GLvoid CreateImage (GLint ImageId)
{
GLint width, height;
switch (ImageId)
{
case 1:
width = 128;
height = 128;
ImageData1 = (GLint*) malloc (width * height * (sizeof (GLint)));
ReadBmp ("kat_128_128.bmp",(unsigned char*) ImageData1, &TexWidth, &TexHeight);
break;
case 2:
width = 74;
height = 94;
SubImageData1 = (GLint*) malloc (width * height * (sizeof (GLint)));
ReadBmp ("Amoeba_74_94.bmp",(unsigned char*) SubImageData1, &TexWidth, &TexHeight);
}
}
int ocrProcessFile(char* fileName) {
int i, h, w;
uint32 **pix;
createNetworkFromFile();
pix = ReadBmp(fileName, &h, &w);
Image inputImg = getGrayLevel(pix, h, w);
for(i = 0; i < h; i++) {
free(pix[i]);
}
free(pix);
ocrProcess(inputImg);
return 0;
}
void main()
{
int fmode=0;
int i,j;
int red[256];
int green[256];
int blue[256];
FILE *f;
char *filename="text_gray.bmp";
ReadBmp(filename,&tmp1);
printf("%d %d\n",tmp1.height,tmp1.width);
while(1){
printf(" 0:モード法\n 1:判別分析法\n 2:移動平均法\n 3:終了\n");
scanf("%d",&fmode);
if(fmode > 2) break;
tmp2=tmp1; /* 元の画像ファイルのすべての画像データをコピーする */
reset( red, green, blue );
Gray( &tmp2 , &tmp1 );
set( red , green , blue );
switch(fmode){
case 0 : mode(red); //モード法
break;
case 1 : sweep(red); //判別分析法
break;
case 2 : mov_ave(red); //移動平均法
break;
}
WriteBmp("border.bmp",&tmp2);
PrintBmpInfo("border.bmp");
}
}
int main() {
unsigned int iter;
int dctin[64];
int dctout[64];
int quantizeout[64];
int zigzagout[64];
// preallocate memory for global variable
unsigned char ScanBuffer[IMG_HEIGHT_MDU*8][IMG_WIDTH_MDU*8];
ReadBmp(ScanBuffer);
for (iter = 0; iter < IMG_BLOCKS; iter++)
{
readblock(ScanBuffer, dctin);
dct(dctin, dctout);
quantize(dctout,quantizeout);
zigzag(quantizeout, zigzagout);
huffencode(zigzagout);
}
return 0;
}
int autoTrainProcess(int nTrainImg, int nTestImg, double *mse) {
int i, j, h, w, cnt = 0;
//int nTrainChar[nTrainImg];
//int nTestChar[nTestImg];
int *nTrainChar = (int*)calloc(nTrainImg, sizeof(int));
int *nTestChar = (int*)calloc(nTestImg, sizeof(int));
//double ** trainFeature[nTrainImg];
double ***trainFeature = (double***)calloc(nTrainImg, sizeof(double**));
//double ** testFeature[nTestImg];
double ***testFeature = (double***)calloc(nTestImg, sizeof(double**));
uint32 **pix;
FILE *f;
//char *str_train[nTrainImg];
char **str_train = (char**)calloc(nTrainImg, sizeof(char*));
//char *str_test[nTestImg];
char **str_test = (char**)calloc(nTestImg, sizeof(char*));
char trainImgName[100];
char trainTxtName[100];
char testImgName[100];
char testTxtName[100];
/// read train image + text
for(i = 0; i < nTrainImg; i++) {
sprintf(trainTxtName, "train/%d.txt", i+1);
f = fopen(trainTxtName, "r");
fscanf(f, "%d\n", &(nTrainChar[i]));
str_train[i] = (char *) malloc(nTrainChar[i] *sizeof(char));
for(j = 0; j < nTrainChar[i]; j++) {
fscanf(f, "%c", &(str_train[i][j]));
}
fclose(f);
sprintf(trainImgName, "train/%d.bmp", i+1);
pix = ReadBmp(trainImgName, &h, &w);
if (pix == NULL)
return -1;
Image trainImg = getGrayLevel(pix, h, w);
for(j = 0; j < h; j++) {
free(pix[j]);
}
free(pix);
trainImg = binarizeGrayImageKmeans(trainImg);
trainFeature[i] = getFeatureFromImage(trainImg, nTrainChar[i]);
}
printf("start read test img\n");
/// read test img + text
for(i = 0; i < nTestImg; i++) {
sprintf(testTxtName, "test/%d.txt", i+1);
f = fopen(testTxtName, "r");
fscanf(f, "%d\n", &(nTestChar[i]));
str_test[i] = (char *) malloc(nTestChar[i] *sizeof(char));
for(j = 0; j < nTestChar[i]; j++) {
fscanf(f, "%c", &(str_test[i][j]));
printf("%c", str_test[i][j]);
}
fclose(f);
sprintf(testImgName, "test/%d.bmp", i+1);
pix = ReadBmp(testImgName, &h, &w);
if (pix == NULL)
return -1;
Image testImg = getGrayLevel(pix, h, w);
for(j = 0; j < h; j++) {
