diff --git a/src/cnn/export.c b/src/cnn/export.c
index 5a2d166..e95b426 100644
--- a/src/cnn/export.c
+++ b/src/cnn/export.c
@@ -1,15 +1,32 @@
+#include <stdbool.h>
 #include <stdlib.h>
 #include <string.h>
 #include <stdio.h>
+#include <math.h>
 
-#include "include/free.h"
-#include "include/struct.h"
-#include "../include/colors.h"
+#include "include/backpropagation.h"
 #include "include/neuron_io.h"
+#include "../include/colors.h"
+#include "../include/mnist.h"
+#include "include/struct.h"
+#include "include/jpeg.h"
+#include "include/free.h"
+#include "include/cnn.h"
 
 
 void help(char* call) {
-    printf("Usage: %s ( print-poids-kernel-cnn ) [OPTIONS]\n\n", call);
+    printf("Usage: %s ( print-poids-kernel-cnn | visual-propagation ) [OPTIONS]\n\n", call);
+    printf("OPTIONS:\n");
+    printf("\tprint-poids-kernel-cnn\n");
+    printf("\t\t--modele | -m [FILENAME]\tFichier contenant le réseau entraîné\n");
+    printf("\tvisual-propagation\n");
+    printf("\t\t--modele | -m [FILENAME]\tFichier contenant le réseau entraîné\n");
+    printf("\t\t--images | -i [FILENAME]\tFichier contenant les images.\n");
+    printf("\t\t--numero | -n [numero]\tNuméro de l'image dont la propagation veut être visualisée\n");
+    printf("\t\t--out    | -o [BASE_FILENAME]\tLes images seront stockées dans ${out}_layer-${numéro de couche}_feature-${kernel_numero}.jpeg\n");
+    
+    printf("\n");
+    printf_warning("Seul les datasets de type MNIST sont pris en charge pour le moment\n");
 }
 
 
@@ -65,6 +82,87 @@ void print_poids_ker_cnn(char* modele) {
 }
 
 
+void write_image(float** data, int width, char* base_filename, int layer_id, int kernel_id) {
+    int filename_length = strlen(base_filename) + (int)log10(layer_id+1)+1 + (int)log10(kernel_id+1)+1 + 21;
+    char* filename = (char*)malloc(sizeof(char)*filename_length);
+
+    sprintf(filename, "%s_layer-%d_feature-%d.jpeg", base_filename, layer_id, kernel_id);
+
+    
+    imgRawImage* image = (imgRawImage*)malloc(sizeof(imgRawImage));
+
+    image->numComponents = 3;
+    image->width = width;
+    image->height = width;
+    image->lpData = (unsigned char*)malloc(sizeof(unsigned char)*width*width*3);
+
+    for (int i=0; i < width; i++) {
+        for (int j=0; j < width; j++) {
+            float color = fmax(fmin(data[i][j], 1.), 0.)*255;
+
+            image->lpData[(i*width+j)*3] = color;
+            image->lpData[(i*width+j)*3 + 1] = color;
+            image->lpData[(i*width+j)*3 + 2] = color;
+        }
+    }
+
+    storeJpegImageFile(image, filename);
+
+    free(image->lpData);
+    free(image);
+    free(filename);
+}
+
+
+void visual_propagation(char* modele_file, char* images_file, char* out_base, int numero) {
+    Network* network = read_network(modele_file);
+
+    int* mnist_parameters = read_mnist_images_parameters(images_file);
+    int*** images = read_mnist_images(images_file);
+
+    int nb_elem = mnist_parameters[0];
+
+    int width = mnist_parameters[1];
+    int height = mnist_parameters[2];
+    free(mnist_parameters);
+
+    if (numero < 0 || numero >= nb_elem) {
+        printf_error("Numéro d'image spécifié invalide.");
+        printf(" Le fichier contient %d images.\n", nb_elem);
+        exit(1);
+    }
+
+    // Forward propagation
+    write_image_in_network_32(images[numero], height, width, network->input[0][0], false);
+    forward_propagation(network);
+
+    for (int i=0; i < network->size-1; i++) {
+        if (i == 0) {
+            write_image(network->input[0][0], width, out_base, 0, 0);
+        } else {
+            if ((!network->kernel[i]->cnn)&&(!network->kernel[i]->nn)) {
+                for (int j=0; j < network->depth[i]; j++) {
+                    write_image(network->input[i][j], network->width[i], out_base, i, j);
+                }
+            } else if (!network->kernel[i]->cnn) {
+                // Couche de type NN, on n'affiche rien
+            } else {
+                write_image(network->input[i][0], network->width[i], out_base, i, 0);
+            }
+        }
+    }
+
+    free_network(network);
+    for (int i=0; i < nb_elem; i++) {
+        for (int j=0; j < width; j++) {
+            free(images[i][j]);
+        }
+        free(images[i]);
+    }
+    free(images);
+}
+
+
 
