colab step by step

docs/vame-docs-app/docs/getting_started/step_by_step.mdx

@@ -3,6 +3,8 @@ title: VAME step-by-step
 sidebar_position: 2
 ---
 
+[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/EthoML/VAME/blob/dev/examples/demo.ipynb)
+
 The VAME workflow consists of four main steps, plus optional steps to analyse your data:
 1. Initialize project: This is step is responsible by starting the project, getting your pose estimation data into the right format
 2. Preprocess: This step is responsible for cleaning, filtering and aligning the pose estimation data

examples/demo.ipynb

@@ -16,18 +16,29 @@
     "- clustering the motifs into communities\n",
     "- visualizing the results\n",
     "\n",
-    "Let's start by importing the necessary libraries:"
+    "If you haven't yet, please install VAME by running `pip`:"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": null,
    "id": "2a9c4951-4ff1-4604-be12-0a7851aef6d3",
-   "metadata": {},
+   "metadata": {
+    "vscode": {
+     "languageId": "bat"
+    }
+   },
    "outputs": [],
    "source": [
-    "%load_ext autoreload\n",
-    "%autoreload 2"
+    "pip install vame"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "ade5d437",
+   "metadata": {},
+   "source": [
+    "Let's start by importing the necessary libraries:"
    ]
   },
   {
@@ -424,9 +435,9 @@
  ],
  "metadata": {
   "kernelspec": {
-   "display_name": "Python [conda env:vame] *",
+   "display_name": "vame",
    "language": "python",
-   "name": "conda-env-vame-py"
+   "name": "python3"
   },
   "language_info": {
    "codemirror_mode": {