From c13dba86b2dbe581353b72602d7fa6e40991964c Mon Sep 17 00:00:00 2001
From: natanielruiz <nataniel777@hotmail.com>
Date: 星期三, 27 九月 2017 04:11:23 +0800
Subject: [PATCH] next

---
 practice/.ipynb_checkpoints/load_AFLW-Copy1-checkpoint.ipynb |   55 ++++++++++++++++++++++++++++++++++++++++++-------------
 1 files changed, 42 insertions(+), 13 deletions(-)

diff --git a/practice/.ipynb_checkpoints/load_AFLW-Copy1-checkpoint.ipynb b/practice/.ipynb_checkpoints/load_AFLW-Copy1-checkpoint.ipynb
index edac84d..856fbb4 100644
--- a/practice/.ipynb_checkpoints/load_AFLW-Copy1-checkpoint.ipynb
+++ b/practice/.ipynb_checkpoints/load_AFLW-Copy1-checkpoint.ipynb
@@ -31,16 +31,24 @@
    "source": [
     "#Change this paths according to your directories\n",
     "images_path = \"/Data/nruiz9/data/facial_landmarks/AFLW/aflw/data/flickr/\"\n",
-    "storing_path = \"/Data/nruiz9/data/facial_landmarks/AFLW/aflw_cropped/\""
+    "storing_path = \"/Data/nruiz9/data/facial_landmarks/AFLW/aflw_cropped_loose/\""
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 3,
+   "execution_count": 4,
    "metadata": {
     "collapsed": false
    },
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Done\n"
+     ]
+    }
+   ],
    "source": [
     "#Image counter\n",
     "counter = 1\n",
@@ -92,17 +100,19 @@
     "        face_h = row[8]\n",
     "\n",
     "        #Error correction\n",
-    "        if(face_x < 0): face_x = 0\n",
-    "        if(face_y < 0): face_y = 0\n",
-    "        if(face_w > image_w): \n",
-    "            face_w = image_w\n",
-    "            face_h = image_w\n",
-    "        if(face_h > image_h): \n",
-    "            face_h = image_h\n",
-    "            face_w = image_h\n",
-    "\n",
+    "        k = 0.35\n",
+    "        x_min = face_x - face_w * k * 0.6\n",
+    "        x_max = face_x + face_w + face_w * k * 0.6\n",
+    "        y_min = face_y - face_h * k * 2\n",
+    "        y_max = face_y + face_h + face_h * k * 0.6\n",
+    "        \n",
+    "        x_min = int(max(0, x_min))\n",
+    "        x_max = int(min(image_w, x_max))\n",
+    "        y_min = int(max(0, y_min))\n",
+    "        y_max = int(min(image_h, y_max))\n",
+    "        \n",
     "        #Crop the face from the image\n",
-    "        image_cropped = np.copy(image[face_y:face_y+face_h, face_x:face_x+face_w])\n",
+    "        image_cropped = np.copy(image[y_min:y_max, x_min:x_max])\n",
     "        #Uncomment the lines below if you want to rescale the image to a particular size\n",
     "        to_size = 240\n",
     "        image_cropped = cv2.resize(image_cropped, (to_size,to_size), interpolation = cv2.INTER_AREA)\n",
@@ -134,6 +144,25 @@
   },
   {
    "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "test\n"
+     ]
+    }
+   ],
+   "source": [
+    "print 'test'"
+   ]
+  },
+  {
+   "cell_type": "code",
    "execution_count": null,
    "metadata": {
     "collapsed": true

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