GIF gist

GIF_gist.ipynb

{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "name": "scratchpad",
      "provenance": [],
      "include_colab_link": true
    },
    "kernelspec": {
      "display_name": "Python 3",
      "name": "python3"
    }
  },
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/gist/ariG23498/3e9f3c138e346a2f3ea7add9249707d3/scratchpad.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "1RM0UzT3IP-o",
        "outputId": "6a70fee2-2b4d-4302-b367-81fbc54170c4",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 35
        }
      },
      "source": [
        "from google.colab import drive\n",
        "drive.mount('/content/drive')"
      ],
      "execution_count": 1,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Mounted at /content/drive\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "lIYdn1woOS1n"
      },
      "source": [
        "import imageio\n",
        "import glob\n",
        "import os\n",
        "import base64\n",
        "from IPython import display"
      ],
      "execution_count": 2,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "nPUxh5WrInht"
      },
      "source": [
        "from tqdm import tqdm"
      ],
      "execution_count": 3,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "w0icbqOnH_1d"
      },
      "source": [
        "def create_gif(path_to_images, name_gif):\n",
        "  filenames = glob.glob(path_to_images)\n",
        "  filenames = sorted(filenames)\n",
        "  images = []\n",
        "  for filename in tqdm(filenames):\n",
        "    images.append(imageio.imread(filename))\n",
        "\n",
        "  kargs = { 'duration': 0.50 }\n",
        "  imageio.mimsave(name_gif, images, 'GIF', **kargs)\n",
        "\n",
        "def show_gif(fname):\n",
        "    with open(fname, 'rb') as fd:\n",
        "        b64 = base64.b64encode(fd.read()).decode('ascii')\n",
        "    return display.HTML(f'<img src=\"data:image/gif;base64,{b64}\" />')"
      ],
      "execution_count": 4,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "IhzwlS95IA26",
        "outputId": "669c4bb5-f744-44af-f976-6bff7920b279",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 35
        }
      },
      "source": [
        "create_gif('/content/drive/My Drive/GIF/RNN_back*.png', 'backprop.gif')"
      ],
      "execution_count": 8,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "100%|██████████| 11/11 [00:07<00:00,  1.45it/s]\n"
          ],
          "name": "stderr"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "g7wL5bYcMHGZ"
      },
      "source": [
        ""
      ],
      "execution_count": null,
      "outputs": []
    }
  ]
}