--- a
+++ b/demo/demo.ipynb
@@ -0,0 +1,128 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {
+    "pycharm": {
+     "is_executing": false
+    }
+   },
+   "outputs": [],
+   "source": [
+    "from mmaction.apis import init_recognizer, inference_recognizer"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {
+    "pycharm": {
+     "is_executing": false
+    }
+   },
+   "outputs": [],
+   "source": [
+    "config_file = '../configs/recognition/tsn/tsn_r50_video_inference_1x1x3_100e_kinetics400_rgb.py'\n",
+    "# download the checkpoint from model zoo and put it in `checkpoints/`\n",
+    "checkpoint_file = '../checkpoints/tsn_r50_1x1x3_100e_kinetics400_rgb_20200614-e508be42.pth'"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {
+    "pycharm": {
+     "is_executing": false
+    }
+   },
+   "outputs": [],
+   "source": [
+    "# build the model from a config file and a checkpoint file\n",
+    "model = init_recognizer(config_file, checkpoint_file, device='cpu')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {
+    "pycharm": {
+     "is_executing": false
+    }
+   },
+   "outputs": [],
+   "source": [
+    "# test a single video and show the result:\n",
+    "video = 'demo.mp4'\n",
+    "label = '../tools/data/kinetics/label_map_k400.txt'\n",
+    "results = inference_recognizer(model, video)\n",
+    "\n",
+    "labels = open(label).readlines()\n",
+    "labels = [x.strip() for x in labels]\n",
+    "results = [(labels[k[0]], k[1]) for k in results]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {
+    "collapsed": false,
+    "jupyter": {
+     "outputs_hidden": false
+    },
+    "pycharm": {
+     "is_executing": false,
+     "name": "#%%\n"
+    }
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "arm wrestling:  29.61644\n",
+      "rock scissors paper:  10.754839\n",
+      "shaking hands:  9.9084\n",
+      "clapping:  9.189912\n",
+      "massaging feet:  8.305307\n"
+     ]
+    }
+   ],
+   "source": [
+    "# show the results\n",
+    "for result in results:\n",
+    "    print(f'{result[0]}: ', result[1])"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.7.4"
+  },
+  "pycharm": {
+   "stem_cell": {
+    "cell_type": "raw",
+    "metadata": {
+     "collapsed": false
+    },
+    "source": []
+   }
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 4
+}