Object_Localization_with_TensorFlow.ipynb

{
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "colab_type": "text",
        "id": "view-in-github"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/eshansurendra/ObjectLoacalizationWithTensorflow/blob/main/Copy_of_Object_Localization_with_TensorFlow_Starter.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "mfJ15yGqjM1z"
      },
      "source": [
        "# Object Localization with TensorFlow\n",
        "\n",
        "Created for the Coursera Guided Project: [Object Localization with TensorFlow](https://www.coursera.org/projects/object-localization-tensorflow)\n",
        "\n",
        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W8MHi1HijVGms5GlKjG8h4wCfXqfzqvreuT2M8qWkkbmCLfJGLOack8nazRjEeRjk565xVl/D8UmpC+N/qAlGQAJ/lCkglQMdMgflTrvQLe8muHa4u4o7r/j4hhmKLKdoXJI+YHAA4IzjmgCPUNVuo7GyuLOA7LnBeU27z+SCuR+7j+Zs9OoApkOrX0vh6W9jhgublJCgWDcRgPtLFcbgQMsU68YHNTtoEBhs0ju72GSziaKGZJvmCtjIOQQ33R1B6U5tCtG09rRnuPnlE7zCYiRpAQQxYf7o46YGMY4oAh0TU7m+uLqG4kgkEKoylIZIJPm3Z3RSfMo4GDnB59K2ao2Olx2U0tw1xcXNxKqo0s7AnaMkKAAAByeg5zzmr1ABRRRQAUUUUAMm/wBRJ/un+VfMGvf8h6+/67t/Ovp+b/USf7p/lXzBr3/Ievv+u7fzrzcx2ifacHfxKvojtdR/5JHZf9dR/I1y3gz/AJG7Tf8Arun/AKEK6nUf+SR2X/XUfyNct4MIHi3TSf8Anun/AKEK5p/xIfI/PuIP+RvP/F+p794h1qDRNKkuJ22/IQv1xXyzqN7qHj7xasTsZE8xkXjAwM13Xxp8WG4Y6LBIVdZF+6SDzirnwr8KCysTdXMf71m3qWAJ5rrzLGLC0HLr0PRpQ55WOw8JeGbfQNLgiEYWZUCsc5ro6KK/O6lSVSTnJ6s9FJJWQUUUVmMKKKKACiiigAooooAKKKKACuC8f+CYddsvNgiHnhizEnFd7TXQOhUjg1th686FRVIPVClFSVmfL2i65qGkRy6GzlYp3yylevaug0v/AJCtp/11X+dbPj/wkLfXoL63jxHHHlioAGcmsbS/+Qraf9dV/nX2MsVHEqFSJ9fwxHlwVVeb/I7D4pf8hq0/690/9BWtX4Nf8hHUP9xf61lfFL/kNWn/AF7p/wCgrWr8Gv8AkI6h/uL/AFrqh/vfzPyD/mYP1Z6V4n1mTQ9Ge4t4TcXkjCK2hClt8h9hzwAT+FGiW1xcIuranE6ahKpAhfGLdM/dUAnrgEnqe+MADYwCQSBkdDS1657YUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQBzni/poX/AGGLf+Zro65zxf00L/sMW/8AM10dABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQBWu7xbSS1V1JFxMIdw/hJViCfxGPxqzWV4i+TRnuP+fWSO4z6BHVj+gNatABRRRQBzngT/AJFKD/r5uv8A0okro65zwJ/yKUH/AF83X/pRJXR0AFFFFABRRRQAUUUUAFFFFABRRRQAyb/USf7p/lXzBr3/ACHr7/ru386+n5v9RJ/un+VfMGvf8h6+/wCu7fzrzcx2ifacHfxKvojtdR/5JHZf9dR/I1wOn3x02+ivASDEwbI9jmu+1H/kkdl/11H8jXlmqnGmTkf3D/Kuaf8AEh8j894g/wCRvP8AxfqPVG8YePZZm+blW+b2/wD1V9G6bbJa6fBGgAxGoP5V4p8GNLI1Y3jgkNGRkjjvXuwGBivC4gxLqYj2a2R7mHjaNwooor586DH1zxFa6FB5twGYc8LXKWvxd0a6uhbrBOGJIycf415N8TdXuLjxDdWp4SN+MH2rg1dlbIJBr6/B5BRnQU6j1ZxzxDUrI+z7G9iv7WOeL7rqGA+tWa8g+C2qz3v2i3kHyxRKAfyr1+vmsbhvq1d0ux1QlzRuFFFFcpQVm6vrVvo9t584JGcYFaVfPHxe1ef/AISCexHCKc5B9zXfluD+t1/Zt6GdWfJG56FH8X9Fkuxbi3n3FtueP8a7fTNTh1S0S4hyFboDXxrvYHOTmvZfgxq08+qCyflFjYg/nXt5lklKhQdWk9jGlXcpWZ7nRRRXyp1HO+NIUbw3eSEfMEODXj2mf8hW0/66r/OvZfGX/IrXv+4a8Vs38q9hf+64P619BlP8N+p9pw9/udT1f5HafFL/AJDVp/17p/6Cta3wa/5COof7i/1rkvGWpDU9QgkBB2xKvH0Fdb8Gv+QjqH+4v9a+hh/vfzPxr/mYP1Z7HRRRXrnthRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFAHOeL+mhf9hi3/ma6Ouc8X9NC/wCwxb/zNdHQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAQXtst5YXFq33ZomjP0Ix/WoNGuWvNEsbh/vyQIzj0bAyPzzV6srQf3drdWve3u5k+gLF1H/fLrQBq0UUUAc54E/wCRSg/6+br/ANKJK6Ouc8Cf8ilB/wBfN1/6USV0dABRRRQAUUUUAFFFFABRRRQAUUUUAMm/1En+6f5V8wa9/wAh6+/67t/Ovp+b/USf7p/lXzBr3/Ievv8Aru38683Mdon2nB38Sr6I7XUf+SR2X/XUfyNeV6r/AMgy4/3D/KvVNR/5JHZf9dR/I15Xqv8AyDLj/cP8q5p/xIfI/PeIP+RvP/F+p6l8JbMJoFtcY5YMM/nXpVcR8LEA8EWTd/m/nXb18fmMnLFTv3Z9DSXuIKKKK4izxH4l+A7ie4kv7dctI247Rk15daeF9SubsQC2mXJ6mM4r69eKOQYdFYf7QzUQsrVTkW0IPqEFe/hc+q0KXs3G9jnlh1J3OK+G/hRvD1iJnADzRKD613lIFCjAAA9BS142Iryr1HUnuzeMVFWQUUUViMK8i+J/gebU5JNQtwC7HsMmvXaayI4w6hh6EZrqwmKnhaiqQJnBSVmfIEfhnUpLsQfZpgS2M+WcV7r8MfBsmiRRX0wAkZGB9epr0X7FaA5FtDn18sVMqqgwqgD0Ar0sdndTFU/ZpWRlCgou4tFFFeGbmD4y/wCRWvf9w14cW2At6c17j4y/5Fa9/wBw14XOcQSH/ZNe/lP8N+p9pw9/udT1f5BHeG8BcnOOK9U+DX/IR1D/AHF/rXjOhOXtpCf75/ma9m+DX/IR1D/cX+tfRQ/3v5n41/zMH6s9jooor1z2wooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigDnPF/TQv+wxb/wAzXR1zni/poX/YYt/5mujoAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACsqy/c+ItUh6CVIbke5IMZ/wDRa/mK1ayrn9z4msJf4Z4JYD7sCrr+gegDVooooA5zwJ/yKUH/AF83X/pRJXR1zngT/kUoP+vm6/8ASiSujoAKKKKACiiigAooooAKKKKACiiigBk3+ok/3T/KvmDXv+Q9ff8AXdv519Pzf6iT/dP8q+YNe/5D19/13b+debmO0T7Tg7+JV9EdrqP/ACSOy/66j+RryvVf+QZcf7h/lXqmo/8AJI7L/rqP5GvK9V/5Blx/uH+Vc0/4kPkfnvEH/I3n/i/U9f8AhVMG8HWcfcbv513teR/B7UFktYrTIyqk4/OvXK+RzOm4Yqafc+gpO8EFFFITiuA0ForjfEvj/S9DDRm4UTDIwfWvPrj4z3SyEQmEr24/+vXo0MrxNePNGOhnKrGO57nRXhA+NF9j/lj+R/xpD8ab/PHk/kf8a3/sPGdifbwPeKK8I/4XRff9MfyP+NIfjTf548n8j/jR/YeM7B7eB7xRXhH/AAui+/6Y/kf8aQ/Gm/zx5P5H/Gj+w8Z2D28D3iivFLH4yyPMounhVM8ken516V4d8Xadr8SfZpw8hBOBXLiMuxGHXNOOhcakZbHQ0UUVwlmD4y/5Fa9/3DXhkozC49Qa9z8Zf8ite/7hrxGNN8ip/eOK9/Kf4b9T7Th7/c6nq/yMzSYTDA4I6sT+tew/Br/kI6h/uL/WvOtRsWsJlRgRuUGvRfg1/wAhHUP9xf619FH/AHv5n41/zMH6s9jooor1z2wooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigDnPF/TQv8AsMW/8zXR1zni/poX/YYt/wCZro6ACiiigAooooAKKKKACiiigAooooAKKKKACiiigArlfEHhkal4s0HVkT/j3lxOf9lQXQ/99DH/AAIV1VFABRRRQBzngT/kUoP+vm6/9KJK6Ouc8Cf8ilB/183X/pRJXR0AFFFFABRRRQAUUUUAFFFFABRRRQAyb/USf7p/lXzBr3/Ievv+u7fzr6fm/wBRJ/un+VfMGvf8h6+/67t/OvNzHaJ9pwd/Eq+iO11H/kkdl/11H8jXmN5A11aSQoCWdSBivTtR/wCSR2X/AF1H8jXH+GLZLzxFZW8gyryqCPxFc0/4kPkfnvEH/I3n/i/UzPhhftofiuSC4OBsxhuOoNfRETiSJHHRgDXzp4/0u58N+NpLuFNkG9ADnPpXt3hHW4tZ0iJ433FEVTxjnFeTxFhWpquup7WGnpynQVyvjrXf7F8PXUqHEioSMHnoa6qvLPi8kp0qdl+4Ijn9a8XL6UamIjGW1zeo7RbR5/4W8N3/AMQtelklldY1YP8AMvBFVPil4ai8MeJ4rGLbgxITj6CvVfgXPasjohHmCP5s/jXFftAf8lAj/wCuKfyFfpMYqK5VseY3c9G8GfDjSNR8IaZdy2sTSS26MxOeSVFeOfF3RLbQfF/2S1jVI/LBwv1NfTPw7/5EDRf+vWP/ANBFfPXx7/5H/wD7Yj+ZqgPVvC/w10e98NWFzJaxF5IsknNeJ/FPRLbRPHr2NtGqRAJwvTkCvqTwV/yJul/9cR/M183/ABu/5KjJ9Iv/AEFaAPW/Dnw00e88OadcSWkJeS3jYk56lQa8J+Juj2+jeO57G3RUiXGAvTqa+r/CP/IoaR/16Rf+givmH4z/APJTrr8P5mgD1WT4S2Op+GIZIEjjleD7wHOa8jb+0Ph/4sa0MkjRoyrnGBzg/wBa+q/D2P8AhHbHPTyhXzx8ZprZ/EkscZHnCWPOB7Cs6tONSDjJaDTad0ey6LfrqGmwSggkxqTz6itGuS8ApImiJ5neNcflXW1+Y4iChVlFHqR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        "\n",
        "All emojis designed by [OpenMoji](https://openmoji.org/) – the open-source emoji and icon project. License: CC BY-SA 4.0"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "4eWHR2O5j2g0"
      },
      "source": [
        "## Task 2: Download and Visualize Data"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "UsuZWoD6cvYt",
        "outputId": "d9df3dec-474b-4cd0-8472-d59a8e79fb71"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "--2023-12-19 12:54:39--  https://github.com/hfg-gmuend/openmoji/releases/latest/download/openmoji-72x72-color.zip\n",
            "Resolving github.com (github.com)... 140.82.114.3\n",
