dataset_maker_v2.ipynb

{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "name": "dataset-maker-v2.ipynb",
      "provenance": [],
      "collapsed_sections": []
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "language_info": {
      "name": "python"
    }
  },
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "cxAbe5eFg80g"
      },
      "source": [
        "# Dataset Maker - Six Shapes\n",
        "More info: https://github.com/reevald/MathEdu\n",
        "## Dataset Information\n",
        "\n",
        "- The data set consists of 6 classes, namely circle, kite, parallelogram, square, trapezoid, triangle.\n",
        "- Each class consists of 4000 images with 224x224x3 pixels\n",
        "- Train:Validation:Test ~ 6:1:1 ~ 3000:500:500"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "PjrepC8IiIDI"
      },
      "source": [
        "## Import Libraries"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "1mQ5TnpcV5px"
      },
      "source": [
        "import os\n",
        "import zipfile\n",
        "import random\n",
        "import math\n",
        "from google.colab import files\n",
        "from PIL import Image, ImageDraw"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "jnQ-L_KEiLvG"
      },
      "source": [
        "## Folder preparation"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "sFgkgf5YjZOA"
      },
      "source": [
        "label = ['circle','kite','parallelogram','square','trapezoid','triangle']\n",
        "base_dir = '/tmp/six-shapes'\n",
        "train_dir = os.path.join(base_dir, 'train')\n",
        "val_dir = os.path.join(base_dir, 'val')\n",
        "test_dir = os.path.join(base_dir, 'test')"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "uVmTkq40EVZq",
        "outputId": "c5436ef1-8333-480b-fa6a-97b5ea74d577"
      },
      "source": [
        "# Create directory\n",
        "try:\n",
        "  os.mkdir(base_dir)\n",
        "  for par_dir in [train_dir, val_dir, test_dir]:\n",
        "    os.mkdir(par_dir)\n",
        "    for ch_dir in [os.path.join(par_dir, lb) for lb in label]:\n",
        "      os.mkdir(ch_dir)\n",
        "  print('\\nCreate directory successfully!')\n",
        "except OSError as err:\n",
        "  print('\\nUnable create directory, {}'.format(err))"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "\n",
            "Create directory successfully!\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "jth0wDIAiWgz"
      },
      "source": [
        "## Shape Handler\n",
        "Reference:  \n",
        "- https://pillow.readthedocs.io/en/stable/handbook/concepts.html#coordinate-system\n",
        "- https://pillow.readthedocs.io/en/stable/reference/ImageDraw.html\n",
        "- https://pillow.readthedocs.io/en/stable/handbook/concepts.html#concept-modes\n",
        "- https://pillow.readthedocs.io/en/stable/reference/Image.html#PIL.Image.new"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "l0KeazCaGJda"
      },
      "source": [
        "# global parameter\n",
        "size_img = (224, 224)\n",
        "list_color_rgb = [\n",
        "    (0, 0, 0), #black\n",
        "    (255, 0, 0), #red\n",
        "    (160, 32, 255), #purple\n",
        "    (0, 32, 255), #blue\n",
        "    (0, 192, 0), #green\n",
        "    (255, 160, 16) #orange\n",
        "]\n",
        "weights_color = [0.167, 0.167, 0.167, 0.167, 0.167, 0.167]"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "DYQviKpJnbzO"
      },
      "source": [
        "### Circle"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "xbS49ZU_PGhR"
      },
      "source": [
        "def createCircle(width_box, height_box, color, size_img, width_line, rotate, path_file, show):\n",
        "\n",
        "  # center box position\n",
        "  # (x0, y0) = coordinate upper left of box\n",
        "  # (x1, y1) = coordinate bottom right of box\n",
        "  # size_img = (width_canvas, height_canvas)\n",
        "\n",
        "  x0 = math.floor((size_img[0] - width_box) / 2)\n",
        "  y0 = math.floor((size_img[1] - height_box) / 2)\n",
        "\n",
        "  x1 = x0 + width_box\n",
        "  y1 = y0 + height_box\n",
        "\n",
        "  im = Image.new(\n",
        "      mode='RGB', # 3 channel (0-255)\n",
        "      size=size_img,\n",
        "      color=(255,255,255) # white background\n",
        "  )\n",
        "\n",
        "  draw = ImageDraw.Draw(im)\n",
        "\n",
        "  draw.ellipse(\n",
        "      xy=[(x0, y0), (x1, y1)],\n",
        "      fill=None,\n",
        "      outline=color,\n",
