diff --git a/tutorials/instructor/intro.ipynb b/tutorials/instructor/intro.ipynb index e5c5c1c50..2c6bde906 100644 --- a/tutorials/instructor/intro.ipynb +++ b/tutorials/instructor/intro.ipynb @@ -93,7 +93,7 @@ " return tab_contents\n", "\n", "\n", - "video_ids = [('Youtube', 'cV2q-vpdKUA'), ('Bilibili', 'BV1Zg4y1A7tJ')]\n", + "video_ids = [('Youtube', 'FwjyhCLeqx0'), ('Bilibili', 'BV1QE421P7EJ')]\n", "tab_contents = display_videos(video_ids, W=854, H=480)\n", "tabs = widgets.Tab()\n", "tabs.children = tab_contents\n", @@ -110,7 +110,7 @@ "source": [ "## Concepts map\n", "\n", - "\"Concept\n", + "\"Concept\n", "\n", "*Image made by John Butler, with expert color advice from Isabelle Butler*" ] diff --git a/tutorials/intro.ipynb b/tutorials/intro.ipynb index 476864b9a..2c6bde906 100644 --- a/tutorials/intro.ipynb +++ b/tutorials/intro.ipynb @@ -1,438 +1,152 @@ { - "cells": [ - { - "cell_type": "markdown", - "metadata": { - "id": "view-in-github", - "colab_type": "text" - }, - "source": [ - "\"Open" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "execution": {}, - "pycharm": { - "name": "#%% md\n" - }, - "id": "rV1aHp-Og4ZB" - }, - "source": [ - "# Introduction\n", - "\n", - "Welcome to the Neuromatch deep learning course!" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "execution": {}, - "id": "idpprpJEg4ZF" - }, - "source": [ - "

" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "execution": {}, - "id": "HdBSWAkGg4ZF" - }, - "source": [ - "## Orientation Video" - ] - }, - { - "cell_type": "code", - "execution_count": 1, - "metadata": { - "cellView": "form", - "execution": {}, - "pycharm": { - "name": "#%%\n" - }, - "id": "H-nu38BHg4ZF", - "outputId": "51b4ef13-4236-429f-e2c9-6c6a4e1fd390", - "colab": { - "base_uri": "https://localhost:8080/", - "height": 582, - "referenced_widgets": [ - "906dab7b90ad4fb08b9bda77b33de2a9", - "7984b265aa16422a94433654e35d57f4", - "3cc6b2d011bd48ec8fc729c555d57a7b", - "036d8a77155f4c44abfb0966253c8cfb", - "e6bb5228e8d9497ebf1b10e9f4dbc480", - "cf5b368ef6154e8f8a4c34bfee794684" - ] - } - }, - "outputs": [ - { - "output_type": "display_data", - "data": { - "text/plain": [ - "Tab(children=(Output(), Output()), _titles={'0': 'Youtube', '1': 'Bilibili'})" - ], - "application/vnd.jupyter.widget-view+json": { - "version_major": 2, - "version_minor": 0, - "model_id": "906dab7b90ad4fb08b9bda77b33de2a9" - } - }, - "metadata": {} - } - ], - "source": [ - "# @markdown\n", - "from ipywidgets import widgets\n", - "from IPython.display import YouTubeVideo\n", - "from IPython.display import IFrame\n", - "from IPython.display import display\n", - "\n", - "\n", - "class PlayVideo(IFrame):\n", - " def __init__(self, id, source, page=1, width=400, height=300, **kwargs):\n", - " self.id = id\n", - " if source == 'Bilibili':\n", - " src = f'https://player.bilibili.com/player.html?bvid={id}&page={page}'\n", - " elif source == 'Osf':\n", - " src = f'https://mfr.ca-1.osf.io/render?url=https://osf.io/download/{id}/?direct%26mode=render'\n", - " super(PlayVideo, self).__init__(src, width, height, **kwargs)\n", - "\n", - "\n", - "def display_videos(video_ids, W=400, H=300, fs=1):\n", - " tab_contents = []\n", - " for i, video_id in enumerate(video_ids):\n", - " out = widgets.Output()\n", - " with out:\n", - " if video_ids[i][0] == 'Youtube':\n", - " video = YouTubeVideo(id=video_ids[i][1], width=W,\n", - " height=H, fs=fs, rel=0)\n", - " print(f'Video available at https://youtube.com/watch?v={video.id}')\n", - " else:\n", - " video = PlayVideo(id=video_ids[i][1], source=video_ids[i][0], width=W,\n", - " height=H, fs=fs, autoplay=False)\n", - " if video_ids[i][0] == 'Bilibili':\n", - " print(f'Video available at https://www.bilibili.com/video/{video.id}')\n", - " elif video_ids[i][0] == 'Osf':\n", - " print(f'Video available at