From e584dfc79115092103c24a0ab046b249f124c4c1 Mon Sep 17 00:00:00 2001
From: augustin64 <augustin.lucas64@gmail.com>
Date: Wed, 30 Nov 2022 10:21:56 +0100
Subject: [PATCH] Add test-network option implementation

---
 src/cnn/test_network.c | 85 +++++++++++++++++++++++++++++++++++++++++-
 1 file changed, 84 insertions(+), 1 deletion(-)

diff --git a/src/cnn/test_network.c b/src/cnn/test_network.c
index b51ad75..70b778b 100644
--- a/src/cnn/test_network.c
+++ b/src/cnn/test_network.c
@@ -9,8 +9,91 @@
 #include "include/free.h"
 #include "include/cnn.h"
 
-void test_network(int dataset_type, char* modele, char* images_file, char* labels_file, char* data_dir, bool preview_fails) {
 
+void test_network_mnist(Network* network, char* images_file, char* labels_file, bool preview_fails) {
+    (void)preview_fails; // Inutilisé pour le moment
+    int width, height; // Dimensions des images
+    int nb_elem; // Nombre d'éléments
+    int maxi; // Catégorie reconnue
+
+    int accuracy = 0; // Nombre d'images reconnues
+
+    // Load image
+    int* mnist_parameters = read_mnist_images_parameters(images_file);
+    
+    int*** images = read_mnist_images(images_file);
+    unsigned int* labels = read_mnist_labels(labels_file);
+    
+    nb_elem = mnist_parameters[0];
+
+    width = mnist_parameters[1];
+    height = mnist_parameters[2];
+    free(mnist_parameters);
+
+    // Load image in the first layer of the Network
+    for (int i=0; i < nb_elem; i++) {
+        if(i %(nb_elem/100) == 0) {
+            printf("Avancement: %.0f%%\r",  100*i/(float)nb_elem);
+            fflush(stdout);
+        }
+        write_image_in_network_32(images[i], height, width, network->input[0][0]);
+        forward_propagation(network);
+        maxi = indice_max(network->input[network->size-1][0][0], 10);
+
+        if (maxi == (int)labels[i]) {
+            accuracy++;
+        }
+
+        for (int j=0; j < height; j++) {
+            free(images[i][j]);
+        }
+        free(images[i]);
+    }
+    free(images);
+    printf("%d Images. Taux de réussite: %.2f%%\n", nb_elem, 100*accuracy/(float)nb_elem);
+}
+
+
+void test_network_jpg(Network* network, char* data_dir, bool preview_fails) {
+    (void)preview_fails; // Inutilisé pour le moment
+    jpegDataset* dataset = loadJpegDataset(data_dir);
+
+    int accuracy = 0;
+    int maxi;
+
+    for (int i=0; i < (int)dataset->numImages; i++) {
+        if(i %(dataset->numImages/100) == 0) {
+            printf("Avancement: %.1f%%\r",  1000*i/(float)dataset->numImages);
+            fflush(stdout);
+        }
+        write_image_in_network_260(dataset->images[i], dataset->height, dataset->height, network->input[0]);
+        forward_propagation(network);
+        maxi = indice_max(network->input[network->size-1][0][0], 50);
+
+        if (maxi == (int)dataset->labels[i]) {
+            accuracy++;
+        }
+
+        free(dataset->images[i]);
+    }
+
+    printf("%d Images. Taux de réussite: %.2f%%\n", dataset->numImages, 100*accuracy/(float)dataset->numImages);
+    free(dataset->images);
+    free(dataset->labels);
+    free(dataset);
+}
+
+
+void test_network(int dataset_type, char* modele, char* images_file, char* labels_file, char* data_dir, bool preview_fails) {
+    Network* network = read_network(modele);
+
+    if (dataset_type == 0) {
+        test_network_mnist(network, images_file, labels_file, preview_fails);
+    } else {
+        test_network_jpg(network, data_dir, preview_fails);
+    }
+
+    free_network(network);
 }