        "      width=width_line\n",
        "  )\n",
        "\n",
        "  im = im.rotate(rotate, fillcolor=(255,255,255))\n",
        "  im.save(path_file)\n",
        "\n",
        "  if show is True:\n",
        "    return im\n"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "VxEk9vluHikk"
      },
      "source": [
        "Test random circle"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 241
        },
        "id": "gKc1JQvucUzS",
        "outputId": "d0f13f23-9433-46b4-890b-dad4e2aa038a"
      },
      "source": [
        "width_box = random.randrange(70, 200)\n",
        "height_box = random.randrange(70, 200)\n",
        "rotate = random.randrange(-40, 40)\n",
        "\n",
        "# Test random circle size\n",
        "createCircle(\n",
        "    width_box=width_box,\n",
        "    height_box=height_box,\n",
        "    color=list_color_rgb[4],\n",
        "    size_img=size_img,\n",
        "    width_line=10,\n",
        "    rotate=rotate,\n",
        "    path_file='/tmp/sample-circle.png',\n",
        "    show=True\n",
        ")"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "image/png": "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\n",
            "text/plain": [
              "<PIL.Image.Image image mode=RGB size=224x224 at 0x7F0227AB3790>"
            ]
          },
          "metadata": {},
          "execution_count": 45
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "c5FNIgHjoAPS"
      },
      "source": [
        "### Kite"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "MQdll52mEown"
      },
      "source": [
        "def createKite(diag_horz, diag_vert, list_4_color, size_img, width_line, rotate, path_file, show):\n",
        "\n",
        "  im = Image.new(\n",
        "      mode='RGB',\n",
        "      size=size_img,\n",
        "      color=(255,255,255)\n",
        "  )\n",
        "\n",
        "  # coord y point on diagonal vertical\n",
        "  top_diag_vert = math.floor((size_img[1] - diag_vert) / 2)\n",
        "  mid_diag_vert = math.floor(size_img[1] / 2)\n",
        "  bot_diag_vert = size_img[1] - top_diag_vert\n",
        "\n",
        "  # buff for : top_diag_vert != intercept_diag != mid_diag_vert\n",
        "  buff = 10\n",
        "  intercept_diag = random.randrange(top_diag_vert + 2 * buff, mid_diag_vert - buff)\n",
        "\n",
        "  # coord x point on diagonal horizontal\n",
        "  left_diag_horz = math.floor((size_img[0] - diag_horz) / 2)\n",
        "  mid_diag_horz = math.floor(size_img[0] / 2)\n",
        "  right_diag_horz = size_img[0] - left_diag_horz\n",
        "\n",
        "  draw = ImageDraw.Draw(im)\n",
        "\n",
        "  point = [\n",
        "      (left_diag_horz, intercept_diag),\n",
        "      (mid_diag_horz, top_diag_vert),\n",
        "      (right_diag_horz, intercept_diag),\n",
        "      (mid_diag_horz, bot_diag_vert)\n",
        "  ]\n",
        "\n",
        "  for i,p in enumerate(point):\n",
        "    j = 0 if (i == 3) else i + 1\n",
        "    draw.line(\n",
        "        xy=[point[i], point[j]],\n",
        "        fill=list_4_color[i],\n",
        "        width=width_line\n",
        "    )\n",
        "    draw.ellipse(\n",
        "        xy=(p[0] - 4, p[1] - 4, p[0]  + 4, p[1] + 4),\n",
        "        fill=list_4_color[i]\n",
        "    )\n",
        "    \n",
        "  im = im.rotate(rotate, fillcolor=(255,255,255))\n",
        "  im.save(path_file)\n",
        "\n",
        "  if show is True:\n",
        "    return im"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "rumcUyZKIa7M"
      },
      "source": [
        "Test random kite"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 241
        },
        "id": "IR6ufmjGTrnN",
        "outputId": "7f01ab27-d2a3-47d4-a9ea-e6b58a7362c0"
      },
      "source": [
        "diag_vert = random.randrange(130, 200)\n",
        "diag_horz = random.randrange(70, 130)\n",
        "rotate = random.randrange(-20, 20)\n",
        "\n",
        "createKite(\n",
        "    diag_horz=diag_horz,\n",
        "    diag_vert=diag_vert,\n",
        "    list_4_color=[color for color in list_color_rgb[0:4]],\n",
        "    size_img=size_img,\n",
        "    width_line=10,\n",
        "    rotate=rotate,\n",
        "    path_file='/tmp/sample-kite.png',\n",
        "    show=True\n",
        ")"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "image/png": "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\n",
            "text/plain": [