 int main(int argc, char* argv[]) {
     if (argc < 2) {
@@ -92,6 +190,50 @@ int main(int argc, char* argv[]) {
         print_poids_ker_cnn(modele);
         return 0;
     }
+    if (! strcmp(argv[1], "visual-propagation")) {
+        char* modele = NULL; // Fichier contenant le modèle
+        char* images = NULL; // Dossier contenant les images
+        char* out_base = NULL; // Préfixe du nom de fichier de sortie
+        int numero = -1; // Numéro de l'image dans le dataset
+        int i = 2;
+        while (i < argc) {
+            if ((! strcmp(argv[i], "--modele"))||(! strcmp(argv[i], "-m"))) {
+                modele = argv[i+1];
+                i += 2;
+            } else if ((! strcmp(argv[i], "--images"))||(! strcmp(argv[i], "-i"))) {
+                images = argv[i+1];
+                i += 2;
+            } else if ((! strcmp(argv[i], "--out"))||(! strcmp(argv[i], "-o"))) {
+                out_base = argv[i+1];
+                i += 2;
+            } else if ((! strcmp(argv[i], "--numero"))||(! strcmp(argv[i], "-n"))) {
+                numero = strtol(argv[i+1], NULL, 10);
+                i += 2;
+            } else {
+                printf_warning("Option choisie inconnue: ");
+                printf("%s\n", argv[i]);
+                i++;
+            }
+        }
+        if (!modele) {
+            printf_error("Pas de modèle à utiliser spécifié.\n");
+            return 1;
+        }
+        if (!images) {
+            printf_error("Pas de fichier d'images spécifié.\n");
+            return 1;
+        }
+        if (!out_base) {
+            printf_error("Pas de fichier de sortie spécifié.\n");
+            return 1;
+        }
+        if (numero == -1) {
+            printf_error("Pas de numéro d'image spécifié.\n");
+            return 1;
+        }
+        visual_propagation(modele, images, out_base, numero);
+        return 0;
+    }
     printf_error("Option choisie non reconnue: ");
     printf("%s\n", argv[1]);
     help(argv[0]);
diff --git a/src/cnn/include/jpeg.h b/src/cnn/include/jpeg.h
index 42120d2..166215b 100644
--- a/src/cnn/include/jpeg.h
+++ b/src/cnn/include/jpeg.h
@@ -33,6 +33,11 @@ typedef struct jpegDataset {
 */
 imgRawImage* loadJpegImageFile(char* lpFilename);
 
+/*
+* Write a JPEG image to lpFilename
+*/
+int storeJpegImageFile(struct imgRawImage* lpImage, char* lpFilename);
+
 /*
 * Load a complete dataset from its path
 */
diff --git a/src/cnn/include/struct.h b/src/cnn/include/struct.h
index 1f04c43..2e04481 100644
--- a/src/cnn/include/struct.h
+++ b/src/cnn/include/struct.h
@@ -15,17 +15,19 @@ typedef struct Kernel_cnn {
     int k_size; // k_size = dim_input - dim_output + 1
     int rows; // Depth de l'input
     int columns; // Depth de l'output
+
     float*** bias; // bias[columns][dim_output][dim_output]
     float*** d_bias; // d_bias[columns][dim_output][dim_output]
     #ifdef ADAM_CNN_BIAS
-    float*** s_d_bias; // s_d_bias[columns][dim_output][dim_output]
-    float*** v_d_bias; // v_d_bias[columns][dim_output][dim_output]
+        float*** s_d_bias; // s_d_bias[columns][dim_output][dim_output]
+        float*** v_d_bias; // v_d_bias[columns][dim_output][dim_output]
     #endif
+
     float**** weights; // weights[rows][columns][k_size][k_size]
     float**** d_weights; // d_weights[rows][columns][k_size][k_size]
     #ifdef ADAM_CNN_WEIGHTS
-    float**** s_d_weights; // s_d_weights[rows][columns][k_size][k_size]
-    float**** v_d_weights; // v_d_weights[rows][columns][k_size][k_size]
+        float**** s_d_weights; // s_d_weights[rows][columns][k_size][k_size]
+        float**** v_d_weights; // v_d_weights[rows][columns][k_size][k_size]
     #endif
 } Kernel_cnn;
 
