The MNIST database of handwritten digits, has a training set of 60,000 examples, and a test set of 10,000 examples. It is a subset of a larger set available from NIST. The digits have been size-normalized and centered in a fixed-size image.
It is a good database for people who want to try learning techniques and pattern recognition methods on real-world data while spending minimal efforts on preprocessing and formatting.
Instruction
FILE FORMATS FOR THE MNIST DATAbase
The data is stored in a very simple file format designed for storing vectors and multidimensional matrices. General info on this format is given at the end of this page, but you don't need to read that to use the data files.
All the integers in the files are stored in the MSB first (high endian) format used by most non-Intel processors. Users of Intel processors and other low-endian machines must flip the bytes of the header.
There are 4 files:
train-images-idx3-ubyte: training set images` train-labels-idx1-ubyte: training set labels` t10k-images-idx3-ubyte: test set images` t10k-labels-idx1-ubyte: test set labels
The training set contains 60000 examples, and the test set 10000 examples.
The first 5000 examples of the test set are taken from the original NIST training set. The last 5000 are taken from the original NIST test set. The first 5000 are cleaner and easier than the last 5000.
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TRAINING SET LABEL FILE (train-labels-idx1-ubyte):
[offset] [type] [value] [description] 0000 32 bit integer 0x00000801(2049) magic number(MSB first) 0004 32 bit integer 60000 number of items 0008 unsigned byte ?? label 0009 unsigned byte ?? label ........ xxxx unsigned byte ?? label
The labels values are 0 to 9.
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TRAINING SET IMAGE FILE (train-images-idx3-ubyte):
[offset] [type] [value] [description] 0000 32 bit integer 0x00000803(2051) magic number 0004 32 bit integer 60000 number of images 0008 32 bit integer 28 number of rows 0012 32 bit integer 28 number of columns 0016 unsigned byte ?? pixel 0017 unsigned byte ?? pixel ........ xxxx unsigned byte ?? pixel
Pixels are organized row-wise. Pixel values are 0 to 255. 0 means background (white), 255 means foreground (black).
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TEST SET LABEL FILE (t10k-labels-idx1-ubyte):
[offset] [type] [value] [description] 0000 32 bit integer 0x00000801(2049) magic number (MSB first) 0004 32 bit integer 10000 number of items 0008 unsigned byte ?? label 0009 unsigned byte ?? label ........ xxxx unsigned byte ?? label
The labels values are 0 to 9.
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TEST SET IMAGE FILE (t10k-images-idx3-ubyte):
[offset] [type] [value] [description] 0000 32 bit integer 0x00000803(2051) magic number 0004 32 bit integer 10000 number of images 0008 32 bit integer 28 number of rows 0012 32 bit integer 28 number of columns 0016 unsigned byte ?? pixel 0017 unsigned byte ?? pixel ........ xxxx unsigned byte ?? pixel
Pixels are organized row-wise. Pixel values are 0 to 255. 0 means background (white), 255 means foreground (black).
THE IDX FILE FORMAT
The IDX file format is a simple format for vectors and multidimensional matrices of various numerical types.
The basic format is
magic number` size in dimension 0 size in dimension 1 size in dimension 2 ..... size in dimension N data
The magic number is an integer (MSB first). The first 2 bytes are always 0.
The third byte codes the type of the data: 0x08: unsigned byte 0x09: signed byte 0x0B: short (2 bytes) 0x0C: int (4 bytes) 0x0D: float (4 bytes) 0x0E: double (8 bytes)
The 4-th byte codes the number of dimensions of the vector/matrix: 1 for vectors, 2 for matrices....
The sizes in each dimension are 4-byte integers (MSB first, high endian, like in most non-Intel processors).
The data is stored like in a C array, i.e. the index in the last dimension changes the fastest.
Citation
Please use the following citation when referencing the dataset:
@article{lecun1998gradient,
title={Gradient-based learning applied to document recognition},
author={LeCun, Yann and Bottou, L{\'e}on and Bengio, Yoshua and Haffner, Patrick},
journal={Proceedings of the IEEE},
volume={86},
number={11},
pages={2278--2324},
year={1998},
publisher={Ieee}
}