              "<PIL.Image.Image image mode=RGB size=224x224 at 0x7F0227AAAD10>"
            ]
          },
          "metadata": {},
          "execution_count": 69
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "bz0havaroCpZ"
      },
      "source": [
        "### Parallelogram"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Q-Rve-G0qBTN"
      },
      "source": [
        "def createParallelogram(top_horz, left_slope, angle_deg, flip, list_4_color, size_img, width_line, rotate, path_file, show):\n",
        "\n",
        "  im = Image.new(\n",
        "      mode='RGB',\n",
        "      size=size_img,\n",
        "      color=(255,255,255)\n",
        "  )\n",
        "\n",
        "  angle_top_left = math.radians(angle_deg) # interval deg (0, 90) or rad (0, pi/2)\n",
        "\n",
        "  # search height and width parallelogram to determine size box frame shape\n",
        "  proj_slope_on_top = left_slope * math.cos(angle_top_left)\n",
        "  height_shape = left_slope * math.sin(angle_top_left)\n",
        "  width_shape = proj_slope_on_top + top_horz\n",
        "\n",
        "  # determine xy coordinate box frame shape\n",
        "  x_left_shape = math.floor((size_img[0] - width_shape) / 2)\n",
        "  y_top_shape = math.floor((size_img[1] - height_shape) / 2)\n",
        "  x_right_shape = size_img[0] - x_left_shape\n",
        "  y_bot_shape = size_img[1] - y_top_shape\n",
        "\n",
        "  point = [\n",
        "      (x_left_shape, y_top_shape),\n",
        "      (x_left_shape + top_horz, y_top_shape),\n",
        "      (x_right_shape, y_bot_shape),\n",
        "      (x_right_shape - top_horz, y_bot_shape)\n",
        "  ]\n",
        "\n",
        "  draw = ImageDraw.Draw(im)\n",
        "\n",
        "  for i,p in enumerate(point):\n",
        "      j = 0 if (i == 3) else i + 1\n",
        "      draw.line(\n",
        "          xy=[point[i], point[j]],\n",
        "          fill=list_4_color[i],\n",
        "          width=width_line\n",
        "      )\n",
        "      draw.ellipse(\n",
        "          xy=(p[0] - 4, p[1] - 4, p[0]  + 4, p[1] + 4),\n",
        "          fill=list_4_color[i]\n",
        "      )\n",
        "\n",
        "  im = im.rotate(rotate, fillcolor=(255,255,255))\n",
        "  if flip is True:\n",
        "    im = im.transpose(method=Image.FLIP_LEFT_RIGHT)\n",
        "\n",
        "  im.save(path_file)\n",
        "  \n",
        "  if show is True:\n",
        "    return im"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "tJvbC3zBIeYA"
      },
      "source": [
        "Test random parallelogram"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 241
        },
        "id": "Eo6w3UCYq4eP",
        "outputId": "b55b9a0d-9ac0-4b21-b21a-1711f12117b2"
      },
      "source": [
        "left_slope = random.randrange(70, 120)\n",
        "top_horz = random.randrange(70, 120)\n",
        "angle_deg = random.randrange(30, 80)\n",
        "rotate = random.randrange(-5, 5)\n",
        "\n",
        "createParallelogram(\n",
        "    top_horz=top_horz,\n",
        "    left_slope=left_slope,\n",
        "    size_img=size_img,\n",
        "    angle_deg=angle_deg,\n",
        "    flip=True,\n",
        "    list_4_color=[color for color in list_color_rgb[0:4]],\n",
        "    width_line=10,\n",
        "    rotate=rotate,\n",
        "    path_file='/tmp/sample-parallelogram.png',\n",
        "    show=True\n",
        ")"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "image/png": "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\n",
            "text/plain": [
              "<PIL.Image.Image image mode=RGB size=224x224 at 0x7F0227B1CC10>"
            ]
          },
          "metadata": {},
          "execution_count": 71
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "EGg5y5oqoI0F"
      },
      "source": [
        "### Square"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "mHP4n3JrzDn8"
      },
      "source": [
        "def createSquare(length_shape, size_img, list_4_color, width_line, rotate, path_file, show):\n",
        "\n",
        "  im = Image.new(\n",
        "      mode='RGB',\n",
        "      size=size_img,\n",
        "      color=(255,255,255)\n",
        "  )\n",
        "\n",
        "  y_top_shape = math.floor((size_img[1] - length_shape) / 2) \n",
        "  y_bot_shape = size_img[1] - y_top_shape\n",
        "\n",
        "  x_left_shape = math.floor((size_img[0] - length_shape) / 2)\n",
        "  x_right_shape = size_img[0] - x_left_shape\n",