free(pix[j]);
}
free(pix);
testImg = binarizeGrayImageKmeans(testImg);
testFeature[i] = getFeatureFromImage(testImg, nTestChar[i]);
}
/// init network randomly
initNetwork();
double *outValue;
double charMse, minCharMse = 10000;
int trainComplete = 0;
/// training process
int nOver = 0;
int saved = 0;
char savedFileName[100];
printf("start training\n");
while (cnt < NUM_LOOP) {
cnt++;
/** processing feature data */
/// training network
for (i = 0; i < nTrainImg; i++) {
for(j = 0; j < nTrainChar[i]; j++) {
outValue = getOutFromChar(str_train[i][j]);
trainNetwork(trainFeature[i][j], outValue, 0.1);
free(outValue);
}
}
/// testing network
charMse = 0;
for (i = 0; i < nTestImg; i ++) {
for (j = 0; j < nTestChar[i]; j++) {
outValue = getOutFromChar(str_test[i][j]);
charMse += testError(testFeature[i][j], outValue);
free(outValue);
}
}
/// check if train complete
if (charMse < minCharMse) {
nOver = 0;
minCharMse = charMse;
} else {
if(nOver == 0) {
///save network to file
saved = 1;
sprintf(savedFileName, "%d_%.4lf.wdb", NUM_HID_CHAR, minCharMse);
saveNetworkToFile(savedFileName);
}
printf("over\n");
nOver ++;
if(nOver > 100)
trainComplete = 1;
}
printf("%.2lf %d\n", charMse, cnt);
if (trainComplete) break;
}
if(!saved) {
sprintf(savedFileName, "%d_%.4lf.wdb", NUM_HID_CHAR, minCharMse);
saveNetworkToFile(savedFileName);
}
if (mse != NULL)
{
*mse = minCharMse;
}
for (i = 0; i < nTrainImg; i++) {
for (j = 0; j < nTrainChar[i]; j++) {
free(trainFeature[i][j]);
}
}
for (i = 0; i < nTestImg; i++) {
for (j = 0; j < nTestChar[i]; j++) {
free(testFeature[i][j]);
}
}
return 0;
}
bool Encryption(char *file_in_name){
//初期化
char *file_out_name;//画像の出力・入力ファイル名
char *key_out_file;//鍵ファイル
char *buf;
img *imagein, *imageout;
int h, w;
int i = 0;
int registered_num = 0;//色の登録数
angou *code;//色を変換するテーブル
FILE* fp;
srand((unsigned)time(NULL));
file_out_name = (char *)malloc(sizeof(char)*(strlen(file_in_name) + 10));
strcpy(file_out_name, file_in_name);
strcat(file_out_name, "_conv.bmp");
key_out_file = (char *)malloc(sizeof(char)*(strlen(file_in_name) + 8));
buf = (char *)malloc(sizeof(char)*(strlen(file_in_name) + 1));
strcpy(buf, file_in_name);
strcpy(key_out_file, buf);
strcat(key_out_file, "_key.kp");
imagein = (img *)malloc(sizeof(img));
imageout = (img *)malloc(sizeof(img));
ReadBmp(file_in_name, imagein);
code = (angou *)malloc(sizeof(angou)*imagein->height*imagein->width);
imageout = imagein;
if ((fp = fopen(key_out_file, "w")) == NULL){
MessageBox(NULL, TEXT("key file output error."), NULL, MB_OK);
return false;
}
//画像処理
for (h = 0; h < imagein->height; h++){
for (w = 0; w < imagein->width; w++){
for (i = 0; i <= registered_num; i++){
if (memcmp(&code[i].original_color,
&imagein->data[h][w],
sizeof(code[i].original_color)) == 0){
//登録してある色が見つかったら代入
imageout->data[h][w] = code[i].converted_color;
goto searched_out;
}
}
//変換する色の登録
//変換前の色を登録
code[registered_num].original_color = imagein->data[h][w];
try_again:
//変換後の色を登録
code[registered_num].converted_color.r = rand() % 256;
code[registered_num].converted_color.g = rand() % 256;
code[registered_num].converted_color.b = rand() % 256;
///*変換後の色が既に登録してある色だったら
// 変換後の色の登録をやり直す*/
for (i = 0; i < registered_num; i++){
if (memcmp(&code[registered_num].converted_color,
&code[i].converted_color,
sizeof(code[registered_num].converted_color)) == 0){
goto try_again;
}
}
//出力画像に変換後の色を代入
imageout->data[h][w] = code[registered_num].converted_color;
registered_num++;
searched_out:
;
}
}
fwrite(code, sizeof(angou), registered_num, fp);//鍵ファイルに変換情報を記録
WriteBmp(file_out_name, imageout);
//後処理
fclose(fp);
//free(file_out_name);
/*free(key_out_file);*/ free(buf);
free(code);
return true;
}