            "Connecting to github.com (github.com)|140.82.114.3|:443... connected.\n",
            "HTTP request sent, awaiting response... 302 Found\n",
            "Location: https://github.com/hfg-gmuend/openmoji/releases/download/14.0.0/openmoji-72x72-color.zip [following]\n",
            "--2023-12-19 12:54:39--  https://github.com/hfg-gmuend/openmoji/releases/download/14.0.0/openmoji-72x72-color.zip\n",
            "Reusing existing connection to github.com:443.\n",
            "HTTP request sent, awaiting response... 302 Found\n",
            "Location: https://objects.githubusercontent.com/github-production-release-asset-2e65be/114106318/3f2e5e8f-810f-46b2-af8e-cfa1afaa3614?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=AKIAIWNJYAX4CSVEH53A%2F20231219%2Fus-east-1%2Fs3%2Faws4_request&X-Amz-Date=20231219T125439Z&X-Amz-Expires=300&X-Amz-Signature=a2b2417c4b85bd90615724277f1a4b3a934d1a5289d3a0a810820a34b207b0ba&X-Amz-SignedHeaders=host&actor_id=0&key_id=0&repo_id=114106318&response-content-disposition=attachment%3B%20filename%3Dopenmoji-72x72-color.zip&response-content-type=application%2Foctet-stream [following]\n",
            "--2023-12-19 12:54:39--  https://objects.githubusercontent.com/github-production-release-asset-2e65be/114106318/3f2e5e8f-810f-46b2-af8e-cfa1afaa3614?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=AKIAIWNJYAX4CSVEH53A%2F20231219%2Fus-east-1%2Fs3%2Faws4_request&X-Amz-Date=20231219T125439Z&X-Amz-Expires=300&X-Amz-Signature=a2b2417c4b85bd90615724277f1a4b3a934d1a5289d3a0a810820a34b207b0ba&X-Amz-SignedHeaders=host&actor_id=0&key_id=0&repo_id=114106318&response-content-disposition=attachment%3B%20filename%3Dopenmoji-72x72-color.zip&response-content-type=application%2Foctet-stream\n",
            "Resolving objects.githubusercontent.com (objects.githubusercontent.com)... 185.199.108.133, 185.199.109.133, 185.199.110.133, ...\n",
            "Connecting to objects.githubusercontent.com (objects.githubusercontent.com)|185.199.108.133|:443... connected.\n",
            "HTTP request sent, awaiting response... 200 OK\n",
            "Length: 7267609 (6.9M) [application/octet-stream]\n",
            "Saving to: ‘openmoji-72x72-color.zip.2’\n",
            "\n",
            "openmoji-72x72-colo 100%[===================>]   6.93M  --.-KB/s    in 0.08s   \n",
            "\n",
            "2023-12-19 12:54:39 (86.0 MB/s) - ‘openmoji-72x72-color.zip.2’ saved [7267609/7267609]\n",
            "\n",
            "mkdir: cannot create directory ‘emojis’: File exists\n",
            "replace ./emojis/1F469-1F3FC-200D-1F9B2.png? [y]es, [n]o, [A]ll, [N]one, [r]ename: y\n",
            "replace ./emojis/1F97F.png? [y]es, [n]o, [A]ll, [N]one, [r]ename: y\n",
            "replace ./emojis/1F9A7.png? [y]es, [n]o, [A]ll, [N]one, [r]ename: y\n",
            "replace ./emojis/1F647-1F3FD-200D-2642-FE0F.png? [y]es, [n]o, [A]ll, [N]one, [r]ename: y\n",
            "replace ./emojis/1F6A3-1F3FC.png? [y]es, [n]o, [A]ll, [N]one, [r]ename: y\n",
            "replace ./emojis/1F9D1-1F3FF-200D-1F9BD.png? [y]es, [n]o, [A]ll, [N]one, [r]ename: y\n",
            "replace ./emojis/1F96B.png? [y]es, [n]o, [A]ll, [N]one, [r]ename: y\n",
            "replace ./emojis/1F958.png? [y]es, [n]o, [A]ll, [N]one, [r]ename: y\n",
            "replace ./emojis/1F469-200D-2696-FE0F.png? [y]es, [n]o, [A]ll, [N]one, [r]ename: a\n",
            "error:  invalid response [a]\n",
            "replace ./emojis/1F469-200D-2696-FE0F.png? [y]es, [n]o, [A]ll, [N]one, [r]ename: y a\n",
            "replace ./emojis/1F970.png? [y]es, [n]o, [A]ll, [N]one, [r]ename: y\n",
            "replace ./emojis/1F469-1F3FC-200D-1F9BD.png? [y]es, [n]o, [A]ll, [N]one, [r]ename: y\n",
            "replace ./emojis/1F9AA.png? [y]es, [n]o, [A]ll, [N]one, [r]ename: y\n",
            "replace ./emojis/1F9D1-1F3FF-200D-1F9B2.png? [y]es, [n]o, [A]ll, [N]one, [r]ename: y\n",
            "replace ./emojis/1F964.png? [y]es, [n]o, [A]ll, [N]one, [r]ename: y\n",
            "replace ./emojis/1F9D1-200D-1F9B0.png? [y]es, [n]o, [A]ll, [N]one, [r]ename: y\n",
            "replace ./emojis/1F1E7-1F1ED.png? [y]es, [n]o, [A]ll, [N]one, [r]ename: y\n",
            "replace ./emojis/1F3CA-1F3FC-200D-2642-FE0F.png? [y]es, [n]o, [A]ll, [N]one, [r]ename: y\n",
            "replace ./emojis/E1D1.png? [y]es, [n]o, [A]ll, [N]one, [r]ename: y\n",
            "y\n",
            "replace ./emojis/23E9.png? [y]es, [n]o, [A]ll, [N]one, [r]ename: replace ./emojis/23FC.png? [y]es, [n]o, [A]ll, [N]one, [r]ename: y\n",
            "replace ./emojis/1F469-200D-2764-FE0F-200D-1F48B-200D-1F469.png? [y]es, [n]o, [A]ll, [N]one, [r]ename: y\n",
            "replace ./emojis/1F596.png? [y]es, [n]o, [A]ll, [N]one, [r]ename: y\n",
            "replace ./emojis/1F1EE-1F1F4.png? [y]es, [n]o, [A]ll, [N]one, [r]ename: y\n",
            "y\n",
            "replace ./emojis/1F930-1F3FE.png? [y]es, [n]o, [A]ll, [N]one, [r]ename: replace ./emojis/1FAF1-1F3FC-200D-1FAF2-1F3FE.png? [y]es, [n]o, [A]ll, [N]one, [r]ename: yy\n",
            "replace ./emojis/1F3CB-1F3FC-200D-2640-FE0F.png? [y]es, [n]o, [A]ll, [N]one, [r]ename: y\n",
            "replace ./emojis/1F1EE-1F1E8.png? [y]es, [n]o, [A]ll, [N]one, [r]ename: y\n",
            "replace ./emojis/1F9D4-1F3FC.png? [y]es, [n]o, [A]ll, [N]one, [r]ename: y\n",
            "replace ./emojis/1F9DD-1F3FC-200D-2642-FE0F.png? [y]es, [n]o, [A]ll, [N]one, [r]ename: y\n",
            "replace ./emojis/1F58D.png? [y]es, [n]o, [A]ll, [N]one, [r]ename: y\n",
            "replace ./emojis/1F443-1F3FB.png? [y]es, [n]o, [A]ll, [N]one, [r]ename: y\n",
            "replace ./emojis/2699.png? [y]es, [n]o, [A]ll, [N]one, [r]ename: y\n",
            "replace ./emojis/1F469-1F3FE-200D-1F37C.png? [y]es, [n]o, [A]ll, [N]one, [r]ename: y\n",
            "replace ./emojis/1F48F-1F3FC.png? [y]es, [n]o, [A]ll, [N]one, [r]ename: y\n",
            "replace ./emojis/1F233.png? [y]es, [n]o, [A]ll, [N]one, [r]ename: y\n",
            "replace ./emojis/1F469-200D-1F469-200D-1F467.png? [y]es, [n]o, [A]ll, [N]one, [r]ename: y\n",
            "y\n",
            "replace ./emojis/1F555.png? [y]es, [n]o, [A]ll, [N]one, [r]ename: replace ./emojis/1F470-1F3FD.png? [y]es, [n]o, [A]ll, [N]one, [r]ename: y\n",
            "replace ./emojis/E318.png? [y]es, [n]o, [A]ll, [N]one, [r]ename: y\n",
            "replace ./emojis/E32B.png? [y]es, [n]o, [A]ll, [N]one, [r]ename: y\n",
            "replace ./emojis/2666.png? [y]es, [n]o, [A]ll, [N]one, [r]ename: yy\n",
            "\n",