        "\n",
        "  point = [\n",
        "      (x_left_shape, y_top_shape),\n",
        "      (x_right_shape, y_top_shape),\n",
        "      (x_right_shape, y_bot_shape),\n",
        "      (x_left_shape, y_bot_shape)\n",
        "  ]\n",
        "\n",
        "  draw = ImageDraw.Draw(im)\n",
        "\n",
        "  for i,p in enumerate(point):\n",
        "      j = 0 if (i == 3) else i + 1\n",
        "      draw.line(\n",
        "          xy=[point[i], point[j]],\n",
        "          fill=list_4_color[i],\n",
        "          width=width_line\n",
        "      )\n",
        "      draw.ellipse(\n",
        "          xy=(p[0] - 4, p[1] - 4, p[0]  + 4, p[1] + 4),\n",
        "          fill=list_4_color[i]\n",
        "      )\n",
        "\n",
        "  im = im.rotate(rotate, fillcolor=(255,255,255))\n",
        "  im.save(path_file)\n",
        "\n",
        "  if show is True:\n",
        "    return im"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "FisHKrHvIyKl"
      },
      "source": [
        "Test random square"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 241
        },
        "id": "_Gat6w2q0xl2",
        "outputId": "52c548e4-d9c4-418e-b571-db89206024ab"
      },
      "source": [
        "length_shape = random.randrange(70, 120)\n",
        "rotate = random.randrange(-10, 10)\n",
        "\n",
        "createSquare(\n",
        "    length_shape=length_shape,\n",
        "    size_img=size_img,\n",
        "    list_4_color=[color for color in list_color_rgb[0:4]],\n",
        "    width_line=10,\n",
        "    rotate=rotate,\n",
        "    path_file='/tmp/sample-square.png',\n",
        "    show=True\n",
        ")"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "image/png": "iVBORw0KGgoAAAANSUhEUgAAAOAAAADgCAIAAACVT/22AAAELUlEQVR4nO3cQVLbQBRFUXeKhcDK2BqsDHaiDEhiKtgNOI71/u9zRhQeIEq3ZPmBPbZtO0CqH3sfAMwIlGgCJZpAiSZQogmUaAIlmkCJJlCiCZRoAiWaQIkmUKIJlGgCJZpAiSZQogmUaAIlmkCJJlCiCZRoAiWaQIkmUKIJlGgCJZpAiSZQogmUaAIlmkCJJlCiCZRoAiWaQIkmUKIJlGgCJZpAiSZQogmUaAIlmkCJJlCiCZRoAiWaQIkmUKIJlGgCJZpAiSZQogmUaAIlmkCJJlCi3e19AFxijPH2xfbxse3E9+oSaLQ/IZ50usQxOjUq0P3NKzynT4NTAr2dy0K87Ce1uYgK9PpuF+ICBHo5Id6AQD9XMsQuz/ICPaoV4ljjddJygdaqkLaBCrGH8oGuGeL2dn+5wO9eL9ClitxavND5F/UCbUmI5xQLtPrlU4jfVSzQE+5/n/LXoHYjQmwxhVYKdDy8yzHDziFuW/vXSZUC3UvE5XBVAj0SYqAVAxViIZ0DFWIDo9ZZHA+zR7eXWx1HjvmLpFIn9yTv6iSaQFurP0IJtLj6T+JzAiWaQIkmUKIJlGitAp2vpFRULNAVp/i1FQuU1Qi0vvkUWnyrFyjRBEo0gRJNoETrFqgptJl6gZpCl1IvUJYi0Bb6TqECJZpAiSZQogmUaA0DNYV2UjJQU+g6SgbKOgTaRdMpVKBEEyjRBEo0gRKtZ6Cm0DaqBmoKXUTVQFmEQJdRcwoVaCMdP8xWoEQTKNEESjSBEq1woPMp1FbfQ+FAWYFAV1JwChVoL+2mUIESTaBEEyjRBEq02oGaQturHSjtCXQx1aZQgbbTawoVKNEESjSBEk2gRCsfqCm0t/KB0ptA11NqChVoR42mUIESTaBEEyjRBEq0/oGaQkvrEKgPs22sQ6A0drf3AfB/bNthjOf74yD6+Ppunx+jylY6tiIHOje/0Wx/D/D85fvsY6ZFzrtAK/l6iBO/Gi1y3gWa6CohTjy+lnmKdw+6p/8dYgNLBDoedr6ICvFiTQLdXvYf5CtVWOT5/dAm0FuqFGJ9Aj1LiAkEulyIj6U2jYUCXS3EN7Vy/GiVQNvXWT3Ec1YJtI2uIZ7T5C9Jhy/83+fTLY7iOlarcKLPFTRhCv0uIX6qT6DJhHgxgV6TEK9OoJcQ4s20CvTqt6FC3F2rQCeepo8KMVafmem9v66jT4fDQYU19QyUNrztmGgCJZpAiSZQogmUaAIlmkCJJlCiCZRoAiWaQIkmUKIJlGgCJZpAiSZQogmUaAIlmkCJJlCiCZRoAiWaQIkmUKIJlGgCJZpAiSZQogmUaAIlmkCJJlCiCZRoAiWaQIkmUKIJlGgCJZpAiSZQogmUaAIlmkCJJlCiCZRoAiWaQIkmUKIJlGgCJZpAiSZQogmUaAIlmkCJJlCi/QTMg6lK65MpEwAAAABJRU5ErkJggg==\n",
            "text/plain": [
              "<PIL.Image.Image image mode=RGB size=224x224 at 0x7F0227AC6490>"
            ]
          },
          "metadata": {},
          "execution_count": 73
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "wl9kefTWoMt1"
      },
      "source": [
        "### Trapezoid"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "XawPXs0g7Npb"
      },
      "source": [
        "def createTrapezoid(top_horz, bot_horz, list_4_color, height_shape, flip, size_img, width_line, rotate, path_file, show):\n",
        "\n",
        "  im = Image.new(\n",
        "      mode='RGB',\n",
        "      size=size_img,\n",
        "      color=(255,255,255)\n",
        "  )\n",
        "\n",
        "  y_top_shape = math.floor((size_img[1] - height_shape) / 2)\n",
        "  y_bot_shape = size_img[1] - y_top_shape\n",
        "\n",
        "  x_left_top_shape = math.floor((size_img[0] - top_horz) / 2)\n",
        "  x_right_top_shape = size_img[0] - x_left_top_shape\n",
        "\n",
        "  x_left_bot_shape = math.floor((size_img[0] - bot_horz) / 2)\n",
        "  x_right_bot_shape = size_img[0] - x_left_bot_shape\n",
        "\n",
        "  point = [\n",
        "      (x_left_top_shape, y_top_shape),\n",
        "      (x_right_top_shape, y_top_shape),\n",
