mirror of
https://github.com/augustin64/projet-tipe
synced 2025-01-23 23:26:25 +01:00
Changes in name of variables
This commit is contained in:
parent
93bad4e59b
commit
3046b502bd
@ -75,10 +75,10 @@ void train(int batches, int layers, int neurons, char* recovery, char* image_fil
|
||||
Network* network;
|
||||
|
||||
//int* repartition = malloc(sizeof(int)*layers);
|
||||
int nb_neurons_der = 10;
|
||||
int repartition[2] = {784, nb_neurons_der};
|
||||
int nb_neurons_last = 10;
|
||||
int repartition[2] = {784, nb_neurons_last};
|
||||
|
||||
float* sortie = malloc(sizeof(float)*nb_neurons_der);
|
||||
float* output = malloc(sizeof(float)*nb_neurons_last);
|
||||
int* desired_output;
|
||||
float accuracy;
|
||||
float loss;
|
||||
@ -121,10 +121,10 @@ void train(int batches, int layers, int neurons, char* recovery, char* image_fil
|
||||
forward_propagation(network);
|
||||
backward_propagation(network, desired_output);
|
||||
|
||||
for (int k=0; k < nb_neurons_der; k++) {
|
||||
sortie[k] = der_layer->neurons[k]->z;
|
||||
for (int k=0; k < nb_neurons_last; k++) {
|
||||
output[k] = der_layer->neurons[k]->z;
|
||||
}
|
||||
if (indice_max(sortie, nb_neurons_der) == labels[j]) {
|
||||
if (indice_max(output, nb_neurons_last) == labels[j]) {
|
||||
accuracy += 1. / (float)nb_images;
|
||||
}
|
||||
loss += loss_computing(network, labels[j]) / (float)nb_images;
|
||||
@ -144,9 +144,9 @@ void train(int batches, int layers, int neurons, char* recovery, char* image_fil
|
||||
deletion_of_network(network);
|
||||
}
|
||||
|
||||
float** recognize(char* modele, char* entree) {
|
||||
Network* network = read_network(modele);
|
||||
Layer* derniere_layer = network->layers[network->nb_layers-1];
|
||||
float** recognize(char* model, char* entree) {
|
||||
Network* network = read_network(model);
|
||||
Layer* last_layer = network->layers[network->nb_layers-1];
|
||||
|
||||
int* parameters = read_mnist_images_parameters(entree);
|
||||
int nb_images = parameters[0];
|
||||
@ -157,13 +157,13 @@ float** recognize(char* modele, char* entree) {
|
||||
float** results = malloc(sizeof(float*)*nb_images);
|
||||
|
||||
for (int i=0; i < nb_images; i++) {
|
||||
results[i] = malloc(sizeof(float)*derniere_layer->nb_neurons);
|
||||
results[i] = malloc(sizeof(float)*last_layer->nb_neurons);
|
||||
|
||||
write_image_in_network(images[i], network, height, width);
|
||||
forward_propagation(network);
|
||||
|
||||
for (int j=0; j < derniere_layer->nb_neurons; j++) {
|
||||
results[i][j] = derniere_layer->neurons[j]->z;
|
||||
for (int j=0; j < last_layer->nb_neurons; j++) {
|
||||
results[i][j] = last_layer->neurons[j]->z;
|
||||
}
|
||||
}
|
||||
deletion_of_network(network);
|
||||
@ -171,8 +171,8 @@ float** recognize(char* modele, char* entree) {
|
||||
return results;
|
||||
}
|
||||
|
||||
void print_recognize(char* modele, char* entree, char* sortie) {
|
||||
Network* network = read_network(modele);
|
||||
void print_recognize(char* model, char* entree, char* output) {
|
||||
Network* network = read_network(model);
|
||||
int nb_der_layer = network->layers[network->nb_layers-1]->nb_neurons;
|
||||
|
||||
deletion_of_network(network);
|
||||
@ -180,28 +180,28 @@ void print_recognize(char* modele, char* entree, char* sortie) {
|
||||
int* parameters = read_mnist_images_parameters(entree);
|
||||
int nb_images = parameters[0];
