我一直在尝试读取MNIST数据集，以便能够将其格式化以用于神经网络。但是我一直在努力试图从高端转换到低端到工作。
当我读取数据时，输出的第一个Integer是529205256，当转换为低端格式为134777631时，仍然高于2051的预期“幻数” {1}}。
无论我尝试哪种解决方案，我都会得到相同的错误号码，所以如果有人能够向我解释我的错误，我真的很感激。
部分代码是从github借来的。
这是我的代码中发生错误的部分：
public static List<int[][]> getImages(String infile) {
ByteBuffer bb = loadFileToByteBuffer(infile);
assertMagicNumber(IMAGE_FILE_MAGIC_NUMBER, bb.getInt());
int numImages = bb.getInt();
int numRows = bb.getInt();
int numColumns = bb.getInt();
List<int[][]> images = new ArrayList<>();
for (int i = 0; i < numImages; i++)
images.add(readImage(numRows, numColumns, bb));
return images;
}
当调用bb.getInt（）时，它返回整数529205256，即使在使用此位代码进行转换后
public static int swap(int value)
{
int b1 = (value >> 0) & 0xff;
int b2 = (value >> 8) & 0xff;
int b3 = (value >> 16) & 0xff;
int b4 = (value >> 24) & 0xff;
return b1 << 24 | b2 << 16 | b3 << 8 | b4 << 0;
}
仍然没有产生正确的数字，因此 assertMagicNumber 会抛出异常，因为值不相等。
如果有必要，这是课程的其余部分：
package core;
import static java.lang.String.format;
import java.io.ByteArrayOutputStream;
import java.io.DataInputStream;
import java.io.RandomAccessFile;
import java.nio.ByteBuffer;
import java.nio.ByteOrder;
import java.nio.channels.FileChannel;
import java.util.ArrayList;
import java.util.List;
public class MnistReader {
public static final int LABEL_FILE_MAGIC_NUMBER = 2049;
public static final int IMAGE_FILE_MAGIC_NUMBER = 2051;
public static int[] getLabels(String infile) {
ByteBuffer bb = loadFileToByteBuffer(infile);
assertMagicNumber(LABEL_FILE_MAGIC_NUMBER, bb.getInt());
int numLabels = bb.getInt();
int[] labels = new int[numLabels];
for (int i = 0; i < numLabels; ++i)
labels[i] = bb.get() & 0xFF; // To unsigned
return labels;
}
public static List<int[][]> getImages(String infile) {
ByteBuffer bb = loadFileToByteBuffer(infile);
assertMagicNumber(IMAGE_FILE_MAGIC_NUMBER, bb.getInt());
int numImages = bb.getInt();
int numRows = bb.getInt();
int numColumns = bb.getInt();
List<int[][]> images = new ArrayList<>();
for (int i = 0; i < numImages; i++)
images.add(readImage(numRows, numColumns, bb));
return images;
}
private static int[][] readImage(int numRows, int numCols, ByteBuffer bb) {
int[][] image = new int[numRows][];
for (int row = 0; row < numRows; row++)
image[row] = readRow(numCols, bb);
return image;
}
private static int[] readRow(int numCols, ByteBuffer bb) {
int[] row = new int[numCols];
for (int col = 0; col < numCols; ++col)
row[col] = bb.get() & 0xFF; // To unsigned
return row;
}
public static void assertMagicNumber(int expectedMagicNumber, int magicNumber) {
System.out.println(expectedMagicNumber);
System.out.println(magicNumber);
if (expectedMagicNumber != magicNumber) {
switch (expectedMagicNumber) {
case LABEL_FILE_MAGIC_NUMBER:
throw new RuntimeException("This is not a label file.");
case IMAGE_FILE_MAGIC_NUMBER:
throw new RuntimeException("This is not an image file.");
default:
throw new RuntimeException(
format("Expected magic number %d, found %d", expectedMagicNumber, magicNumber));
}
}
}
//
//
//
//
public static ByteBuffer loadFileToByteBuffer(String infile) {
return ByteBuffer.wrap(loadFile(infile));
}
public static byte[] loadFile(String infile) {
try {
RandomAccessFile f = new RandomAccessFile(infile, "r");
FileChannel chan = f.getChannel();
long fileSize = chan.size();
ByteBuffer bb = ByteBuffer.allocate((int) fileSize);
chan.read(bb);
bb.flip();
ByteArrayOutputStream baos = new ByteArrayOutputStream();
for (int i = 0; i < fileSize; i++)
baos.write(bb.get());
chan.close();
f.close();
return baos.toByteArray();
} catch (Exception e) {
throw new RuntimeException(e);
}
}
public static String renderImage(int[][] image) {
StringBuffer sb = new StringBuffer();
for (int row = 0; row < image.length; row++) {
sb.append("|");
for (int col = 0; col < image[row].length; col++) {
int pixelVal = image[row][col];
if (pixelVal == 0)
sb.append(" ");
else if (pixelVal < 256 / 3)
sb.append(".");
else if (pixelVal < 2 * (256 / 3))
sb.append("x");
else
sb.append("X");
}
sb.append("|\n");
}
return sb.toString();
}
public static String repeat(String s, int n) {
StringBuilder sb = new StringBuilder();
for (int i = 0; i < n; i++)
sb.append(s);
return sb.toString();
}
/* (Added method)
* converts the image data from a 2-dimensional to a 1-dimensional array
* and compresses the pixel values between 0 and 1
*/
public static double[] convertImage(int[][] source) {
double[] convertedImage = new double[784];
int currentPos = 0;
for(int i = 0; i < source.length; i++) {
for(int j = 0; j < source[i].length; j++) {
convertedImage[currentPos] = source[i][j] / 255;
}
}
return convertedImage;
}
/* (Added method)
* converts the label data from an Integer to a vector that can be used
* as output for the neural network
*/
public static double[] convertLabel(int label) {
double[] convertedLabel = new double[10];
convertedLabel[label] = 1;
return convertedLabel;
}
public static int swap(int value)
{
int b1 = (value >> 0) & 0xff;
int b2 = (value >> 8) & 0xff;
int b3 = (value >> 16) & 0xff;
int b4 = (value >> 24) & 0xff;
return b1 << 24 | b2 << 16 | b3 << 8 | b4 << 0;
}
}
我真的不知道我的错误在哪里，所以我们将不胜感激。
链接到MNIST：http://yann.lecun.com/exdb/mnist/
编辑：事实证明解压缩文件本身存在问题。修好之后，一切都按预期开始了