        "      (x_right_bot_shape, y_bot_shape),\n",
        "      (x_left_bot_shape, y_bot_shape)\n",
        "  ]\n",
        "\n",
        "  draw = ImageDraw.Draw(im)\n",
        "\n",
        "  for i,p in enumerate(point):\n",
        "      j = 0 if (i == 3) else i + 1\n",
        "      draw.line(\n",
        "          xy=[point[i], point[j]],\n",
        "          fill=list_4_color[i],\n",
        "          width=width_line\n",
        "      )\n",
        "      draw.ellipse(\n",
        "          xy=(p[0] - 4, p[1] - 4, p[0]  + 4, p[1] + 4),\n",
        "          fill=list_4_color[i]\n",
        "      )\n",
        "\n",
        "  im = im.rotate(rotate, fillcolor=(255,255,255))\n",
        "  if flip is True:\n",
        "    im = im.transpose(method=Image.FLIP_TOP_BOTTOM)\n",
        "\n",
        "  im.save(path_file)\n",
        "\n",
        "  if show is True:\n",
        "    return im"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "PmbqPI76I_K5"
      },
      "source": [
        "Test random trapezoid"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 241
        },
        "id": "U1GtvvzW8cjS",
        "outputId": "438021be-8bdf-465e-9b47-9c05aa8038f5"
      },
      "source": [
        "top_horz = random.randrange(70, 120)\n",
        "bot_horz = random.randrange(top_horz+50, 200)\n",
        "height_shape = random.randrange(50, 150)\n",
        "rotate = random.randrange(-5, 5)\n",
        "\n",
        "createTrapezoid(\n",
        "    top_horz=top_horz,\n",
        "    bot_horz=bot_horz,\n",
        "    list_4_color=[color for color in list_color_rgb[0:4]],\n",
        "    height_shape=height_shape,\n",
        "    size_img=size_img,\n",
        "    flip=True,\n",
        "    width_line=10,\n",
        "    rotate=rotate,\n",
        "    path_file='/tmp/sample-trapezoid.png',\n",
        "    show=True\n",
        ")"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "image/png": "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\n",
            "text/plain": [
              "<PIL.Image.Image image mode=RGB size=224x224 at 0x7F0227B1CA50>"
            ]
          },
          "metadata": {},
          "execution_count": 75
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "GFLHID6BoOwA"
      },
      "source": [
        "### Triangle"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "vKUri6EioQZl"
      },
      "source": [
        "def createTriangle(height_shape, width_shape, list_3_color, size_img, width_line, rotate, path_file, show):\n",
        "\n",
        "  im = Image.new(\n",
        "      mode='RGB',\n",
        "      size=size_img,\n",
        "      color=(255,255,255)\n",
        "  )\n",
        "\n",
        "  y_top_shape = math.floor((size_img[1] - height_shape) / 2)\n",
        "  y_bot_shape = size_img[1] - y_top_shape\n",
        "\n",
        "  x_min_top = math.floor((size_img[0] - (width_shape / 2)) / 2)\n",
        "  x_max_top = size_img[0] - x_min_top\n",
        "  x_top_shape = random.randrange(x_min_top, x_max_top)\n",
        "\n",
        "  x_left_bot_shape = math.floor((size_img[0] - width_shape) / 2)\n",
        "  x_right_bot_shape = size_img[0] - x_left_bot_shape\n",
        "\n",
        "  point = [\n",
        "      (x_left_bot_shape, y_bot_shape),\n",
        "      (x_top_shape, y_top_shape),\n",
        "      (x_right_bot_shape, y_bot_shape)\n",
        "  ]\n",
        "\n",
        "  draw = ImageDraw.Draw(im)\n",
        "\n",
        "  for i,p in enumerate(point):\n",
        "      j = 0 if (i == 2) else i + 1\n",
        "      draw.line(\n",
        "          xy=[point[i], point[j]],\n",
        "          fill=list_3_color[i],\n",
        "          width=width_line\n",
        "      )\n",
        "      draw.ellipse(\n",
        "          xy=(p[0] - 4, p[1] - 4, p[0]  + 4, p[1] + 4),\n",
        "          fill=list_3_color[i]\n",
        "      )\n",
        "\n",
        "  im = im.rotate(rotate, fillcolor=(255,255,255))\n",
        "  im.save(path_file)\n",
        "\n",
        "  if show is True:\n",
        "    return im"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "R_fkh5yMdPUy"
      },
      "source": [
        "Test random triangle"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 241
        },
        "id": "sKlyzt_3GNk9",
        "outputId": "885b466f-f395-4ae2-8c23-9335013f735b"
      },
      "source": [
        "height_shape = random.randrange(70, 180)\n",
        "width_shape = random.randrange(70, 180)\n",
