naveen521kk · August 10, 2021 12:39 · naveen521kk · Aug 10, 2021
diff --git a/moderngl.ipynb b/moderngl.ipynb
 {
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "name": "Moderngl.ipynb",
      "provenance": [],
      "collapsed_sections": [],
      "authorship_tag": "ABX9TyOzpHExAJG9ttdi5KO2Ozh3",
      "include_colab_link": true
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "language_info": {
      "name": "python"
    },
    "accelerator": "GPU"
  },
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/gist/naveen521kk/d7920a00c47afbd463f702d63681fd83/moderngl.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "mn2uvwLOD06I"
      },
      "source": [
        "## ModernGL Notebook\n",
        "\n",
        "First change the runtime to `GPU` (`Runtime > Change runtime type > Hardware accelerator`).\n",
        "\n",
        "After that click `Run all`(`Runtime > Run all`) to execute all the cell."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "dKpSZMmN1nBT",
        "outputId": "e71e675d-e787-4cbe-d886-08f65eddacfd"
      },
      "source": [
        "#@markdown Install **Moderngl** using *pip* and **libegl-mesa** from *apt*\n",
        "!pip install moderngl\n",
        "!sudo apt install  mesa-utils libegl1-mesa"
      ],
      "execution_count": 1,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Collecting moderngl\n",
            "  Downloading moderngl-5.6.4-cp37-cp37m-manylinux1_x86_64.whl (670 kB)\n",
            "\u001b[K     |████████████████████████████████| 670 kB 7.4 MB/s \n",
            "\u001b[?25hCollecting glcontext<3,>=2\n",
            "  Downloading glcontext-2.3.4-cp37-cp37m-manylinux_2_5_x86_64.manylinux1_x86_64.whl (64 kB)\n",
            "\u001b[K     |████████████████████████████████| 64 kB 3.8 MB/s \n",
            "\u001b[?25hInstalling collected packages: glcontext, moderngl\n",
            "Successfully installed glcontext-2.3.4 moderngl-5.6.4\n",
            "Reading package lists... Done\n",
            "Building dependency tree       \n",
            "Reading state information... Done\n",
            "The following NEW packages will be installed:\n",
            "  libegl1-mesa mesa-utils\n",
            "0 upgraded, 2 newly installed, 0 to remove and 40 not upgraded.\n",
            "Need to get 40.7 kB of archives.\n",
            "After this operation, 217 kB of additional disk space will be used.\n",
            "Get:1 http://archive.ubuntu.com/ubuntu bionic-updates/main amd64 libegl1-mesa amd64 20.0.8-0ubuntu1~18.04.1 [6,416 B]\n",
            "Get:2 http://archive.ubuntu.com/ubuntu bionic/universe amd64 mesa-utils amd64 8.4.0-1 [34.3 kB]\n",
            "Fetched 40.7 kB in 1s (60.3 kB/s)\n",
            "debconf: unable to initialize frontend: Dialog\n",
            "debconf: (No usable dialog-like program is installed, so the dialog based frontend cannot be used. at /usr/share/perl5/Debconf/FrontEnd/Dialog.pm line 76, <> line 2.)\n",
            "debconf: falling back to frontend: Readline\n",
            "debconf: unable to initialize frontend: Readline\n",
            "debconf: (This frontend requires a controlling tty.)\n",
            "debconf: falling back to frontend: Teletype\n",
            "dpkg-preconfigure: unable to re-open stdin: \n",
            "Selecting previously unselected package libegl1-mesa:amd64.\n",
            "(Reading database ... 160837 files and directories currently installed.)\n",
            "Preparing to unpack .../libegl1-mesa_20.0.8-0ubuntu1~18.04.1_amd64.deb ...\n",
            "Unpacking libegl1-mesa:amd64 (20.0.8-0ubuntu1~18.04.1) ...\n",
            "Selecting previously unselected package mesa-utils.\n",