            "replace ./emojis/1F646-1F3FD.png? [y]es, [n]o, [A]ll, [N]one, [r]ename: error:  invalid response [{ENTER}]\n",
            "replace ./emojis/1F646-1F3FD.png? [y]es, [n]o, [A]ll, [N]one, [r]ename: yy\n",
            "replace ./emojis/1FAC5-1F3FF.png? [y]es, [n]o, [A]ll, [N]one, [r]ename: y\n",
            "replace ./emojis/1F469-1F3FD-200D-1F9B1.png? [y]es, [n]o, [A]ll, [N]one, [r]ename: y\n",
            "replace ./emojis/1F5C2.png? [y]es, [n]o, [A]ll, [N]one, [r]ename: \n",
            "error:  invalid response [{ENTER}]\n",
            "replace ./emojis/1F5C2.png? [y]es, [n]o, [A]ll, [N]one, [r]ename: yy\n",
            "replace ./emojis/1F55C.png? [y]es, [n]o, [A]ll, [N]one, [r]ename: \n",
            "error:  invalid response [{ENTER}]\n",
            "replace ./emojis/1F55C.png? [y]es, [n]o, [A]ll, [N]one, [r]ename: y\n",
            "replace ./emojis/1FAF3-1F3FD.png? [y]es, [n]o, [A]ll, [N]one, [r]ename: yy\n",
            "y\n",
            "replace ./emojis/E324.png? [y]es, [n]o, [A]ll, [N]one, [r]ename: replace ./emojis/1F1FF-1F1F2.png? [y]es, [n]o, [A]ll, [N]one, [r]ename: y\n",
            "replace ./emojis/1F6B6-1F3FB.png? [y]es, [n]o, [A]ll, [N]one, [r]ename: y\n",
            "replace ./emojis/1F384.png? [y]es, [n]o, [A]ll, [N]one, [r]ename: y\n",
            "replace ./emojis/1F3F4-E0067-E0062-E0073-E0063-E0074-E007F.png? [y]es, [n]o, [A]ll, [N]one, [r]ename: y\n",
            "replace ./emojis/1F390.png? [y]es, [n]o, [A]ll, [N]one, [r]ename: y\n",
            "replace ./emojis/1F38B.png? [y]es, [n]o, [A]ll, [N]one, [r]ename: y\n",
            "replace ./emojis/1F574-1F3FF.png? [y]es, [n]o, [A]ll, [N]one, [r]ename: y\n",
            "replace ./emojis/2935.png? [y]es, [n]o, [A]ll, [N]one, [r]ename: y\n",
            "y\n",
            "replace ./emojis/1F39F.png? [y]es, [n]o, [A]ll, [N]one, [r]ename: replace ./emojis/1F347.png? [y]es, [n]o, [A]ll, [N]one, [r]ename: y\n",
            "replace ./emojis/1F468-200D-1F468-200D-1F466-200D-1F466.png? [y]es, [n]o, [A]ll, [N]one, [r]ename: y\n",
            "replace ./emojis/E24B.png? [y]es, [n]o, [A]ll, [N]one, [r]ename: y\n",
            "replace ./emojis/1F421.png? [y]es, [n]o, [A]ll, [N]one, [r]ename: y\n",
            "replace ./emojis/1F3BF.png? [y]es, [n]o, [A]ll, [N]one, [r]ename: y\n",
            "y\n",
            "replace ./emojis/1F469-1F3FF-200D-2764-FE0F-200D-1F468-1F3FE.png? [y]es, [n]o, [A]ll, [N]one, [r]ename: replace ./emojis/E25F.png? [y]es, [n]o, [A]ll, [N]one, [r]ename: y\n",
            "replace ./emojis/1F435.png? [y]es, [n]o, [A]ll, [N]one, [r]ename: y\n",
            "y\n",
            "replace ./emojis/1F3CB.png? [y]es, [n]o, [A]ll, [N]one, [r]ename: replace ./emojis/2712.png? [y]es, [n]o, [A]ll, [N]one, [r]ename: y\n",
            "replace ./emojis/1F486-1F3FC-200D-2640-FE0F.png? [y]es, [n]o, [A]ll, [N]one, [r]ename: y\n",
            "replace ./emojis/1F46E-1F3FF.png? [y]es, [n]o, [A]ll, [N]one, [r]ename: y\n",
            "replace ./emojis/1F4ED.png? [y]es, [n]o, [A]ll, [N]one, [r]ename: y\n",
            "replace ./emojis/1F353.png? [y]es, [n]o, [A]ll, [N]one, [r]ename: y\n",
            "replace ./emojis/E2C7.png? [y]es, [n]o, [A]ll, [N]one, [r]ename: y\n",
            "replace ./emojis/1F4D6.png? [y]es, [n]o, [A]ll, [N]one, [r]ename: y\n",
            "replace ./emojis/1F34A.png? [y]es, [n]o, [A]ll, [N]one, [r]ename: y\n",
            "y\n",
            "replace ./emojis/E244.png? [y]es, [n]o, [A]ll, [N]one, [r]ename: replace ./emojis/1F3B0.png? [y]es, [n]o, [A]ll, [N]one, [r]ename: y\n",
            "replace ./emojis/1F9CD-1F3FE.png? [y]es, [n]o, [A]ll, [N]one, [r]ename: y\n",
            "replace ./emojis/1F9D1-1F3FE-200D-1F91D-200D-1F9D1-1F3FB.png? [y]es, [n]o, [A]ll, [N]one, [r]ename: y\n",
            "replace ./emojis/1F3CC-1F3FE.png? [y]es, [n]o, [A]ll, [N]one, [r]ename: y\n",
            "y\n",
            "replace ./emojis/1F469-1F3FE-200D-2764-FE0F-200D-1F48B-200D-1F469-1F3FE.png? [y]es, [n]o, [A]ll, [N]one, [r]ename: replace ./emojis/271D.png? [y]es, [n]o, [A]ll, [N]one, [r]ename: y\n",
            "replace ./emojis/E250.png? [y]es, [n]o, [A]ll, [N]one, [r]ename: y\n",
            "replace ./emojis/1F409.png? [y]es, [n]o, [A]ll, [N]one, [r]ename: y\n",
            "replace ./emojis/1F43C.png? [y]es, [n]o, [A]ll, [N]one, [r]ename: y\n",
            "replace ./emojis/1F3C4.png? [y]es, [n]o, [A]ll, [N]one, [r]ename: y\n",
            "replace ./emojis/1F4E2.png? [y]es, [n]o, [A]ll, [N]one, [r]ename: y\n",
            "replace ./emojis/1F35E.png? [y]es, [n]o, [A]ll, [N]one, [r]ename: y\n",
            "\n",
            "replace ./emojis/1F9D1-1F3FE-200D-2764-FE0F-200D-1F9D1-1F3FC.png? [y]es, [n]o, [A]ll, [N]one, [r]ename: error:  invalid response [{ENTER}]\n",
            "replace ./emojis/1F9D1-1F3FE-200D-2764-FE0F-200D-1F9D1-1F3FC.png? [y]es, [n]o, [A]ll, [N]one, [r]ename: y\n",
            "replace ./emojis/E2CA.png? [y]es, [n]o, [A]ll, [N]one, [r]ename: yy\n",
            "replace ./emojis/1F477-1F3FB-200D-2642-FE0F.png? [y]es, [n]o, [A]ll, [N]one, [r]ename: y\n",
            "replace ./emojis/E08C.png? [y]es, [n]o, [A]ll, [N]one, [r]ename: y\n",
            "replace ./emojis/1F46E-1F3FE-200D-2640-FE0F.png? [y]es, [n]o, [A]ll, [N]one, [r]ename: y\n",
            "replace ./emojis/1FAF5.png? [y]es, [n]o, [A]ll, [N]one, [r]ename: y\n",
            "replace ./emojis/1F93D-1F3FC-200D-2640-FE0F.png? [y]es, [n]o, [A]ll, [N]one, [r]ename: y\n",
            "replace ./emojis/1F192.png? [y]es, [n]o, [A]ll, [N]one, [r]ename: y\n",
            "y\n",
            "replace ./emojis/1F926-1F3FD-200D-2642-FE0F.png? [y]es, [n]o, [A]ll, [N]one, [r]ename: replace ./emojis/1FAF1-1F3FF-200D-1FAF2-1F3FD.png? [y]es, [n]o, [A]ll, [N]one, [r]ename: y\n",
            "replace ./emojis/1FAF5-1F3FC.png? [y]es, [n]o, [A]ll, [N]one, [r]ename: y\n",
            "replace ./emojis/E085.png? [y]es, [n]o, [A]ll, [N]one, [r]ename: y\n",
            "replace ./emojis/1F476-1F3FC.png? [y]es, [n]o, [A]ll, [N]one, [r]ename: y\n",
            "replace ./emojis/1F9DC-1F3FF.png? [y]es, [n]o, [A]ll, [N]one, [r]ename: y\n",
            "replace ./emojis/1F469-1F3FC-200D-1F91D-200D-1F469-1F3FB.png? [y]es, [n]o, [A]ll, [N]one, [r]ename: y\n",
            "replace ./emojis/1F448-1F3FF.png? [y]es, [n]o, [A]ll, [N]one, [r]ename: y\n",
            "y\n",
            "replace ./emojis/E091.png? [y]es, [n]o, [A]ll, [N]one, [r]ename: replace ./emojis/1F481-1F3FF.png? [y]es, [n]o, [A]ll, [N]one, [r]ename: y\n",
