From 734d71b9bc370d1fd812f900f9892db8ffa2e7d1 Mon Sep 17 00:00:00 2001
From: Mohcen23 <mouhcen.chouireb@ensia.edu.dz>
Date: Sun, 19 Feb 2023 20:37:08 +0100
Subject: [PATCH] updated in a pythonic manner the parts 5.2 and 6.2

---
 FaceDetection.ipynb | 68 +++++++++++++++++++++++++++++++++++++++++++++
 1 file changed, 68 insertions(+)

diff --git a/FaceDetection.ipynb b/FaceDetection.ipynb
index 8fd179ea..412ec8af 100644
--- a/FaceDetection.ipynb
+++ b/FaceDetection.ipynb
@@ -633,6 +633,41 @@
     "val_images = val_images.map(lambda x: x/255)"
    ]
   },
+  {
+   "attachments": {},
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "#### -> An alternative manner to do so :"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "images = list()\n",
+    "\n",
+    "for folder in ['train', 'test', 'val']:\n",
+    "    specific_images = tf.data.Dataset.list_files(f'aug_data\\\\{folder}\\\\images\\\\*.jpg', shuffle=False)\n",
+    "    specific_images = specific_images.map(load_image)\n",
+    "    specific_images = specific_images.map(lambda x: tf.image.resize(x, (120,120)))\n",
+    "    specific_images = specific_images.map(lambda x: x/255)\n",
+    "    images.append(specific_images)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "train_images = images[0]\n",
+    "test_images = images[1]\n",
+    "val_images = images[2]"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
@@ -716,6 +751,39 @@
     "val_labels = val_labels.map(lambda x: tf.py_function(load_labels, [x], [tf.uint8, tf.float16]))"
    ]
   },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "#### -> An alternative manner to do so:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "labels = list()\n",
+    "\n",
+    "for folder in ['train', 'test', 'val']:\n",
+    "    specific_labels = tf.data.Dataset.list_files(f'aug_data\\\\{folder}\\\\labels\\\\*.json', shuffle=False)\n",
+    "    # loading the labels\n",
+    "    specific_labels = specific_labels.map(lambda x: tf.py_function(load_labels, [x], [tf.uint8, tf.float16 ]))\n",
+    "    labels.append(specific_labels)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "train_labels = labels[0]\n",
+    "test_labels = labels[1]\n",
+    "val_labels = labels[2]"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,