            "Preparing to unpack .../mesa-utils_8.4.0-1_amd64.deb ...\n",
            "Unpacking mesa-utils (8.4.0-1) ...\n",
            "Setting up libegl1-mesa:amd64 (20.0.8-0ubuntu1~18.04.1) ...\n",
            "Setting up mesa-utils (8.4.0-1) ...\n",
            "Processing triggers for man-db (2.8.3-2ubuntu0.1) ...\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "VdQQvavX3P1V"
      },
      "source": [
        "#@markdown Imports.\n",
        "\n",
        "import moderngl\n",
        "import numpy as np\n",
        "from PIL import Image"
      ],
      "execution_count": 2,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "y26DVHRX1u_W"
      },
      "source": [
        "#@markdown Create a context using egl backend\n",
        "ctx = moderngl.create_context(\n",
        "    standalone=True,\n",
        "    backend='egl',\n",
        ")"
      ],
      "execution_count": 3,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Bq7v66Z93TSm"
      },
      "source": [
        "#@markdown First, Vertex shaders ill set `gl_Position` \n",
        "#@markdown to `in_vert` and `color` to `in_color`.\n",
        "#@markdown After that, the frament shaders are \n",
        "#@markdown executed and the `color` variable which \n",
        "#@markdown `vertex_shader` returns is set to `fragColor`.\n",
        "#@markdown This would give the color of the point\n",
        "#@markdown at a particular point.\n",
        "\n",
        "prog = ctx.program(vertex_shader=\"\"\"\n",
        "    #version 330\n",
        "    in vec2 in_vert;\n",
        "    in vec3 in_color;\n",
        "    out vec3 color;\n",
        "    void main() {\n",
        "        gl_Position = vec4(in_vert, 0.0, 1.0);\n",
        "        color = in_color;\n",
        "    }\n",
        "    \"\"\",\n",
        "    fragment_shader=\"\"\"\n",
        "    #version 330\n",
        "    in vec3 color;\n",
        "    out vec4 fragColor;\n",
        "    void main() {\n",
        "        fragColor = vec4(color, 1.0);\n",
        "    }\n",
        "\"\"\")\n"
      ],
      "execution_count": 4,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "dMMHonZk7My7"
      },
      "source": [
        "#@markdown See [this guide](https://moderngl.readthedocs.io/en/latest/the_guide/program.html#module-moderngl)\n",
        "#@markdown about coordinates.\n",
        "#@markdown Here, we create vertices which draw a\n",
        "#@markdown triangle with vertices \n",
        "#@markdown `[-1, -1], [1, -1], [1, 1]` and also defined color \n",
        "#@markdown for them in a single NumPy Array.\n",
        "\n",
        "vertices = np.array([\n",
        "    -1, -1,\n",
        "    1.0, 0.0, 0.0, # red color\n",
        "    1, -1,\n",
        "    0.0, 1.0, 0.0, # blue color\n",
        "    1, 1,\n",
        "    0.0, 0.0, 1.0, # green color\n",
        "], dtype='f4') # use float32 array\n",
        "\n",
        "vbo = ctx.buffer(vertices) # create a buffer in gpu from the vertices we created\n"
      ],
      "execution_count": 5,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "UnwuCuF_7YjN"
      },
      "source": [
        "#@markdown Create a vertex array from our `vbo`.\n",
        "#@markdown Now, the parameters `in_vert` and `in_color`\n",
        "#@markdown in `ctx.vertex_array()` says to parse the\n",
        "#@markdown buffer of vertices and assign it to\n",
        "#@markdown corresponding variables in our shaders.\n",
        "#@markdown For example, the first value for `in_vert`\n",
        "#@markdown would be `(-1 ,-1)` and for `in_color` \n",
        "#@markdown `1.0, 0.0, 0.0`.\n",
