int main(int argc, const char * argv[]) {
const char* imageFileName;
void* imageHandle;
void* networkHandle;
float* predictions;
int predictionsLength;
char** predictionsLabels;
int predictionsLabelsLength;
int index;
if (argc < 2) {
imageFileName = "lena.png";
} else {
imageFileName = argv[1];
}
const char* networkFileName;
if (argc < 3) {
networkFileName = NETWORK_FILE_NAME;
} else {
networkFileName = argv[2];
}
networkHandle = jpcnn_create_network(networkFileName);
if (networkHandle == NULL) {
fprintf(stderr, "DeepBeliefSDK: Couldn't load network file '%s'\n", networkFileName);
return 1;
}
imageHandle = jpcnn_create_image_buffer_from_file(imageFileName);
if (imageHandle == NULL) {
fprintf(stderr, "DeepBeliefSDK: Couldn't load image file '%s'\n", imageFileName);
return 1;
}
jpcnn_classify_image(networkHandle, imageHandle, 0, 0, &predictions, &predictionsLength, &predictionsLabels, &predictionsLabelsLength);
jpcnn_destroy_image_buffer(imageHandle);
for (index = 0; index < predictionsLength; index += 1) {
float predictionValue;
char* label;
predictionValue = predictions[index];
if (predictionValue < 0.01f) {
continue;
}
label = predictionsLabels[index];
fprintf(stdout, "%f\t%s\n", predictionValue, label);
}
jpcnn_destroy_network(networkHandle);
return 0;
}
int main(int argc, const char * argv[]) {
float* predictions;
int predictionsLength;
char** predictionsLabels;
int predictionsLabelsLength;
if (argc!=5) {
fprintf(stderr,"%s network_filename layer svm_filename img_filename\n",argv[0]);
exit(1);
}
const char * networkFileName=argv[1];
int layer = atoi(argv[2]);
const char * predictorFileName=argv[3];
const char * imageFileName=argv[4];
void * networkHandle = jpcnn_create_network(networkFileName);
if (networkHandle == NULL) {
fprintf(stderr, "DeepBeliefSDK: Couldn't load network file '%s'\n", networkFileName);
return 1;
}
void * predictor=NULL;
if (strcmp(predictorFileName,"-")!=0) {
predictor = jpcnn_load_predictor(predictorFileName);
if (predictor==NULL) {
fprintf(stderr,"Failed to load predictor\n");
return 1;
}
}
int i=0;
for (i=0; i<1; i++) {
void * imageHandle = jpcnn_create_image_buffer_from_file(imageFileName);
if (imageHandle == NULL) {
fprintf(stderr, "DeepBeliefSDK: Couldn't load image file '%s'\n", imageFileName);
return 1;
}
jpcnn_classify_image(networkHandle, imageHandle, 0, layer, &predictions, &predictionsLength, &predictionsLabels, &predictionsLabelsLength);
if (strcmp(predictorFileName,"-")!=0) {
float pred = jpcnn_predict(predictor, predictions, predictionsLength);
fprintf(stdout,"%f\n",pred);
} else {
int index;
for (index = 0; index < predictionsLength; index += 1) {
float predictionValue;
char* label = predictionsLabels[index];
predictionValue = predictions[index];
fprintf(stdout, "%d\t%f\t%s\n", index, predictionValue, label);
}
}
jpcnn_destroy_image_buffer(imageHandle);
}
jpcnn_destroy_predictor(predictor);
/*for (index = 0; index < predictionsLength; index += 1) {
float predictionValue;
char* label = predictionsLabels[index];
predictionValue = predictions[index];
fprintf(stdout, "%d\t%f\t%s\n", index, predictionValue, label);
}*/
jpcnn_destroy_network(networkHandle);
return 0;
}
ConvNet::~ConvNet()
{
jpcnn_destroy_network(net_);
}