|
||||
|
||||
float** resultats = recognize(modele, entree);
|
||||
float** results = recognize(model, entree);
|
||||
|
||||
if (! strcmp(sortie, "json")) {
|
||||
if (! strcmp(output, "json")) {
|
||||
printf("{\n");
|
||||
}
|
||||
for (int i=0; i < nb_images; i++) {
|
||||
if (! strcmp(sortie, "text"))
|
||||
if (! strcmp(output, "text"))
|
||||
printf("Image %d\n", i);
|
||||
else
|
||||
printf("\"%d\" : [", i);
|
||||
|
||||
for (int j=0; j < nb_der_layer; j++) {
|
||||
if (! strcmp(sortie, "json")) {
|
||||
printf("%f", resultats[i][j]);
|
||||
if (! strcmp(output, "json")) {
|
||||
printf("%f", results[i][j]);
|
||||
|
||||
if (j+1 < nb_der_layer) {
|
||||
printf(", ");
|
||||
}
|
||||
} else
|
||||
printf("Probabilité %d: %f\n", j, resultats[i][j]);
|
||||
printf("Probabilité %d: %f\n", j, results[i][j]);
|
||||
}
|
||||
if (! strcmp(sortie, "json")) {
|
||||
if (! strcmp(output, "json")) {
|
||||
if (i+1 < nb_images) {
|
||||
printf("],\n");
|
||||
} else {
|
||||
@ -209,13 +209,13 @@ void print_recognize(char* modele, char* entree, char* sortie) {
|
||||
}
|
||||
}
|
||||
}
|
||||
if (! strcmp(sortie, "json"))
|
||||
if (! strcmp(output, "json"))
|
||||
printf("}\n");
|
||||
|
||||
}
|
||||
|
||||
void test(char* modele, char* fichier_images, char* fichier_labels, bool preview_fails) {
|
||||
Network* network = read_network(modele);
|
||||
void test(char* model, char* fichier_images, char* fichier_labels, bool preview_fails) {
|
||||
Network* network = read_network(model);
|
||||
int nb_der_layer = network->layers[network->nb_layers-1]->nb_neurons;
|
||||
|
||||
deletion_of_network(network);
|
||||
@ -226,16 +226,16 @@ void test(char* modele, char* fichier_images, char* fichier_labels, bool preview
|
||||
int height = parameters[2];
|
||||
int*** images = read_mnist_images(fichier_images);
|
||||
|
||||
float** resultats = recognize(modele, fichier_images);
|
||||
float** results = recognize(model, fichier_images);
|
||||
unsigned int* labels = read_mnist_labels(fichier_labels);
|
||||
float accuracy;
|
||||
|
||||
for (int i=0; i < nb_images; i++) {
|
||||
if (indice_max(resultats[i], nb_der_layer) == labels[i]) {
|
||||
if (indice_max(results[i], nb_der_layer) == labels[i]) {
|
||||
accuracy += 1. / (float)nb_images;
|
||||
} else if (preview_fails) {
|
||||
printf("--- Image %d, %d --- Prévision: %d ---\n", i, labels[i], indice_max(resultats[i], nb_der_layer));
|
||||
print_image(width, height, images[i], resultats[i]);
|
||||
printf("--- Image %d, %d --- Prévision: %d ---\n", i, labels[i], indice_max(results[i], nb_der_layer));
|
||||
print_image(width, height, images[i], results[i]);
|
||||
}
|
||||
}
|
||||
printf("%d Images\tAccuracy: %0.1f%%\n", nb_images, accuracy*100);
|
||||
@ -304,7 +304,7 @@ int main(int argc, char* argv[]) {
|
||||
}
|
||||
if (! strcmp(argv[1], "recognize")) {
|
||||
char* in = NULL;
|
||||
char* modele = NULL;
|
||||
char* model = NULL;
|
||||
char* out = NULL;
|
||||
int i = 2;
|
||||
while(i < argc) {
|
||||
@ -312,7 +312,7 @@ int main(int argc, char* argv[]) {
|
||||
in = argv[i+1];
|
||||
i += 2;
|
||||
} else if ((! strcmp(argv[i], "--modele"))||(! strcmp(argv[i], "-m"))) {
|
||||
modele = argv[i+1];
|
||||
model = argv[i+1];
|
||||
i += 2;
|
||||
} else if ((! strcmp(argv[i], "--out"))||(! strcmp(argv[i], "-o"))) {
|
||||
out = argv[i+1];
|
||||