        "\n",
        "vao = ctx.vertex_array(prog, vbo, 'in_vert', 'in_color') "
      ],
      "execution_count": 6,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "eDmpsLjC_kDl"
      },
      "source": [
        "#@markdown Now create a framebuffer for rendering.\n",
        "#@markdown Here, we create a `Context.texture` to hold\n",
        "#@markdown our finally rendered Image. Change the size\n",
        "#@markdown the `texture` will change size of the image\n",
        "#@markdown rendered.\n",
        "fbo = ctx.framebuffer(\n",
        "    color_attachments=[ctx.texture((512, 512), 4)],\n",
        ")\n",
        "\n",
        "fbo.use() # use the frame buffer we created.\n"
      ],
      "execution_count": 7,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "W7PE0U5pBlTo"
      },
      "source": [
        "#@markdown Now clear the screen with white and\n",
        "#@markdown then render the `vao` using \n",
        "#@markdown as triangles `moderngl.TRIANGLES`\n",
        "ctx.clear(1, 1, 1)\n",
        "vao.render(moderngl.TRIANGLES)\n"
      ],
      "execution_count": 8,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "dsya-wH4B53e"
      },
      "source": [
        "#@markdown Now everything is rendered and \n",
        "#@markdown time to read it from `fbo`. Finally,\n",
        "#@markdown after reading them we pass them to a\n",
        "#@markdown Pillow Image so that we can save as\n",
        "#@markdown file (`test.png`).\n",
        "\n",
        "data = fbo.read(components=3)\n",
        "image = Image.frombytes('RGB', fbo.size, data)\n",
        "image.save('test.png')"
      ],
      "execution_count": 9,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "2N4gN3Oj38dp",
        "outputId": "fbe9e527-c626-4d05-e1ea-3c6ce2eee78f"
      },
      "source": [
        "#@markdown Finally, just to be fancy, use\n",
        "#@markdown `IPython.display.Image` to display the\n",
        "#@markdown Image `test.png` which we previously saved.\n",
        "from IPython.display import Image as IPYImage\n",
        "IPYImage('test.png')"
      ],
      "execution_count": 10,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<IPython.core.display.Image object>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 10
        }
      ]
    }
  ]
 }
	{
	"nbformat": 4,
	"nbformat_minor": 0,
	"metadata": {
	"colab": {
	"name": "Moderngl.ipynb",
	"provenance": [],
	"collapsed_sections": [],
	"authorship_tag": "ABX9TyOzpHExAJG9ttdi5KO2Ozh3",
	"include_colab_link": true
	},
	"kernelspec": {
	"name": "python3",
	"display_name": "Python 3"
	},
	"language_info": {
	"name": "python"
	},
	"accelerator": "GPU"
	},
	"cells": [
	{
	"cell_type": "markdown",
	"metadata": {
	"id": "view-in-github",
	"colab_type": "text"
	},
	"source": [
	"<a href=\"https://colab.research.google.com/gist/naveen521kk/d7920a00c47afbd463f702d63681fd83/moderngl.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
	]
	},
	{
	"cell_type": "markdown",
	"metadata": {
	"id": "mn2uvwLOD06I"
	},
	"source": [
	"## ModernGL Notebook\n",
	"\n",
	"First change the runtime to `GPU` (`Runtime > Change runtime type > Hardware accelerator`).\n",
	"\n",
	"After that click `Run all`(`Runtime > Run all`) to execute all the cell."
	]
	},
	{
	"cell_type": "code",
	"metadata": {
	"colab": {
	"base_uri": "https://localhost:8080/"
	},
	"id": "dKpSZMmN1nBT",
	"outputId": "e71e675d-e787-4cbe-d886-08f65eddacfd"
	},
	"source": [
	"#@markdown Install Moderngl using pip and libegl-mesa from apt\n",
	"!pip install moderngl\n",
	"!sudo apt install mesa-utils libegl1-mesa"
	],
	"execution_count": 1,
	"outputs": [