        "rotate = random.randrange(-180, 180)\n",
        "\n",
        "createTriangle(\n",
        "    height_shape=height_shape,\n",
        "    width_shape=width_shape,\n",
        "    list_3_color=[color for color in list_color_rgb[0:3]],\n",
        "    size_img=size_img,\n",
        "    width_line=10,\n",
        "    rotate=rotate,\n",
        "    path_file='/tmp/sample-triangle.png',\n",
        "    show=True\n",
        ")"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "image/png": "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\n",
            "text/plain": [
              "<PIL.Image.Image image mode=RGB size=224x224 at 0x7F0227ADDFD0>"
            ]
          },
          "metadata": {},
          "execution_count": 77
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "Dpj7T8SgJktJ"
      },
      "source": [
        "## Split Handler"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "KLIhg4FLYSfV"
      },
      "source": [
        "num_train = 3000\n",
        "num_val = 500\n",
        "num_test = 500"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "dOI0SQEor1zQ"
      },
      "source": [
        "list_color_train = random.choices(list_color_rgb, weights=weights_color, k=num_train)\n",
        "list_color_val = random.choices(list_color_rgb, weights=weights_color, k=num_val)\n",
        "list_color_test = random.choices(list_color_rgb, weights=weights_color, k=num_test)"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "641n-QasaFEl"
      },
      "source": [
        "def split_dataset(name, num, list_color, size_img, base_class_dir):\n",
        "  for i in range(num):\n",
        "    # balance flip image (~50%)\n",
        "    flip = True if i % 2 == 0 else False\n",
        "    # fix index out of range\n",
        "    i_start = 0 if (i + 4 >= num - 1) else i\n",
        "\n",
        "    # circle generator\n",
        "    width_box = random.randrange(70, 200)\n",
        "    height_box = random.randrange(70, 200)\n",
        "    rotate = random.randrange(-40, 40)\n",
        "\n",
        "    createCircle(\n",
        "        width_box=width_box,\n",
        "        height_box=height_box,\n",
        "        color=list_color[i],\n",
        "        size_img=size_img,\n",
        "        width_line=10,\n",
        "        rotate=rotate,\n",
        "        path_file=os.path.join(base_class_dir, 'circle', 'circle-{}-{}.png'.format(name,i)),\n",
        "        show=False\n",
        "    )\n",
        "\n",
        "    # kite generator\n",
        "    diag_vert = random.randrange(130, 200)\n",
        "    diag_horz = random.randrange(70, 130)\n",
        "    rotate = random.randrange(-20, 20)\n",
        "\n",
        "    createKite(\n",
        "        diag_horz=diag_horz,\n",
        "        diag_vert=diag_vert,\n",
        "        list_4_color=[color for color in list_color[i_start:i_start+4]],\n",
        "        size_img=size_img,\n",
        "        width_line=10,\n",
        "        rotate=rotate,\n",
        "        path_file=os.path.join(base_class_dir, 'kite', 'kite-{}-{}.png'.format(name,i)),\n",
        "        show=False\n",
        "    )\n",
        "\n",
        "    # parallelogram generator\n",
        "    left_slope = random.randrange(70, 120)\n",
        "    top_horz = random.randrange(70, 120)\n",
        "    angle_deg = random.randrange(30, 80)\n",
        "    rotate = random.randrange(-5, 5)\n",
        "\n",
        "    createParallelogram(\n",
        "        top_horz=top_horz,\n",
        "        left_slope=left_slope,\n",
        "        list_4_color=[color for color in list_color[i_start:i_start+4]],\n",
        "        size_img=size_img,\n",
        "        angle_deg=angle_deg,\n",
        "        flip=flip,\n",
        "        width_line=10,\n",
        "        rotate=rotate,\n",
        "        path_file=os.path.join(base_class_dir, 'parallelogram', 'parallelogram-{}-{}.png'.format(name,i)),\n",
        "        show=False\n",
        "    )\n",
        "\n",
        "    # square generator\n",
        "    length_shape = random.randrange(70, 120)\n",
        "    rotate = random.randrange(-10, 10)\n",
        "\n",
        "    createSquare(\n",
        "        length_shape=length_shape,\n",
        "        list_4_color=[color for color in list_color[i_start:i_start+4]],\n",
        "        size_img=size_img,\n",
        "        width_line=10,\n",
        "        rotate=rotate,\n",
        "        path_file=os.path.join(base_class_dir, 'square', 'square-{}-{}.png'.format(name,i)),\n",
