From 003183d3fdda98a94844c1395ab626e120f07fbe Mon Sep 17 00:00:00 2001
From: julienChemillier <chemillier.julien@gmail.com>
Date: Sun, 14 May 2023 19:00:40 +0200
Subject: [PATCH] Add VGG16 architecture

---
 src/cnn/creation.c         | 32 ++++++++++++++++++++++++++++++++
 src/cnn/include/creation.h | 10 ++++++++--
 2 files changed, 40 insertions(+), 2 deletions(-)

diff --git a/src/cnn/creation.c b/src/cnn/creation.c
index 112ce7b..53728aa 100644
--- a/src/cnn/creation.c
+++ b/src/cnn/creation.c
@@ -62,6 +62,38 @@ Network* create_network_alexnet(float learning_rate, int dropout, int activation
     return network;
 }
 
+Network* create_network_VGG16(float learning_rate, int dropout, int activation, int initialisation, int size_output) {
+    Network* network = create_network(23, learning_rate, dropout, initialisation, 256, 3);
+    add_convolution(network, 3, 64, 1, 0, activation); // Conv3-64
+    add_convolution(network, 3, 64, 1, 0, activation); // Conv3-64
+    add_average_pooling(network, 2, 2, 0); // Max Pool
+
+    add_convolution(network, 3, 128, 1, 0, activation); // Conv3-128
+    add_convolution(network, 1, 128, 1, 0, activation); // Conv1-128
+    add_average_pooling(network, 2, 2, 0); // Max Pool
+
+    add_convolution(network, 3, 256, 1, 0, activation); // Conv3-256
+    add_convolution(network, 3, 256, 1, 0, activation); // Conv3-256
+    add_convolution(network, 1, 256, 1, 0, activation); // Conv1-256
+    add_average_pooling(network, 2, 2, 0); // Max Pool
+
+    add_convolution(network, 3, 512, 1, 0, activation); // Conv3-512
+    add_convolution(network, 3, 512, 1, 0, activation); // Conv3-512
+    add_convolution(network, 1, 512, 1, 0, activation); // Conv1-512
+    add_average_pooling(network, 2, 2, 0); // Max Pool
+
+    add_convolution(network, 3, 512, 1, 0, activation); // Conv3-512
+    add_convolution(network, 3, 512, 1, 0, activation); // Conv3-512
+    add_convolution(network, 1, 512, 1, 0, activation); // Conv1-512
+    add_average_pooling(network, 2, 2, 0); // Max Pool
+
+    add_dense_linearisation(network, 2048, activation);
+    add_dense(network, 2048, activation);
+    add_dense(network, 256, activation);
+    add_dense(network, size_output, SOFTMAX);
+    return network;
+}
+
 Network* create_simple_one(float learning_rate, int dropout, int activation, int initialisation, int input_width, int input_depth) {
     Network* network = create_network(3, learning_rate, dropout, initialisation, input_width, input_depth);
     add_dense_linearisation(network, 80, activation);
diff --git a/src/cnn/include/creation.h b/src/cnn/include/creation.h
index e55f6d0..0c1bca1 100644
--- a/src/cnn/include/creation.h
+++ b/src/cnn/include/creation.h
@@ -15,11 +15,17 @@ Network* create_network(int max_size, float learning_rate, int dropout, int init
 Network* create_network_lenet5(float learning_rate, int dropout, int activation, int initialisation, int input_width, int input_depth);
 
 /*
-* Renvoie un réseau suivante l'architecture AlexNet
-* C'est à dire une entrée de 3x227x227 et une sortie de taille 'size_output'
+* Renvoie un réseau suivant l'architecture AlexNet
+* C'est à dire en entrée 3x227x227 et une sortie de taille 'size_output'
 */
 Network* create_network_alexnet(float learning_rate, int dropout, int activation, int initialisation, int size_output);
 
+/*
+* Renvoie un réseau suivant l'architecture VGG16 modifiée pour prendre en entrée 3x256x256
+* et une sortie de taille 'size_output'
+*/
+Network* create_network_VGG16(float learning_rate, int dropout, int activation, int initialisation, int size_output);
+
 /*
 * Renvoie un réseau sans convolution, similaire à celui utilisé dans src/dense
 */