	{
	"output_type": "stream",
	"text": [
	"Collecting moderngl\n",
	" Downloading moderngl-5.6.4-cp37-cp37m-manylinux1_x86_64.whl (670 kB)\n",
	"\u001b[K \|████████████████████████████████\| 670 kB 7.4 MB/s \n",
	"\u001b[?25hCollecting glcontext<3,>=2\n",
	" Downloading glcontext-2.3.4-cp37-cp37m-manylinux_2_5_x86_64.manylinux1_x86_64.whl (64 kB)\n",
	"\u001b[K \|████████████████████████████████\| 64 kB 3.8 MB/s \n",
	"\u001b[?25hInstalling collected packages: glcontext, moderngl\n",
	"Successfully installed glcontext-2.3.4 moderngl-5.6.4\n",
	"Reading package lists... Done\n",
	"Building dependency tree \n",
	"Reading state information... Done\n",
	"The following NEW packages will be installed:\n",
	" libegl1-mesa mesa-utils\n",
	"0 upgraded, 2 newly installed, 0 to remove and 40 not upgraded.\n",
	"Need to get 40.7 kB of archives.\n",
	"After this operation, 217 kB of additional disk space will be used.\n",
	"Get:1 http://archive.ubuntu.com/ubuntu bionic-updates/main amd64 libegl1-mesa amd64 20.0.8-0ubuntu1~18.04.1 [6,416 B]\n",
	"Get:2 http://archive.ubuntu.com/ubuntu bionic/universe amd64 mesa-utils amd64 8.4.0-1 [34.3 kB]\n",
	"Fetched 40.7 kB in 1s (60.3 kB/s)\n",
	"debconf: unable to initialize frontend: Dialog\n",
	"debconf: (No usable dialog-like program is installed, so the dialog based frontend cannot be used. at /usr/share/perl5/Debconf/FrontEnd/Dialog.pm line 76, <> line 2.)\n",
	"debconf: falling back to frontend: Readline\n",
	"debconf: unable to initialize frontend: Readline\n",
	"debconf: (This frontend requires a controlling tty.)\n",
	"debconf: falling back to frontend: Teletype\n",
	"dpkg-preconfigure: unable to re-open stdin: \n",
	"Selecting previously unselected package libegl1-mesa:amd64.\n",
	"(Reading database ... 160837 files and directories currently installed.)\n",
	"Preparing to unpack .../libegl1-mesa_20.0.8-0ubuntu1~18.04.1_amd64.deb ...\n",
	"Unpacking libegl1-mesa:amd64 (20.0.8-0ubuntu1~18.04.1) ...\n",
	"Selecting previously unselected package mesa-utils.\n",
	"Preparing to unpack .../mesa-utils_8.4.0-1_amd64.deb ...\n",
	"Unpacking mesa-utils (8.4.0-1) ...\n",
	"Setting up libegl1-mesa:amd64 (20.0.8-0ubuntu1~18.04.1) ...\n",
	"Setting up mesa-utils (8.4.0-1) ...\n",
	"Processing triggers for man-db (2.8.3-2ubuntu0.1) ...\n"
	],
	"name": "stdout"
	}
	]
	},
	{
	"cell_type": "code",
	"metadata": {
	"id": "VdQQvavX3P1V"
	},
	"source": [
	"#@markdown Imports.\n",
	"\n",
	"import moderngl\n",
	"import numpy as np\n",
	"from PIL import Image"
	],
	"execution_count": 2,
	"outputs": []
	},
	{
	"cell_type": "code",
	"metadata": {
	"id": "y26DVHRX1u_W"
	},
	"source": [
	"#@markdown Create a context using egl backend\n",
	"ctx = moderngl.create_context(\n",
	" standalone=True,\n",
	" backend='egl',\n",
	")"
	],
	"execution_count": 3,
	"outputs": []
	},
	{
	"cell_type": "code",
	"metadata": {
	"id": "Bq7v66Z93TSm"
	},
	"source": [
	"#@markdown First, Vertex shaders ill set `gl_Position` \n",
	"#@markdown to `in_vert` and `color` to `in_color`.\n",
	"#@markdown After that, the frament shaders are \n",
	"#@markdown executed and the `color` variable which \n",
	"#@markdown `vertex_shader` returns is set to `fragColor`.\n",
	"#@markdown This would give the color of the point\n",
	"#@markdown at a particular point.\n",
	"\n",
	"prog = ctx.program(vertex_shader=\"\"\"\n",
	" #version 330\n",
	" in vec2 in_vert;\n",
	" in vec3 in_color;\n",
	" out vec3 color;\n",
	" void main() {\n",
	" gl_Position = vec4(in_vert, 0.0, 1.0);\n",
	" color = in_color;\n",
	" }\n",
	" \"\"\",\n",
	" fragment_shader=\"\"\"\n",
	" #version 330\n",
	" in vec3 color;\n",
	" out vec4 fragColor;\n",