        "        show=False\n",
        "    )\n",
        "\n",
        "    # trapezoid generator\n",
        "    top_horz = random.randrange(70, 120)\n",
        "    bot_horz = random.randrange(top_horz+50, 200)\n",
        "    height_shape = random.randrange(50, 150)\n",
        "    rotate = random.randrange(-5, 5)\n",
        "\n",
        "    createTrapezoid(\n",
        "        top_horz=top_horz,\n",
        "        bot_horz=bot_horz,\n",
        "        height_shape=height_shape,\n",
        "        list_4_color=[color for color in list_color[i_start:i_start+4]],\n",
        "        size_img=size_img,\n",
        "        flip=flip,\n",
        "        width_line=10,\n",
        "        rotate=rotate,\n",
        "        path_file=os.path.join(base_class_dir, 'trapezoid', 'trapezoid-{}-{}.png'.format(name,i)),\n",
        "        show=False\n",
        "    )\n",
        "\n",
        "    # triangle generator\n",
        "    height_shape = random.randrange(70, 180)\n",
        "    width_shape = random.randrange(70, 180)\n",
        "    rotate = random.randrange(-180, 180)\n",
        "\n",
        "    createTriangle(\n",
        "        height_shape=height_shape,\n",
        "        width_shape=width_shape,\n",
        "        list_3_color=[color for color in list_color[i_start:i_start+3]],\n",
        "        size_img=size_img,\n",
        "        width_line=10,\n",
        "        rotate=rotate,\n",
        "        path_file=os.path.join(base_class_dir, 'triangle', 'triangle-{}-{}.png'.format(name,i)),\n",
        "        show=False\n",
        "    )"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "WEuScua8goaT"
      },
      "source": [
        "def len_class_dir(base_dir, label):\n",
        "  for lb in label:\n",
        "    print('\\n{} : train({}), val({}), test({})'.format(\n",
        "        lb,\n",
        "        len(os.listdir(os.path.join(base_dir, 'train', lb))),\n",
        "        len(os.listdir(os.path.join(base_dir, 'val', lb))),\n",
        "        len(os.listdir(os.path.join(base_dir, 'test', lb)))\n",
        "    ))"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "3b3p2tEiJtJH"
      },
      "source": [
        "### Generate Dataset"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "TuMsHYiizQ7_"
      },
      "source": [
        "!rm -R /tmp/six-shapes"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "sEX8IvlmJn0z",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "67338b9c-56ee-41c9-eabf-efc454565491"
      },
      "source": [
        "split_dataset(\n",
        "    name='train',\n",
        "    num=num_train,\n",
        "    list_color=list_color_train,\n",
        "    size_img=size_img,\n",
        "    base_class_dir=train_dir\n",
        ")\n",
        "\n",
        "# show result\n",
        "len_class_dir(\n",
        "    base_dir=base_dir,\n",
        "    label=label\n",
        ")"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "\n",
            "circle : train(3000), val(0), test(0)\n",
            "\n",
            "kite : train(3000), val(0), test(0)\n",
            "\n",
            "parallelogram : train(3000), val(0), test(0)\n",
            "\n",
            "square : train(3000), val(0), test(0)\n",
            "\n",
            "trapezoid : train(3000), val(0), test(0)\n",
            "\n",
            "triangle : train(3000), val(0), test(0)\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "QMqKDROOJwO8"
      },
      "source": [
        "### Validation Dataset"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "l00T7ziQJ0GW",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "95a2ff2e-a6d7-4373-8057-db415c5389d6"
      },
      "source": [
        "split_dataset(\n",
        "    name='val',\n",
        "    num=num_val,\n",
        "    list_color=list_color_val,\n",
        "    size_img=size_img,\n",
        "    base_class_dir=val_dir\n",
        ")\n",
        "\n",
        "# show result\n",
        "len_class_dir(\n",
        "    base_dir=base_dir,\n",
        "    label=label\n",
        ")"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "\n",
            "circle : train(3000), val(500), test(0)\n",
            "\n",
            "kite : train(3000), val(500), test(0)\n",
            "\n",
            "parallelogram : train(3000), val(500), test(0)\n",
            "\n",
            "square : train(3000), val(500), test(0)\n",
            "\n",
            "trapezoid : train(3000), val(500), test(0)\n",
