Change the paths inside the notebook to relative folder paths

tutorials/notebooks/example_keras_effdet_lite0.ipynb

@@ -106,8 +106,8 @@
    "outputs": [],
    "source": [
     "import sys\n",
-    "sys.path.insert(0,\"/content/local_mct\")\n",
-    "!pip install -r /content/local_mct/requirements.txt\n",
+    "sys.path.insert(0,\"./local_mct\")\n",
+    "!pip install -r ./local_mct/requirements.txt\n",
     "from tutorials.resources.efficientdet import EfficientDetKeras"
    ],
    "metadata": {
@@ -133,10 +133,10 @@
    "outputs": [],
    "source": [
     "!wget -nc http://images.cocodataset.org/annotations/annotations_trainval2017.zip\n",
-    "!unzip -q -o annotations_trainval2017.zip -d /content/coco\n",
+    "!unzip -q -o annotations_trainval2017.zip -d ./coco\n",
     "!echo Done loading annotations\n",
     "!wget -nc http://images.cocodataset.org/zips/val2017.zip\n",
-    "!unzip -q -o val2017.zip -d /content/coco\n",
+    "!unzip -q -o val2017.zip -d ./coco\n",
     "!echo Done loading val2017 images"
    ],
    "metadata": {
@@ -213,7 +213,7 @@
     "        The DataLoader and evaluation object for calculating accuracy\n",
     "\n",
     "    \"\"\"\n",
-    "    root = '/content/coco'\n",
+    "    root = './coco'\n",
     "\n",
     "    args = dict(interpolation='bilinear', mean=None,\n",
     "                std=None, fill_color=None)\n",
@@ -299,7 +299,7 @@
     "\n",
     "model = EfficientDetKeras(config, pretrained_backbone=False).get_model([*config.image_size] + [3])\n",
     "\n",
-    "model.save('/content/model.keras')"
+    "model.save('./model.keras')"
    ],
    "metadata": {
     "collapsed": false
@@ -397,7 +397,7 @@
     "    target_kpi=kpi,\n",
     "    core_config=core_config,\n",
     "    target_platform_capabilities=tpc)\n",
-    "quant_model.save('/content/quant_model.keras')"
+    "quant_model.save('./quant_model.keras')"
    ],
    "metadata": {
     "collapsed": false