	" void main() {\n",
	" fragColor = vec4(color, 1.0);\n",
	" }\n",
	"\"\"\")\n"
	],
	"execution_count": 4,
	"outputs": []
	},
	{
	"cell_type": "code",
	"metadata": {
	"id": "dMMHonZk7My7"
	},
	"source": [
	"#@markdown See [this guide](https://moderngl.readthedocs.io/en/latest/the_guide/program.html#module-moderngl)\n",
	"#@markdown about coordinates.\n",
	"#@markdown Here, we create vertices which draw a\n",
	"#@markdown triangle with vertices \n",
	"#@markdown `[-1, -1], [1, -1], [1, 1]` and also defined color \n",
	"#@markdown for them in a single NumPy Array.\n",
	"\n",
	"vertices = np.array([\n",
	" -1, -1,\n",
	" 1.0, 0.0, 0.0, # red color\n",
	" 1, -1,\n",
	" 0.0, 1.0, 0.0, # blue color\n",
	" 1, 1,\n",
	" 0.0, 0.0, 1.0, # green color\n",
	"], dtype='f4') # use float32 array\n",
	"\n",
	"vbo = ctx.buffer(vertices) # create a buffer in gpu from the vertices we created\n"
	],
	"execution_count": 5,
	"outputs": []
	},
	{
	"cell_type": "code",
	"metadata": {
	"id": "UnwuCuF_7YjN"
	},
	"source": [
	"#@markdown Create a vertex array from our `vbo`.\n",
	"#@markdown Now, the parameters `in_vert` and `in_color`\n",
	"#@markdown in `ctx.vertex_array()` says to parse the\n",
	"#@markdown buffer of vertices and assign it to\n",
	"#@markdown corresponding variables in our shaders.\n",
	"#@markdown For example, the first value for `in_vert`\n",
	"#@markdown would be `(-1 ,-1)` and for `in_color` \n",
	"#@markdown `1.0, 0.0, 0.0`.\n",
	"\n",
	"vao = ctx.vertex_array(prog, vbo, 'in_vert', 'in_color') "
	],
	"execution_count": 6,
	"outputs": []
	},
	{
	"cell_type": "code",
	"metadata": {
	"id": "eDmpsLjC_kDl"
	},
	"source": [
	"#@markdown Now create a framebuffer for rendering.\n",
	"#@markdown Here, we create a `Context.texture` to hold\n",
	"#@markdown our finally rendered Image. Change the size\n",
	"#@markdown the `texture` will change size of the image\n",
	"#@markdown rendered.\n",
	"fbo = ctx.framebuffer(\n",
	" color_attachments=[ctx.texture((512, 512), 4)],\n",
	")\n",
	"\n",
	"fbo.use() # use the frame buffer we created.\n"
	],
	"execution_count": 7,
	"outputs": []
	},
	{
	"cell_type": "code",
	"metadata": {
	"id": "W7PE0U5pBlTo"
	},
	"source": [
	"#@markdown Now clear the screen with white and\n",
	"#@markdown then render the `vao` using \n",
	"#@markdown as triangles `moderngl.TRIANGLES`\n",
	"ctx.clear(1, 1, 1)\n",
	"vao.render(moderngl.TRIANGLES)\n"
	],
	"execution_count": 8,
	"outputs": []
	},
	{
	"cell_type": "code",
	"metadata": {
	"id": "dsya-wH4B53e"
	},
	"source": [
	"#@markdown Now everything is rendered and \n",
	"#@markdown time to read it from `fbo`. Finally,\n",
	"#@markdown after reading them we pass them to a\n",
	"#@markdown Pillow Image so that we can save as\n",
	"#@markdown file (`test.png`).\n",
	"\n",
	"data = fbo.read(components=3)\n",
	"image = Image.frombytes('RGB', fbo.size, data)\n",
	"image.save('test.png')"
	],
	"execution_count": 9,
	"outputs": []
	},
	{
	"cell_type": "code",
	"metadata": {
	"colab": {
	"base_uri": "https://localhost:8080/"
	},
	"id": "2N4gN3Oj38dp",
	"outputId": "fbe9e527-c626-4d05-e1ea-3c6ce2eee78f"
	},
	"source": [
	"#@markdown Finally, just to be fancy, use\n",
	"#@markdown `IPython.display.Image` to display the\n",
	"#@markdown Image `test.png` which we previously saved.\n",
	"from IPython.display import Image as IPYImage\n",
	"IPYImage('test.png')"
	],
	"execution_count": 10,
	"outputs": [
	{
	"output_type": "execute_result",
	"data": {
	"image/png": 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\n",
	"text/plain": [
	"<IPython.core.display.Image object>"
	]
	},
	"metadata": {
	"tags": []
	},
	"execution_count": 10
	}
	]
	}
	]
	}