https://osf.io/{video.id}')\n", - " display(video)\n", - " tab_contents.append(out)\n", - " return tab_contents\n", - "\n", - "\n", - "video_ids = [('Youtube', 'cV2q-vpdKUA'), ('Bilibili', 'BV1Zg4y1A7tJ')]\n", - "tab_contents = display_videos(video_ids, W=854, H=480)\n", - "tabs = widgets.Tab()\n", - "tabs.children = tab_contents\n", - "for i in range(len(tab_contents)):\n", - " tabs.set_title(i, video_ids[i][0])\n", - "display(tabs)" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "execution": {}, - "id": "_eLZR6Mrg4ZH" - }, - "source": [ - "## Concepts map\n", - "\n", - "\"Concept\n", - "\n", - "*Image made by John Butler, with expert color advice from Isabelle Butler*" - ] + "cells": [ + { + "cell_type": "markdown", + "metadata": { + "colab_type": "text", + "execution": {}, + "id": "view-in-github" + }, + "source": [ + "\"Open   \"Open" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "execution": {}, + "pycharm": { + "name": "#%% md\n" } - ], - "metadata": { - "colab": { - "name": "intro", - "provenance": [], - "toc_visible": true, - "include_colab_link": true - }, - "kernel": { - "display_name": "Python 3", - "language": "python", - "name": "python3" - }, - "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": "3.7.10" - }, - "widgets": { - "application/vnd.jupyter.widget-state+json": { - "906dab7b90ad4fb08b9bda77b33de2a9": { - "model_module": "@jupyter-widgets/controls", - "model_name": "TabModel", - "model_module_version": "1.5.0", - "state": { - "_dom_classes": [], - "_model_module": "@jupyter-widgets/controls", - "_model_module_version": "1.5.0", - "_model_name": "TabModel", - "_titles": { - "0": "Youtube", - "1": "Bilibili" - }, - "_view_count": null, - "_view_module": "@jupyter-widgets/controls", - "_view_module_version": "1.5.0", - "_view_name": "TabView", - "box_style": "", - "children": [ - "IPY_MODEL_7984b265aa16422a94433654e35d57f4", - "IPY_MODEL_3cc6b2d011bd48ec8fc729c555d57a7b" - ], - "layout": "IPY_MODEL_036d8a77155f4c44abfb0966253c8cfb", - "selected_index": 0 - } - }, - "7984b265aa16422a94433654e35d57f4": { - "model_module": "@jupyter-widgets/output", - "model_name": "OutputModel", - "model_module_version": "1.0.0", - "state": { - "_dom_classes": [], - 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"justify_content": null, - "justify_items": null, - "left": null, - "margin": null, - "max_height": null, - "max_width": null, - "min_height": null, - "min_width": null, - "object_fit": null, - "object_position": null, - "order": null, - "overflow": null, - "overflow_x": null, - "overflow_y": null, - "padding": null, - "right": null, - "top": null, - "visibility": null, - "width": null - } - }, - "cf5b368ef6154e8f8a4c34bfee794684": { - "model_module": "@jupyter-widgets/base", - "model_name": "LayoutModel", - "model_module_version": "1.2.0", - "state": { - "_model_module": "@jupyter-widgets/base", - "_model_module_version": "1.2.0", - "_model_name": "LayoutModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/base", - "_view_module_version": "1.2.0", - "_view_name": "LayoutView", - "align_content": null, - "align_items": null, - "align_self": null, - "border": null, - "bottom": null, - "display": null, - "flex": null, - "flex_flow": null, - "grid_area": null, - "grid_auto_columns": null, - "grid_auto_flow": null, - "grid_auto_rows": null, - "grid_column": null, - "grid_gap": null, - "grid_row": null, - "grid_template_areas": null, - "grid_template_columns": null, - "grid_template_rows": null, - "height": null, - "justify_content": null, - "justify_items": null, - "left": null, - "margin": null, - "max_height": null, - "max_width": null, - "min_height": null, - "min_width": null, - "object_fit": null, - "object_position": null, - "order": null, - "overflow": null, - "overflow_x": null, - "overflow_y": null, - "padding": null, - "right": null, - "top": null, - "visibility": null, - "width": null - } - } - } + }, + "source": [ + "# Introduction\n", + "\n", + "Welcome to the Neuromatch deep learning course!" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "execution": {} + }, + "source": [ + "

" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "execution": {} + }, + "source": [ + "## Orientation Video" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "cellView": "form", + "execution": {}, + "pycharm": { + "name": "#%%\n" } + }, + "outputs": [], + "source": [ + "# @markdown\n", + "from ipywidgets import widgets\n", + "from IPython.display import YouTubeVideo\n", + "from IPython.display import IFrame\n", + "from IPython.display import display\n", + "\n", + "\n", + "class PlayVideo(IFrame):\n", + " def __init__(self, id, source, page=1, width=400, height=300, **kwargs):\n", + " self.id = id\n", + " if source == 'Bilibili':\n", + " src = f'https://player.bilibili.com/player.html?bvid={id}&page={page}'\n", + " elif source == 'Osf':\n", + " src = f'https://mfr.ca-1.osf.io/render?url=https://osf.io/download/{id}/?direct%26mode=render'\n", + " super(PlayVideo, self).__init__(src, width, height, **kwargs)\n", + "\n", + "\n", + "def display_videos(video_ids, W=400, H=300, fs=1):\n", + " tab_contents = []\n", + " for i, video_id in enumerate(video_ids):\n", + " out = widgets.Output()\n", + " with out:\n", + " if video_ids[i][0] == 'Youtube':\n", + " video = YouTubeVideo(id=video_ids[i][1], width=W,\n", + " height=H, fs=fs, rel=0)\n", + " print(f'Video available at https://youtube.com/watch?v={video.id}')\n", + " else:\n", + " video = PlayVideo(id=video_ids[i][1], source=video_ids[i][0], width=W,\n", + " height=H, fs=fs, autoplay=False)\n", + " if video_ids[i][0] == 'Bilibili':\n", + " print(f'Video available at https://www.bilibili.com/video/{video.id}')\n", + " elif video_ids[i][0] == 'Osf':\n", + " print(f'Video available at https://osf.io/{video.id}')\n", + " display(video)\n", + " tab_contents.append(out)\n", + " return tab_contents\n", + "\n", + "\n", + "video_ids = [('Youtube', 'FwjyhCLeqx0'), ('Bilibili', 'BV1QE421P7EJ')]\n", + "tab_contents = display_videos(video_ids, W=854, H=480)\n", + "tabs = widgets.Tab()\n", + "tabs.children = tab_contents\n", + "for i in range(len(tab_contents)):\n", + " tabs.set_title(i, video_ids[i][0])\n", + "display(tabs)" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "execution": {} + }, + "source": [ + "## Concepts map\n", + "\n", + "\"Concept\n", + "\n", + "*Image made by John Butler, with expert color advice from Isabelle Butler*" + ] + } + ], + "metadata": { + "colab": { + "collapsed_sections": [], + "include_colab_link": true, + "name": "intro", + "provenance": [], + "toc_visible": true + }, + "kernel": { + "display_name": "Python 3", + "language": "python", + "name": "python3" + }, + "kernelspec": { + "display_name": "Python 3", + "language": "python", + "name": "python3" }, - "nbformat": 4, - "nbformat_minor": 0 -} \ No newline at end of file + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.7.10" + } + }, + "nbformat": 4, + "nbformat_minor": 0 +} diff --git a/tutorials/student/intro.ipynb b/tutorials/student/intro.ipynb index e5c5c1c50..2c6bde906 100644 --- a/tutorials/student/intro.ipynb +++ b/tutorials/student/intro.ipynb @@ -93,7 +93,7 @@ " return tab_contents\n", "\n", "\n", - "video_ids = [('Youtube', 'cV2q-vpdKUA'), ('Bilibili', 'BV1Zg4y1A7tJ')]\n", + "video_ids = [('Youtube', 'FwjyhCLeqx0'), ('Bilibili', 'BV1QE421P7EJ')]\n", "tab_contents = display_videos(video_ids, W=854, H=480)\n", "tabs = widgets.Tab()\n", "tabs.children = tab_contents\n", @@ -110,7 +110,7 @@ "source": [ "## Concepts map\n", "\n", - "\"Concept\n", + "\"Concept\n", "\n", "*Image made by John Butler, with expert color advice from Isabelle Butler*" ]