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MNIST database Introduction: MNIST is a handwritten digital database, which has 60 000 and 10 000 training set test sample set. It is a subset of the NIST database.
MNIST official database at: http: //yann.lecun.com/exdb/mnist/, can also be downloaded directly under the windows, train-images-idx3-ubyte.gz, train-labels-idx1-ubyte.gz like. Download four files, unzip. After extracting these files are not found in standard image format. These image data are stored in a binary file. Each sample image width and height is 28 * 28.
The following is to convert it into a normal jpg image format code:
#include < iostream >
#include < fstream >
#include "opencv2 / core / core.hpp"
#include "opencv2 / highgui / highgui.hpp"
#include "opencv2 / imgproc / imgproc.hpp"
using namespace std;
int ReverseInt (int i)
{
unsigned char ch1, ch2, ch3, ch4;
ch1 = i & 255;
ch2 = (i >> 8) & 255;
ch3 = (i >> 16) & 255;
ch4 = (i >> 24) & 255;
return ((int) ch1 << 24) + ((int) ch2 << 16) + ((int) ch3 << 8) + ch4;
}
void read_Mnist (string filename, vector & vec)
{
ifstream file (filename, ios :: binary);
if (file.is_open ()) {
int magic_number = 0;
int number_of_images = 0;
int n_rows = 0;
int n_cols = 0;
file.read ((char *) & magic_number, sizeof (magic_number));
magic_number = ReverseInt (magic_number);
file.read ((char *) & number_of_images, sizeof (number_of_images));
number_of_images = ReverseInt (number_of_images);
file.read ((char *) & n_rows, sizeof (n_rows));
n_rows = ReverseInt (n_rows);
file.read ((char *) & n_cols, sizeof (n_cols));
n_cols = ReverseInt (n_cols);
for (int i = 0; i
cv :: Mat tp = cv :: Mat :: zeros (n_rows, n_cols, CV_8UC1);
for (int r = 0; r
for (int c = 0; c
unsigned char temp = 0;
file.read ((char *) & temp, sizeof (temp));
tp.at (r, c) = (int) temp;
}
}
vec.push_back (tp);
}
}
}
void read_Mnist_Label (string filename, vector & vec)
{
ifstream file (filename, ios :: binary);
if (file.is_open ()) {
int magic_number = 0;
int number_of_images = 0;
int n_rows = 0;
int n_cols = 0;
file.read ((char *) & magic_number, sizeof (magic_number));
magic_number = ReverseInt (magic_number);
file.read ((char *) & number_of_images, sizeof (number_of_images));
number_of_images = ReverseInt (number_of_images);
for (int i = 0; i
unsigned char temp = 0;
file.read ((char *) & temp, sizeof (temp));
vec [i] = (int) temp;
}
}
}
string GetImageName (int number, int arr [])
{
string str1, str2;
for (int i = 0; i <10; i ++) {
if (number == i) {
arr [i] ++;
char ch1 [10];
sprintf (ch1, "% d", arr [i]);
str1 = std :: string (ch1);
if (arr [i] <10) {
str1 = "0000" + str1;
} Else if (arr [i] <100) {
str1 = "000" + str1;
} Else if (arr [i] <1000) {
str1 = "00" + str1;
} Else if (arr [i] <10000) {
str1 = "0" + str1;
}
break;
}
}
char ch2 [10];
sprintf (ch2, "% d", number);
str2 = std :: string (ch2);
str2 = str2 + "_" + str1;
return str2;
}
int main ()
{
// Reference: http://eric-yuan.me/cpp-read-mnist/
// Test images and test labels
// Read MNIST image into OpenCV Mat vector
string filename_test_images = "D: /Download/t10k-images-idx3-ubyte/t10k-images.idx3-ubyte";
int number_of_test_images = 10000;
vector vec_test_images;
read_Mnist (filename_test_images, vec_test_images);
// Read MNIST label into int vector
string filename_test_labels = "D: /Download/t10k-labels-idx1-ubyte/t10k-labels.idx1-ubyte";
vector vec_test_labels (number_of_test_images);
read_Mnist_Label (filename_test_labels, vec_test_labels);
if (vec_test_images.size ()! = vec_test_labels.size ()) {
cout << "parse MNIST test file error" << endl;
return -1;
}
// Save test images
int count_digits [10];
for (int i = 0; i <10; i ++)
count_digits [i] = 0;
string save_test_images_path = "D: / Download / MNIST / test_images /";
for (int i = 0; i
int number = vec_test_labels [i];
string image_name = GetImageName (number, count_digits);
image_name = save_test_images_path + image_name + ".jpg";
cv :: imwrite (image_name, vec_test_images [i]);
}
// Train images and train labels
// Read MNIST image into OpenCV Mat vector
string filename_train_images = "D: /Download/train-images-idx3-ubyte/train-images.idx3-ubyte";
int number_of_train_images = 60000;
vector vec_train_images;
read_Mnist (filename_train_images, vec_train_images);
// Read MNIST label into int vector
string filename_train_labels = "D: /Download/train-labels-idx1-ubyte/train-labels.idx1-ubyte";
vector vec_train_labels (number_of_train_images);
read_Mnist_Label (filename_train_labels, vec_train_labels);
if (vec_train_images.size ()! = vec_train_labels.size ()) {
cout << "parse MNIST train file error" << endl;
return -1;
}
// Save train images
for (int i = 0; i <10; i ++)
count_digits [i] = 0;
string save_train_images_path = "D: / Download / MNIST / train_images /";
for (int i = 0; i
int number = vec_train_labels [i];
string image_name = GetImageName (number, count_digits);
image_name = save_train_images_path + image_name + ".jpg";
cv :: imwrite (image_name, vec_train_images [i]);
}
return 0;
} |
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