            "replace ./emojis/1F9D1-1F3FF-200D-2764-FE0F-200D-1F9D1-1F3FE.png? [y]es, [n]o, [A]ll, [N]one, [r]ename: y\n",
            "replace ./emojis/1F623.png? [y]es, [n]o, [A]ll, [N]one, [r]ename: y\n",
            "replace ./emojis/1F1EC-1F1FE.png? [y]es, [n]o, [A]ll, [N]one, [r]ename: y\n",
            "y\n",
            "replace ./emojis/1F9D2-1F3FD.png? [y]es, [n]o, [A]ll, [N]one, [r]ename: replace ./emojis/25FE.png? [y]es, [n]o, [A]ll, [N]one, [r]ename: y\n",
            "replace ./emojis/1F64E-200D-2642-FE0F.png? [y]es, [n]o, [A]ll, [N]one, [r]ename: \n",
            "error:  invalid response [{ENTER}]\n",
            "replace ./emojis/1F64E-200D-2642-FE0F.png? [y]es, [n]o, [A]ll, [N]one, [r]ename: yy\n",
            "replace ./emojis/E0B1.png? [y]es, [n]o, [A]ll, [N]one, [r]ename: \n",
            "y\n",
            "error:  invalid response [{ENTER}]\n",
            "replace ./emojis/E0B1.png? [y]es, [n]o, [A]ll, [N]one, [r]ename: replace ./emojis/E0C5.png? [y]es, [n]o, [A]ll, [N]one, [r]ename: yy\n",
            "replace ./emojis/1F1F1-1F1FA.png? [y]es, [n]o, [A]ll, [N]one, [r]ename: y\n",
            "replace ./emojis/1F469-1F3FC-200D-2764-FE0F-200D-1F469-1F3FC.png? [y]es, [n]o, [A]ll, [N]one, [r]ename: y\n",
            "replace ./emojis/1F637.png? [y]es, [n]o, [A]ll, [N]one, [r]ename: y\n",
            "replace ./emojis/E05D.png? [y]es, [n]o, [A]ll, [N]one, [r]ename: y\n",
            "replace ./emojis/1F62E.png? [y]es, [n]o, [A]ll, [N]one, [r]ename: y\n",
            "replace ./emojis/1F1EC-1F1F3.png? [y]es, [n]o, [A]ll, [N]one, [r]ename: y\n",
            "replace ./emojis/1F469-1F3FB-200D-2764-FE0F-200D-1F48B-200D-1F468-1F3FE.png? [y]es, [n]o, [A]ll, [N]one, [r]ename: y\n",
            "replace ./emojis/1F64E-1F3FF-200D-2642-FE0F.png? [y]es, [n]o, [A]ll, [N]one, [r]ename: y\n",
            "replace ./emojis/E046.png? [y]es, [n]o, [A]ll, [N]one, [r]ename: y\n",
            "replace ./emojis/1F936-1F3FB.png? [y]es, [n]o, [A]ll, [N]one, [r]ename: A\n",
            "Requirement already satisfied: tensorflow==2.10.0 in /usr/local/lib/python3.10/dist-packages (2.10.0)\n",
            "Requirement already satisfied: absl-py>=1.0.0 in /usr/local/lib/python3.10/dist-packages (from tensorflow==2.10.0) (1.4.0)\n",
            "Requirement already satisfied: astunparse>=1.6.0 in /usr/local/lib/python3.10/dist-packages (from tensorflow==2.10.0) (1.6.3)\n",
            "Requirement already satisfied: flatbuffers>=2.0 in /usr/local/lib/python3.10/dist-packages (from tensorflow==2.10.0) (23.5.26)\n",
            "Requirement already satisfied: gast<=0.4.0,>=0.2.1 in /usr/local/lib/python3.10/dist-packages (from tensorflow==2.10.0) (0.4.0)\n",
            "Requirement already satisfied: google-pasta>=0.1.1 in /usr/local/lib/python3.10/dist-packages (from tensorflow==2.10.0) (0.2.0)\n",
            "Requirement already satisfied: grpcio<2.0,>=1.24.3 in /usr/local/lib/python3.10/dist-packages (from tensorflow==2.10.0) (1.60.0)\n",
            "Requirement already satisfied: h5py>=2.9.0 in /usr/local/lib/python3.10/dist-packages (from tensorflow==2.10.0) (3.9.0)\n",
            "Requirement already satisfied: keras<2.11,>=2.10.0 in /usr/local/lib/python3.10/dist-packages (from tensorflow==2.10.0) (2.10.0)\n",
            "Requirement already satisfied: keras-preprocessing>=1.1.1 in /usr/local/lib/python3.10/dist-packages (from tensorflow==2.10.0) (1.1.2)\n",
            "Requirement already satisfied: libclang>=13.0.0 in /usr/local/lib/python3.10/dist-packages (from tensorflow==2.10.0) (16.0.6)\n",
            "Requirement already satisfied: numpy>=1.20 in /usr/local/lib/python3.10/dist-packages (from tensorflow==2.10.0) (1.23.5)\n",
            "Requirement already satisfied: opt-einsum>=2.3.2 in /usr/local/lib/python3.10/dist-packages (from tensorflow==2.10.0) (3.3.0)\n",
            "Requirement already satisfied: packaging in /usr/local/lib/python3.10/dist-packages (from tensorflow==2.10.0) (23.2)\n",
            "Requirement already satisfied: protobuf<3.20,>=3.9.2 in /usr/local/lib/python3.10/dist-packages (from tensorflow==2.10.0) (3.19.6)\n",
            "Requirement already satisfied: setuptools in /usr/local/lib/python3.10/dist-packages (from tensorflow==2.10.0) (67.7.2)\n",
            "Requirement already satisfied: six>=1.12.0 in /usr/local/lib/python3.10/dist-packages (from tensorflow==2.10.0) (1.16.0)\n",
            "Requirement already satisfied: tensorboard<2.11,>=2.10 in /usr/local/lib/python3.10/dist-packages (from tensorflow==2.10.0) (2.10.1)\n",
            "Requirement already satisfied: tensorflow-io-gcs-filesystem>=0.23.1 in /usr/local/lib/python3.10/dist-packages (from tensorflow==2.10.0) (0.34.0)\n",
            "Requirement already satisfied: tensorflow-estimator<2.11,>=2.10.0 in /usr/local/lib/python3.10/dist-packages (from tensorflow==2.10.0) (2.10.0)\n",
            "Requirement already satisfied: termcolor>=1.1.0 in /usr/local/lib/python3.10/dist-packages (from tensorflow==2.10.0) (2.4.0)\n",
            "Requirement already satisfied: typing-extensions>=3.6.6 in /usr/local/lib/python3.10/dist-packages (from tensorflow==2.10.0) (4.5.0)\n",
            "Requirement already satisfied: wrapt>=1.11.0 in /usr/local/lib/python3.10/dist-packages (from tensorflow==2.10.0) (1.14.1)\n",
            "Requirement already satisfied: wheel<1.0,>=0.23.0 in /usr/local/lib/python3.10/dist-packages (from astunparse>=1.6.0->tensorflow==2.10.0) (0.42.0)\n",
            "Requirement already satisfied: google-auth<3,>=1.6.3 in /usr/local/lib/python3.10/dist-packages (from tensorboard<2.11,>=2.10->tensorflow==2.10.0) (2.17.3)\n",
            "Requirement already satisfied: google-auth-oauthlib<0.5,>=0.4.1 in /usr/local/lib/python3.10/dist-packages (from tensorboard<2.11,>=2.10->tensorflow==2.10.0) (0.4.6)\n",
            "Requirement already satisfied: markdown>=2.6.8 in /usr/local/lib/python3.10/dist-packages (from tensorboard<2.11,>=2.10->tensorflow==2.10.0) (3.5.1)\n",
            "Requirement already satisfied: requests<3,>=2.21.0 in /usr/local/lib/python3.10/dist-packages (from tensorboard<2.11,>=2.10->tensorflow==2.10.0) (2.31.0)\n",
            "Requirement already satisfied: tensorboard-data-server<0.7.0,>=0.6.0 in /usr/local/lib/python3.10/dist-packages (from tensorboard<2.11,>=2.10->tensorflow==2.10.0) (0.6.1)\n",
            "Requirement already satisfied: tensorboard-plugin-wit>=1.6.0 in /usr/local/lib/python3.10/dist-packages (from tensorboard<2.11,>=2.10->tensorflow==2.10.0) (1.8.1)\n",
