make sure that landmarks are in the face bounding box

Author: bahar3474

Face Quality Assessment.ipynb

@@ -19,9 +19,22 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 1,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "WARNING:tensorflow:From D:\\Almaatech\\face\\face-quality-metrics\\detection\\mtcnn\\detect_face.py:210: calling reduce_max (from tensorflow.python.ops.math_ops) with keep_dims is deprecated and will be removed in a future version.\n",
+      "Instructions for updating:\n",
+      "keep_dims is deprecated, use keepdims instead\n",
+      "WARNING:tensorflow:From D:\\Almaatech\\face\\face-quality-metrics\\detection\\mtcnn\\detect_face.py:212: calling reduce_sum (from tensorflow.python.ops.math_ops) with keep_dims is deprecated and will be removed in a future version.\n",
+      "Instructions for updating:\n",
+      "keep_dims is deprecated, use keepdims instead\n"
+     ]
+    }
+   ],
    "source": [
     "import tensorflow as tf\n",
     "from detection.mtcnn import detect_face\n",
@@ -32,7 +45,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 2,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -47,7 +60,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 3,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -69,15 +82,6 @@
     "# Illumination "
    ]
   },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "points"
-   ]
-  },
   {
    "cell_type": "code",
    "execution_count": null,
@@ -146,19 +150,22 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "# Facial symmetry"
+    "# Facial Symmetry"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 4,
    "metadata": {},
    "outputs": [],
    "source": [
     "from skimage.feature import hog\n",
     "\n",
     "def symmetry(img, landmark, bounding_box):\n",
-    "    x1, y1, x2, y2 = int(bounding_box[0]), int(bounding_box[1]), int(bounding_box[2]), int(bounding_box[3])\n",
+    "    x1, y1, x2, y2 = int(min(bounding_box[0], min(landmark[:5]))), \\\n",
+    "        int(min(bounding_box[1], min(landmark[5:]))), \\\n",
+    "        int(max(bounding_box[2], max(landmark[:5]))), \\\n",
+    "        int(max(bounding_box[3], max(landmark[5:])))\n",
     "    \n",
     "    landmark = np.array([[landmark[i], landmark[5 + i]] for i in  range(5)], np.int32).reshape((-1,1,2))\n",
     "    contour = landmark[:, 0] - [[x1, y1]]\n",
@@ -181,9 +188,28 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 5,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "c:\\users\\bahar\\appdata\\local\\programs\\python\\python35\\lib\\site-packages\\skimage\\feature\\_hog.py:150: skimage_deprecation: Default value of `block_norm`==`L1` is deprecated and will be changed to `L2-Hys` in v0.15. To supress this message specify explicitly the normalization method.\n",
+      "  skimage_deprecation)\n"
+     ]
+    },
+    {
+     "data": {
+      "text/plain": [
+       "0.02465394288301468"
+      ]
+     },
+     "execution_count": 5,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
    "source": [
     "symmetry(img, points, bounding_boxes[0])"
    ]
@@ -197,7 +223,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 6,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -216,12 +242,30 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 7,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "1"
+      ]
+     },
+     "execution_count": 7,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
    "source": [
     "size(img)"
    ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
   }
  ],
  "metadata": {