@@ -33,23 +35,26 @@ typedef struct Kernel_nn {
     // Noyau ayant une couche vectorielle en sortie
     int size_input; // Nombre d'éléments en entrée
     int size_output; // Nombre d'éléments en sortie
+
     float* bias; // bias[size_output]
     float* d_bias; // d_bias[size_output]
     #ifdef ADAM_DENSE_BIAS
-    float* s_d_bias; // s_d_bias[size_output]
-    float* v_d_bias; // v_d_bias[size_output]
+        float* s_d_bias; // s_d_bias[size_output]
+        float* v_d_bias; // v_d_bias[size_output]
     #endif
+
     float** weights; // weight[size_input][size_output]
     float** d_weights; // d_weights[size_input][size_output]
     #ifdef ADAM_DENSE_WEIGHTS
-    float** s_d_weights; // s_d_weights[size_input][size_output]
-    float** v_d_weights; // v_d_weights[size_input][size_output]
+        float** s_d_weights; // s_d_weights[size_input][size_output]
+        float** v_d_weights; // v_d_weights[size_input][size_output]
     #endif
 } Kernel_nn;
 
 typedef struct Kernel {
     Kernel_cnn* cnn; // NULL si ce n'est pas un cnn
     Kernel_nn* nn; // NULL si ce n'est pas un nn
+
     int activation; // Id de la fonction d'activation et -Id de sa dérivée
     int linearisation; // 1 si c'est la linéarisation d'une couche, 0 sinon
     int pooling; // 0 si pas pooling, 1 si average_pooling, 2 si max_pooling
@@ -60,10 +65,13 @@ typedef struct Network{
     int dropout; // Probabilité d'abandon d'un neurone dans [0, 100] (entiers)
     float learning_rate; // Taux d'apprentissage du réseau
     int initialisation; // Id du type d'initialisation
+
     int max_size; // Taille du tableau contenant le réseau
     int size; // Taille actuelle du réseau (size ≤ max_size)
+
     int* width; // width[size]
     int* depth; // depth[size]
+    
     Kernel** kernel; // kernel[size], contient tous les kernels
     float**** input_z; // Tableau de toutes les couches du réseau input_z[size][couche->depth][couche->width][couche->width]
     float**** input; // input[i] = f(input_z[i]) où f est la fonction d'activation de la couche i
diff --git a/src/cnn/jpeg.c b/src/cnn/jpeg.c
index cbcf7e7..723c39f 100644
--- a/src/cnn/jpeg.c
+++ b/src/cnn/jpeg.c
@@ -74,6 +74,52 @@ imgRawImage* loadJpegImageFile(char* lpFilename) {
     return lpNewImage;
 }
 
+
+int storeJpegImageFile(imgRawImage* lpImage, char* lpFilename) {
+	struct jpeg_compress_struct info;
+	struct jpeg_error_mgr err;
+
+	unsigned char* lpRowBuffer[1];
+
+	FILE* fHandle;
+
+	fHandle = fopen(lpFilename, "wb");
+	if(fHandle == NULL) {
+		#ifdef DEBUG
+			fprintf(stderr, "%s:%u Failed to open output file %s\n", __FILE__, __LINE__, lpFilename);
+		#endif
+		return 1;
+	}
+
+	info.err = jpeg_std_error(&err);
+	jpeg_create_compress(&info);
+
+	jpeg_stdio_dest(&info, fHandle);
+
+	info.image_width = lpImage->width;
+	info.image_height = lpImage->height;
+	info.input_components = 3;
+	info.in_color_space = JCS_RGB;
+
+	jpeg_set_defaults(&info);
+	jpeg_set_quality(&info, 100, TRUE);
+
+	jpeg_start_compress(&info, TRUE);
+
+	/* Write every scanline ... */
+	while(info.next_scanline < info.image_height) {
+		lpRowBuffer[0] = &(lpImage->lpData[info.next_scanline * (lpImage->width * 3)]);
+		jpeg_write_scanlines(&info, lpRowBuffer, 1);
+	}
+
+	jpeg_finish_compress(&info);
+	fclose(fHandle);
+
+	jpeg_destroy_compress(&info);
+	return 0;
+}
+
+
 jpegDataset* loadJpegDataset(char* folderPath) {
     jpegDataset* dataset = (jpegDataset*)malloc(sizeof(jpegDataset));
     imgRawImage* image;