            "Requirement already satisfied: werkzeug>=1.0.1 in /usr/local/lib/python3.10/dist-packages (from tensorboard<2.11,>=2.10->tensorflow==2.10.0) (3.0.1)\n",
            "Requirement already satisfied: cachetools<6.0,>=2.0.0 in /usr/local/lib/python3.10/dist-packages (from google-auth<3,>=1.6.3->tensorboard<2.11,>=2.10->tensorflow==2.10.0) (5.3.2)\n",
            "Requirement already satisfied: pyasn1-modules>=0.2.1 in /usr/local/lib/python3.10/dist-packages (from google-auth<3,>=1.6.3->tensorboard<2.11,>=2.10->tensorflow==2.10.0) (0.3.0)\n",
            "Requirement already satisfied: rsa<5,>=3.1.4 in /usr/local/lib/python3.10/dist-packages (from google-auth<3,>=1.6.3->tensorboard<2.11,>=2.10->tensorflow==2.10.0) (4.9)\n",
            "Requirement already satisfied: requests-oauthlib>=0.7.0 in /usr/local/lib/python3.10/dist-packages (from google-auth-oauthlib<0.5,>=0.4.1->tensorboard<2.11,>=2.10->tensorflow==2.10.0) (1.3.1)\n",
            "Requirement already satisfied: charset-normalizer<4,>=2 in /usr/local/lib/python3.10/dist-packages (from requests<3,>=2.21.0->tensorboard<2.11,>=2.10->tensorflow==2.10.0) (3.3.2)\n",
            "Requirement already satisfied: idna<4,>=2.5 in /usr/local/lib/python3.10/dist-packages (from requests<3,>=2.21.0->tensorboard<2.11,>=2.10->tensorflow==2.10.0) (3.6)\n",
            "Requirement already satisfied: urllib3<3,>=1.21.1 in /usr/local/lib/python3.10/dist-packages (from requests<3,>=2.21.0->tensorboard<2.11,>=2.10->tensorflow==2.10.0) (2.0.7)\n",
            "Requirement already satisfied: certifi>=2017.4.17 in /usr/local/lib/python3.10/dist-packages (from requests<3,>=2.21.0->tensorboard<2.11,>=2.10->tensorflow==2.10.0) (2023.11.17)\n",
            "Requirement already satisfied: MarkupSafe>=2.1.1 in /usr/local/lib/python3.10/dist-packages (from werkzeug>=1.0.1->tensorboard<2.11,>=2.10->tensorflow==2.10.0) (2.1.3)\n",
            "Requirement already satisfied: pyasn1<0.6.0,>=0.4.6 in /usr/local/lib/python3.10/dist-packages (from pyasn1-modules>=0.2.1->google-auth<3,>=1.6.3->tensorboard<2.11,>=2.10->tensorflow==2.10.0) (0.5.1)\n",
            "Requirement already satisfied: oauthlib>=3.0.0 in /usr/local/lib/python3.10/dist-packages (from requests-oauthlib>=0.7.0->google-auth-oauthlib<0.5,>=0.4.1->tensorboard<2.11,>=2.10->tensorflow==2.10.0) (3.2.2)\n"
          ]
        }
      ],
      "source": [
        "!wget https://github.com/hfg-gmuend/openmoji/releases/latest/download/openmoji-72x72-color.zip\n",
        "!mkdir emojis\n",
        "!unzip -q openmoji-72x72-color.zip -d ./emojis\n",
        "!pip install tensorflow==2.10.0"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "PsBFzZWNxnFN",
        "outputId": "87828b4b-130f-4a1c-c661-09314eef3883"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "Check if we are using TensorFlow 2.4\n",
            "Using TensorFlow version 2.10.0\n"
          ]
        }
      ],
      "source": [
        "%matplotlib inline\n",
        "\n",
        "import tensorflow as tf\n",
        "import numpy as np\n",
        "import matplotlib.pyplot as plt\n",
        "import os\n",
        "\n",
        "from PIL import Image, ImageDraw\n",
        "from tensorflow.keras.layers import Input, Dense, Flatten, Conv2D, MaxPool2D, BatchNormalization, Dropout\n",
        "\n",
        "print('Check if we are using TensorFlow 2.4')\n",
        "print('Using TensorFlow version', tf.__version__)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 660
        },
        "id": "9_cD7ll7gAnD",
        "outputId": "e24377ad-8e51-44a5-f20d-158a2198eb71"
      },
      "outputs": [
        {
          "data": {
            "image/png": 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",
            "text/plain": [
              "<Figure size 900x900 with 9 Axes>"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        }
      ],
      "source": [
        "emojis = {\n",
        "    0: {'name': 'happy', 'file': '1F642.png'},\n",
        "    1: {'name': 'laughing', 'file': '1F602.png'},\n",
        "    2: {'name': 'skeptical', 'file': '1F928.png'},\n",
        "    3: {'name': 'sad', 'file': '1F630.png'},\n",
        "    4: {'name': 'cool', 'file': '1F60E.png'},\n",
        "    5: {'name': 'whoa', 'file': '1F62F.png'},\n",
        "    6: {'name': 'crying', 'file': '1F62D.png'},\n",
        "    7: {'name': 'puking', 'file': '1F92E.png'},\n",
        "    8: {'name': 'nervous', 'file': '1F62C.png'}\n",
        "}\n",
        "\n",
        "plt.figure(figsize=(9, 9))\n",
        "\n",
        "for i, (j, e) in enumerate(emojis.items()):\n",
        "    plt.subplot(3, 3, i + 1)\n",
        "    plt.imshow(plt.imread(os.path.join('emojis', e['file'])))\n",
        "    plt.xlabel(e['name'])\n",
        "    plt.xticks([])\n",
        "    plt.yticks([])\n",
        "plt.show()"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "C0gSTjKDkJ9y"
      },
      "source": [
        "## Task 3: Create Examples"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "rn91bMsseWJu"
      },
      "outputs": [],
      "source": [
        "for class_id, values in emojis.items():\n",
        "    png_file = Image.open(os.path.join('emojis', values['file'])).convert('RGBA')\n",
        "    png_file.load()\n",
        "    new_file = Image.new(\"RGB\", png_file.size, (255, 255, 255))\n",
        "    new_file.paste(png_file, mask=png_file.split()[3])\n",
        "    emojis[class_id]['image'] = new_file"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "bBZgOVsUke6o",
        "outputId": "3b9aad14-d813-4b34-8efe-8cb91feb417f"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "{0: {'name': 'happy',\n",
              "  'file': '1F642.png',\n",
              "  'image': <PIL.Image.Image image mode=RGB size=72x72>},\n",
              " 1: {'name': 'laughing',\n",
              "  'file': '1F602.png',\n",
              "  'image': <PIL.Image.Image image mode=RGB size=72x72>},\n",
              " 2: {'name': 'skeptical',\n",
              "  'file': '1F928.png',\n",
              "  'image': <PIL.Image.Image image mode=RGB size=72x72>},\n",
              " 3: {'name': 'sad',\n",
              "  'file': '1F630.png',\n",
              "  'image': <PIL.Image.Image image mode=RGB size=72x72>},\n",
              " 4: {'name': 'cool',\n",
              "  'file': '1F60E.png',\n",
              "  'image': <PIL.Image.Image image mode=RGB size=72x72>},\n",
              " 5: {'name': 'whoa',\n",
