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julianfbeck/renderlunarlander.ipynb

Created January 16, 2021 10:12
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RenderLunarLander.ipynb
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renderlunarlander.ipynb
{
"nbformat": 4,
"nbformat_minor": 0,
"metadata": {
"colab": {
"name": "RenderLunarLander.ipynb",
"provenance": [],
"authorship_tag": "ABX9TyPisLLZCoZq8NLGDgxRiJyE",
"include_colab_link": true
},
"kernelspec": {
"name": "python3",
"display_name": "Python 3"
}
},
"cells": [
{
"cell_type": "markdown",
"metadata": {
"id": "view-in-github",
"colab_type": "text"
},
"source": [
"<a href=\"https://colab.research.google.com/gist/jufabeck2202/6ce22a4a2446cd9b6c118b81eb933bd5/renderlunarlander.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "kOYH3BEWdSRq"
},
"source": [
"# Not my Code, Code found [here](https://colab.research.google.com/github/jeffheaton/t81_558_deep_learning/blob/master/t81_558_class_12_01_ai_gym.ipynb#scrollTo=78BfQoQKOq7z)"
]
},
{
"cell_type": "code",
"metadata": {
"id": "90YwiYSiq21F"
},
"source": [
"!pip install gym pyvirtualdisplay > /dev/null 2>&1\n",
"!apt-get install -y xvfb python-opengl ffmpeg > /dev/null 2>&1\n",
"!pip3 install box2d-py gym > /dev/null"
],
"execution_count": null,
"outputs": []
},
{
"cell_type": "code",
"metadata": {
"id": "jIgWkRqoq-2e"
},
"source": [
"import gym\n",
"from gym.wrappers import Monitor\n",
"import glob\n",
"import io\n",
"import base64\n",
"from IPython.display import HTML\n",
"from pyvirtualdisplay import Display\n",
"from IPython import display as ipythondisplay\n",
"\n",
"display = Display(visible=0, size=(1400, 900))\n",
"display.start()\n",
"\n",
"\"\"\"\n",
"Utility functions to enable video recording of gym environment \n",
"and displaying it.\n",
"To enable video, just do \"env = wrap_env(env)\"\"\n",
"\"\"\"\n",
"\n",
"def show_video():\n",
" mp4list = glob.glob('video/*.mp4')\n",
" if len(mp4list) > 0:\n",
" mp4 = mp4list[0]\n",
" video = io.open(mp4, 'r+b').read()\n",
" encoded = base64.b64encode(video)\n",
" ipythondisplay.display(HTML(data='''<video alt=\"test\" autoplay \n",
" loop controls style=\"height: 400px;\">\n",
" <source src=\"data:video/mp4;base64,{0}\" type=\"video/mp4\" />\n",
" </video>'''.format(encoded.decode('ascii'))))\n",
" else: \n",
" print(\"Could not find video\")\n",
" \n",
"\n",
"def wrap_env(env):\n",
" env = Monitor(env, './video', force=True)\n",
" return env"
],
"execution_count": null,
"outputs": []
},
{
"cell_type": "code",
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 421
},
"id": "cyRVMXYLrAla",
"outputId": "dc5dcef9-4283-4892-cc64-2d1af9f9af5e"
},
"source": [
"env = wrap_env(gym.make(\"LunarLander-v2\"))\n",
"\n",
"observation = env.reset()\n",
"\n",
"while True:\n",
" \n",
" env.render()\n",
" \n",
" #your agent goes here\n",
" action = env.action_space.sample() \n",
" \n",
" observation, reward, done, info = env.step(action) \n",
" \n",
" \n",
" if done: \n",
" break;\n",
" \n",
"env.close()\n",
"show_video()"
],
"execution_count": null,
"outputs": [
{
"output_type": "display_data",
"data": {
"text/html": [
"<video alt=\"test\" autoplay \n",
" loop controls style=\"height: 400px;\">\n",
" <source 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],
"text/plain": [
"<IPython.core.display.HTML object>"
]
},
"metadata": {
"tags": []
}
}
]
}
]
}
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