@ -326,19 +326,19 @@ int main(int argc, char* argv[]) {
|
||||
printf("Pas d'entrée spécifiée\n");
|
||||
exit(1);
|
||||
}
|
||||
if (! modele) {
|
||||
if (! model) {
|
||||
printf("Pas de modèle spécifié\n");
|
||||
exit(1);
|
||||
}
|
||||
if (! out) {
|
||||
out = "text";
|
||||
}
|
||||
print_recognize(modele, in, out);
|
||||
print_recognize(model, in, out);
|
||||
// Reconnaissance puis affichage des données sous le format spécifié
|
||||
exit(0);
|
||||
}
|
||||
if (! strcmp(argv[1], "test")) {
|
||||
char* modele = NULL;
|
||||
char* model = NULL;
|
||||
char* images = NULL;
|
||||
char* labels = NULL;
|
||||
bool preview_fails = false;
|
||||
@ -351,14 +351,14 @@ int main(int argc, char* argv[]) {
|
||||
labels = argv[i+1];
|
||||
i += 2;
|
||||
} else if ((! strcmp(argv[i], "--modele"))||(! strcmp(argv[i], "-m"))) {
|
||||
modele = argv[i+1];
|
||||
model = argv[i+1];
|
||||
i += 2;
|
||||
} else if ((! strcmp(argv[i], "--preview-fails"))||(! strcmp(argv[i], "-p"))) {
|
||||
preview_fails = true;
|
||||
i++;
|
||||
}
|
||||
}
|
||||
test(modele, images, labels, preview_fails);
|
||||
test(model, images, labels, preview_fails);
|
||||
exit(0);
|
||||
}
|
||||
printf("Option choisie non reconnue: %s\n", argv[1]);
|
||||
|
@ -15,16 +15,16 @@ int** read_image(unsigned int width, unsigned int height, FILE* ptr) {
|
||||
unsigned char buffer[width*height];
|
||||
int** image = (int**)malloc(sizeof(int*)*height);
|
||||
|
||||
size_t ligne_size = sizeof(int) * width;
|
||||
size_t line_size = sizeof(int) * width;
|
||||
|
||||
fread(buffer, sizeof(buffer), 1, ptr);
|
||||
|
||||
for (int i=0; i<height; i++) {
|
||||
int* ligne = (int*)malloc(ligne_size);
|
||||
int* line = (int*)malloc(line_size);
|
||||
for (int j=0; j<width; j++) {
|
||||
ligne[j] = (int)buffer[j+i*width];
|
||||
line[j] = (int)buffer[j+i*width];
|
||||
}
|
||||
image[i] = ligne;
|
||||
image[i] = line;
|
||||
}
|
||||
return image;
|
||||
}
|
||||
|
@ -96,7 +96,7 @@ Network* read_network(char* filename) {
|
||||
|
||||
|
||||
// Écrit un neurone dans le fichier pointé par *ptr
|
||||
void ecrire_neuron(Neuron* neuron, int weights, FILE *ptr) {
|
||||
void write_neuron(Neuron* neuron, int weights, FILE *ptr) {
|
||||
float buffer[weights+2];
|
||||
|
||||
buffer[1] = neuron->bias;
|
||||
@ -130,7 +130,7 @@ int write_network(char* filename, Network* network) {
|
||||
|
||||
for (int i=0; i < nb_layers; i++) {
|
||||
for (int j=0; j < nb_neurons[i]; j++) {
|
||||
ecrire_neuron(network->layers[i]->neurons[j], nb_neurons[i+1], ptr);
|
||||
write_neuron(network->layers[i]->neurons[j], nb_neurons[i+1], ptr);
|
||||
}
|
||||
}
|
||||
|
||||
|
@ -37,7 +37,7 @@ void print_bias(char* filename) {
|
||||
deletion_of_network(network);
|
||||
}
|
||||
|
||||
void print_poids(char* filename) {
|
||||
void print_weights(char* filename) {
|
||||
Network* network = read_network(filename);
|
||||
|
||||
for (int i=0; i < network->nb_layers -1; i++) {
|
||||
@ -140,7 +140,7 @@ int main(int argc, char* argv[]) {
|
||||
printf("Pas de fichier spécifié, utilisation de '.cache/reseau.bin'\n");
|
||||
filename = ".cache/reseau.bin";
|
||||
}
|
||||
print_poids(filename);
|
||||
print_weights(filename);
|
||||
exit(1);
|
||||
} else if (! strcmp(argv[1], "print-biais")) {
|
||||
char* filename = NULL;
|
||||
|
Loading…
Reference in New Issue
Block a user