              "  'file': '1F62F.png',\n",
              "  'image': <PIL.Image.Image image mode=RGB size=72x72>},\n",
              " 6: {'name': 'crying',\n",
              "  'file': '1F62D.png',\n",
              "  'image': <PIL.Image.Image image mode=RGB size=72x72>},\n",
              " 7: {'name': 'puking',\n",
              "  'file': '1F92E.png',\n",
              "  'image': <PIL.Image.Image image mode=RGB size=72x72>},\n",
              " 8: {'name': 'nervous',\n",
              "  'file': '1F62C.png',\n",
              "  'image': <PIL.Image.Image image mode=RGB size=72x72>}}"
            ]
          },
          "execution_count": 6,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "emojis"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "8xz9sL75lFLW"
      },
      "outputs": [],
      "source": [
        "def create_example():\n",
        "  class_id = np.random.randint(0, 9)\n",
        "  image = np.ones((144, 144, 3)) * 255\n",
        "  row = np.random.randint(0, 72)\n",
        "  col = np.random.randint(0, 72)\n",
        "  image[row:row+72, col:col+72,:]=np.array(emojis[class_id]['image'])\n",
        "  return image.astype('uint8'), class_id,(row+10)/144, (col +10)/144\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 451
        },
        "id": "BxyRweUqyFkF",
        "outputId": "f70a88e5-531f-49dd-94a5-e97ff949966d"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "<matplotlib.image.AxesImage at 0x7ae511821330>"
            ]
          },
          "execution_count": 8,
          "metadata": {},
          "output_type": "execute_result"
        },
        {
          "data": {
            "image/png": 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",
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        }
      ],
      "source": [
        "image,class_id, row, col = create_example()\n",
        "plt.imshow(image)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "yAriAzdGkO49"
      },
      "source": [
        "## Task 4: Plot Bounding Boxes"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "TSSY93pHm1Z5"
      },
      "outputs": [],
      "source": [
        "def plot_bounding_box(image, gt_coords, pred_coords=[], norm = False):\n",
        "  if norm:\n",
        "    image *= 255\n",
        "    image = image.astype('uint8')\n",
        "  image = Image.fromarray(image)\n",
        "  draw = ImageDraw.Draw(image)\n",
        "\n",
        "  row,col = gt_coords\n",
        "  row *= 144\n",
        "  col *= 144\n",
        "  draw.rectangle((col, row, col+52, row+52), outline = 'green',width=3)\n",
        "\n",
        "  if len(pred_coords) == 2:\n",
        "    row,col = pred_coords\n",
        "    row *= 144\n",
        "    col *= 144\n",
        "    draw.rectangle((col, row, col+52, row+52), outline = 'red',width=3)\n",
        "\n",
        "  return image\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 452
        },
        "id": "01TUfno0mTQv",
        "outputId": "164df57e-ab67-40c9-c38e-67aa25bf830a"
      },
      "outputs": [
        {
          "data": {
            "image/png": 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",
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        }
      ],
      "source": [
        "image = plot_bounding_box(image, gt_coords=[row,col])\n",
        "plt.imshow(image)\n",
        "plt.title(emojis[class_id]['name'])\n",
        "plt.show()"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "dHiS285zkSNK"
      },
      "source": [
        "## Task 5: Data Generator"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "gR5AYygBqAVH"
      },
      "outputs": [],
      "source": [
        "def data_generator(batch_size = 16):\n",
        "  while True:\n",
        "    x_batch = np.zeros((batch_size,144,144,3))\n",
        "    y_batch = np.zeros((batch_size,9))\n",
        "    bbox_batch = np.zeros((batch_size,2))\n",
        "\n",
        "    for i in range(0,batch_size):\n",
        "      image, class_id, row, col = create_example()\n",
        "      x_batch[i] = image / 255\n",
        "      y_batch[i, class_id] = 1.0\n",
        "      bbox_batch[i] = np.array([row,col])\n",
        "    yield {'image': x_batch} , {'class_out': y_batch, 'box_out': bbox_batch}\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 452
        },
        "id": "fY3pM-O5sS0H",
        "outputId": "88c9fb6a-214e-443f-c47f-53d08a5107cf"
      },
      "outputs": [
        {
          "data": {
            "image/png": 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",
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        }
      ],
      "source": [
        "example, label = next(data_generator(1))\n",
        "image = example['image'][0]\n",
        "class_id = np.argmax(label['class_out'][0])\n",
        "coords = label['box_out'][0]\n",
        "\n",
        "image = plot_bounding_box(image, coords, norm = True)\n",
        "plt.imshow(image)\n",
        "plt.title(emojis[class_id]['name'])\n",
        "plt.show()"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "JIfAVFDGkVAT"
      },
      "source": [
        "## Task 6: Model"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "jahKrZ9yspGi",
        "outputId": "63b72fd1-415b-4987-abec-91e170833fae"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "Model: \"model\"\n",
            "__________________________________________________________________________________________________\n",
            " Layer (type)                   Output Shape         Param #     Connected to                     \n",
            "==================================================================================================\n",
            " image (InputLayer)             [(None, 144, 144, 3  0           []                               \n",
            "                                )]                                                                \n",
            "                                                                                                  \n",
            " conv2d (Conv2D)                (None, 142, 142, 16  448         ['image[0][0]']                  \n",
            "                                )                                                                 \n",
            "                                                                                                  \n",
            " batch_normalization (BatchNorm  (None, 142, 142, 16  64         ['conv2d[0][0]']                 \n",
