
images = fread(fp, inf, 'unsigned char');
images = reshape(images, num_rows, num_cols, num_images);
images = permute(images, [2 1 3]);
fclose(fp);

% 读取标签数据
fp = fopen(test_labels_file, 'rb');
magic = fread(fp, 1, 'int32', 0, 'ieee-be');
num_labels = fread(fp, 1, 'int32', 0, 'ieee-be');
labels = fread(fp, inf, 'unsigned char');
fclose(fp);

% 显示图像和标签
index = 1;
imshow(images(:,:,index));
title(num2str(labels(index)));

在这个示例中，我们首先读取训练集和测试集的图像数据和标签数据。然后，我们使用`imshow`函数显示了第一张图像和它的标签。需要注意的是，MNIST数据库中的图像数据是28x28的灰度图像，因此需要使用`permute`函数将它们的维度从[行，列，图像数]转换为[列，行，图像数]。