            "\n",
            "triangle : train(3000), val(500), test(0)\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "5WfyoSlKJ0tu"
      },
      "source": [
        "### Test Dataset"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "eVQoc9EGJ3kh",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "118606f4-375c-4989-81d0-c1368122ab54"
      },
      "source": [
        "split_dataset(\n",
        "    name='test',\n",
        "    num=num_test,\n",
        "    list_color=list_color_test,\n",
        "    size_img=size_img,\n",
        "    base_class_dir=test_dir\n",
        ")\n",
        "\n",
        "# show result\n",
        "len_class_dir(\n",
        "    base_dir=base_dir,\n",
        "    label=label\n",
        ")"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "\n",
            "circle : train(3000), val(500), test(500)\n",
            "\n",
            "kite : train(3000), val(500), test(500)\n",
            "\n",
            "parallelogram : train(3000), val(500), test(500)\n",
            "\n",
            "square : train(3000), val(500), test(500)\n",
            "\n",
            "trapezoid : train(3000), val(500), test(500)\n",
            "\n",
            "triangle : train(3000), val(500), test(500)\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "BrhZtNJJoRfP"
      },
      "source": [
        "## Compress Files"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Wit4H-SfoeFI"
      },
      "source": [
        "!cd /tmp && zip -r 'six-shapes-dataset-v2.zip' 'six-shapes'"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "0N0tpWy2og3V"
      },
      "source": [
        "## Download"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "irm4pZ_6ojBJ",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "ffb6690e-99a3-439c-9205-bb7017517563"
      },
      "source": [
        "files.download('/tmp/six-shapes-dataset-v2.zip')"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "application/javascript": [
              "\n",
              "    async function download(id, filename, size) {\n",
              "      if (!google.colab.kernel.accessAllowed) {\n",
              "        return;\n",
              "      }\n",
              "      const div = document.createElement('div');\n",
              "      const label = document.createElement('label');\n",
              "      label.textContent = `Downloading \"${filename}\": `;\n",
              "      div.appendChild(label);\n",
              "      const progress = document.createElement('progress');\n",
              "      progress.max = size;\n",
              "      div.appendChild(progress);\n",
              "      document.body.appendChild(div);\n",
              "\n",
              "      const buffers = [];\n",
              "      let downloaded = 0;\n",
              "\n",
              "      const channel = await google.colab.kernel.comms.open(id);\n",
              "      // Send a message to notify the kernel that we're ready.\n",
              "      channel.send({})\n",
              "\n",
              "      for await (const message of channel.messages) {\n",
              "        // Send a message to notify the kernel that we're ready.\n",
              "        channel.send({})\n",
              "        if (message.buffers) {\n",
              "          for (const buffer of message.buffers) {\n",
              "            buffers.push(buffer);\n",
              "            downloaded += buffer.byteLength;\n",
              "            progress.value = downloaded;\n",
              "          }\n",
              "        }\n",
              "      }\n",
              "      const blob = new Blob(buffers, {type: 'application/binary'});\n",
              "      const a = document.createElement('a');\n",
              "      a.href = window.URL.createObjectURL(blob);\n",
              "      a.download = filename;\n",
              "      div.appendChild(a);\n",
              "      a.click();\n",
              "      div.remove();\n",
              "    }\n",
              "  "
            ],
            "text/plain": [
              "<IPython.core.display.Javascript object>"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "application/javascript": [
              "download(\"download_a234f4b2-200f-42ad-894e-d2abce8b84b3\", \"six-shapes-dataset-v2.zip\", 34834011)"
            ],
            "text/plain": [
              "<IPython.core.display.Javascript object>"
            ]
          },
          "metadata": {}
        }
      ]
    }
  ]
}