            " alization)                     )                                                                 \n",
            "                                                                                                  \n",
            " max_pooling2d (MaxPooling2D)   (None, 71, 71, 16)   0           ['batch_normalization[0][0]']    \n",
            "                                                                                                  \n",
            " conv2d_1 (Conv2D)              (None, 69, 69, 32)   4640        ['max_pooling2d[0][0]']          \n",
            "                                                                                                  \n",
            " batch_normalization_1 (BatchNo  (None, 69, 69, 32)  128         ['conv2d_1[0][0]']               \n",
            " rmalization)                                                                                     \n",
            "                                                                                                  \n",
            " max_pooling2d_1 (MaxPooling2D)  (None, 34, 34, 32)  0           ['batch_normalization_1[0][0]']  \n",
            "                                                                                                  \n",
            " conv2d_2 (Conv2D)              (None, 32, 32, 64)   18496       ['max_pooling2d_1[0][0]']        \n",
            "                                                                                                  \n",
            " batch_normalization_2 (BatchNo  (None, 32, 32, 64)  256         ['conv2d_2[0][0]']               \n",
            " rmalization)                                                                                     \n",
            "                                                                                                  \n",
            " max_pooling2d_2 (MaxPooling2D)  (None, 16, 16, 64)  0           ['batch_normalization_2[0][0]']  \n",
            "                                                                                                  \n",
            " conv2d_3 (Conv2D)              (None, 14, 14, 128)  73856       ['max_pooling2d_2[0][0]']        \n",
            "                                                                                                  \n",
            " batch_normalization_3 (BatchNo  (None, 14, 14, 128)  512        ['conv2d_3[0][0]']               \n",
            " rmalization)                                                                                     \n",
            "                                                                                                  \n",
            " max_pooling2d_3 (MaxPooling2D)  (None, 7, 7, 128)   0           ['batch_normalization_3[0][0]']  \n",
            "                                                                                                  \n",
            " conv2d_4 (Conv2D)              (None, 5, 5, 256)    295168      ['max_pooling2d_3[0][0]']        \n",
            "                                                                                                  \n",
            " batch_normalization_4 (BatchNo  (None, 5, 5, 256)   1024        ['conv2d_4[0][0]']               \n",
            " rmalization)                                                                                     \n",
            "                                                                                                  \n",
            " max_pooling2d_4 (MaxPooling2D)  (None, 2, 2, 256)   0           ['batch_normalization_4[0][0]']  \n",
            "                                                                                                  \n",
            " flatten (Flatten)              (None, 1024)         0           ['max_pooling2d_4[0][0]']        \n",
            "                                                                                                  \n",
            " dense (Dense)                  (None, 256)          262400      ['flatten[0][0]']                \n",
            "                                                                                                  \n",
            " class_out (Dense)              (None, 9)            2313        ['dense[0][0]']                  \n",
            "                                                                                                  \n",
            " box_out (Dense)                (None, 2)            514         ['dense[0][0]']                  \n",
            "                                                                                                  \n",
            "==================================================================================================\n",
            "Total params: 659,819\n",
            "Trainable params: 658,827\n",
            "Non-trainable params: 992\n",
            "__________________________________________________________________________________________________\n"
          ]
        }
      ],
      "source": [
        "input_ = Input(shape = (144,144,3), name = 'image')\n",
        "x = input_\n",
        "for i in range(0, 5):\n",
        "  n_filters = 2**(4+i)\n",
        "  x = Conv2D(n_filters, 3, activation = 'relu')(x)\n",
        "  x = BatchNormalization()(x)\n",
        "  x = MaxPool2D(2)(x)\n",
        "\n",
        "x = Flatten()(x)\n",
        "x = Dense(256, activation = 'relu')(x)\n",
        "\n",
        "class_out = Dense(9, activation = 'softmax', name = 'class_out')(x)\n",
        "box_out = Dense(2, name='box_out')(x)\n",
        "\n",
        "model = tf.keras.models.Model(input_,[class_out, box_out])\n",
        "model.summary()\n"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "287Mj5b8kZ_t"
      },
      "source": [
        "## Task 7: Custom Metric: IoU"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "608R_-1V9QCh"
      },
      "outputs": [],
      "source": [
        "class IoU(tf.keras.metrics.Metric):\n",
        "  def _init_(self, **kwargs):\n",
        "    super(IoU, self)._init_(**kwargs)\n",
        "\n",
        "    self.iou = self.add_weight(name = 'iou', initializer = 'zeros')\n",
        "    self.total_iou = self.add_weight(name = 'total_iou', initializer = 'zeros')\n",
        "    self.num_ex = self.add_weight(name='num_ex',initializer='zeros')\n",
        "\n",
        "  def update_state(self, y_true, y_pred, sample_weight = None):\n",
        "    def get_box(y):\n",
        "      rows, cols = y[:,0],y[:,1]\n",
        "      rows,cols = rows * 144, cols *144\n",
        "      y1, y2 = rows,rows +52\n",
        "      x1,x2 = cols,cols+52\n",
        "      return x1, y1, x2, y2\n",
        "\n",
        "    def get_area(x1, y1, x2, y2):\n",
        "      return tf.math.abs(x2-x1)* tf.math.abs(y2 - y1)\n",
        "\n",
        "    gt_x1, gt_y1, gt_x2, gt_y2 = get_box(y_true)\n",
        "    p_x1, p_y1, p_x2,p_y2 = get_box(y_pred)\n",
        "\n",
        "    i_x1 = tf.maximum(gt_x1, p_x1)\n",
        "    i_y1 = tf.maximum(gt_y1, p_y1)\n",
        "    i_x2 = tf.maximum(gt_x2, p_x2)\n",
        "    i_y2 = tf.maximum(gt_y2, p_y2)\n",
        "\n",
        "    i_area = get_area(i_x1, i_y1, i_x2, i_y2)\n",
        "    u_area = get_area(gt_x1, gt_y1, gt_x2, gt_y2) + get_area(p_x1, p_y1, p_x2, p_y2) - i_area\n",
        "\n",
        "    iou = tf.math.divide(i_area, u_area)\n",
        "    self.num_ex.assign_add(1)\n",
        "    self.total_iou.assign_add(tf.reduce_mean(iou))\n",
        "    self.iou = tf.math.divide(self.total_iou, self.num_ex)\n",
        "\n",
        "  def result(self):\n",
        "    return self.iou\n",
        "\n",
        "  def reset_state(self):\n",
        "    self.iou = self.add_weight(name = 'iou', initializer = 'zeros')\n",
        "    self.total_iou = self.add_weight(name = 'total_iou', initializer = 'zeros')\n",
        "    self.num_ex = self.add_weight(name='num_ex',initializer='zeros')\n",
        "\n"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "Q9Qzo_RpNFaM"
      },
      "source": [
        "## Task 8: Compile the Model"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "jl4KzYM9NEb4"
      },
      "outputs": [],
      "source": [
        "model.compile(\n",
        "    loss={\n",
        "        'class_out': 'categorical_crossentropy',\n",
        "        'box_out': 'mse'\n",
        "    },\n",
        "    optimizer = tf.keras.optimizers.Adam(learning_rate = 1e-3),\n",
        "    metrics = {\n",
        "        'class_out':'accuracy',\n",
        "        'box_out': IoU(name='iou')\n",
        "    }\n",
        ")"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "TgorrihHLZox"
      },
      "source": [
        "## Task 9: Custom Callback: Model Testing"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "Di5DItY5vuu1"
      },
      "outputs": [],
      "source": [
        "def test_model(model, test_datagen):\n",
        "  exmaple, label = next(test_datagen)\n",
        "  x = example['image']\n",
        "  y = label['class_out']\n",
        "  box = label['box_out']\n",
        "\n",
        "  pred_y, pred_box = model.predict(x)\n",
        "\n",
        "  pred_coords = pred_box[0]\n",
        "  gt_coords = box[0]\n",
        "  pred_class = np.argmax(pred_y[0])\n",
        "  image = x[0]\n",
        "\n",
        "  gt = emojis[np.argmax(y[0])]['name']\n",
        "  pred_class_name = emojis[pred_class]['name']\n",
        "\n",
        "  image = plot_bounding_box(image, gt_coords, pred_coords, norm = True)\n",
        "  color = 'green' if gt == pred_class_name else 'red'\n",
        "\n",
        "  plt.imshow(image)\n",
        "  plt.xlabel(f'Pred: {pred_class_name}',color = color)\n",
        "  plt.ylabel(f'GT: {gt}',color = color)\n",
        "  plt.xticks([])\n",
        "  plt.yticks([])"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "xR3C5zQ_LZox"
      },
      "outputs": [],
      "source": [
        "def test(model):\n",
        "  test_datagen = data_generator(1)\n",
        "\n",
        "  plt.figure(figsize=(16,4))\n",
        "\n",
        "  for i in range(0,6):\n",
        "    plt.subplot(1,6,i+1)\n",
        "    test_model(model,test_datagen)\n",
        "  plt.show()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 227
        },
        "id": "_9UgYrTILZox",
        "outputId": "326d1ef2-c802-4f2e-9a3e-e534c70e5f0a"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "1/1 [==============================] - 0s 499ms/step\n",
            "1/1 [==============================] - 0s 69ms/step\n",
            "1/1 [==============================] - 0s 102ms/step\n",
            "1/1 [==============================] - 0s 86ms/step\n",
            "1/1 [==============================] - 0s 128ms/step\n",
            "1/1 [==============================] - 0s 80ms/step\n"
          ]
        },
        {
          "data": {
            "image/png": 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",
            "text/plain": [
              "<Figure size 1600x400 with 6 Axes>"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        }
      ],
      "source": [
        "test(model)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "LDznD1EjkOAV"
      },
      "outputs": [],
      "source": [
        "class showTestImages(tf.keras.callbacks.Callback):\n",
        "  def on_epoch_end(self, epoch, logs = None):\n",
        "    test(self.model)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "lvaxZOzOkgDN"
      },
      "source": [
        "## Task 10: Model Training"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {},
      "outputs": [],
      "source": [
        "def lr_schedule(epoch,lr):\n",
        "  if (epoch + 1) % 5 == 0:\n",
        "    lr *= 0.2\n",
        "  return max(lr,3e-7)\n",
        "\n",
        "\n",
        "\n",
        "\n",
        "_ = model.fit(\n",
        "    data_generator(),\n",
        "    epochs = 50,\n",
        "    steps_per_epoch = 500,\n",
        "    callbacks = [\n",
        "        showTestImages(),\n",
        "        tf.keras.callbacks.EarlyStopping(monitor = 'box_out_iou', patience = 3, mode = 'max'),\n",
        "        tf.keras.callbacks.LearningRateScheduler(lr_schedule)\n",
        "    ]\n",
        ")\n",
        "\n",
        "_ = model.fit(\n",
        "    data_generator(),\n",
        "    epochs = 50,\n",
        "    steps_per_epoch = 500,\n",
        "    callbacks = [\n",
        "        showTestImages(),\n",
        "        tf.keras.callbacks.EarlyStopping(monitor = 'box_out_iou', patience = 3, mode = 'max'),\n",
        "        tf.keras.callbacks.LearningRateScheduler(lr_schedule)\n",
        "    ]\n",
        ")"
      ]
    }
  ],
  "metadata": {
    "colab": {
      "include_colab_link": true,
      "provenance": []
    },
    "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": "3.8.5"
    }
  },
  "nbformat": 4,
  "nbformat_minor": 0
}