Draw Shapes on an Image.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## <code>Import Libraries</code>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "#!pip install opencv-python-headless"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "#!pip install opencv-contrib-python-headless"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "import cv2"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## <code>Create a black image to work</code>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "blackImg = np.zeros(shape = (512, 512, 3),\n",
    "                    dtype = np.int16)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## <code>Get the Shape of the Image</code>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(512, 512, 3)"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "blackImg.shape"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## <code>Show it</code>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.image.AxesImage at 0x7ff307e922e8>"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.imshow(blackImg)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## <code>Draw a Cicle</code>\n",
    "<p><code>The center is the first number on x-axis and second on y-axis</code></p>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.image.AxesImage at 0x7ff2d2307f60>"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "cv2.circle(img = blackImg,\n",
    "           center = (400, 100),\n",
    "           radius = 50,\n",
    "           color = (0, 255, 0),\n",
    "           thickness = 8)\n",
    "\n",
    "plt.imshow(blackImg)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## <code>Filled Circle</code>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.image.AxesImage at 0x7ff2d2278438>"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "cv2.circle(img = blackImg,\n",
    "           center = (400, 200),\n",
    "           radius = 50,\n",
    "           color = (0, 255, 255),\n",
    "           thickness = -1)\n",
    "\n",
    "plt.imshow(blackImg)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## <code>Draw a Rectangle</code>\n",
    "\n",
    "<code>The first number is on x-axis & the second on the y-axis\n",
    "\n",
    "We need two points. One forup and diagonally down</code>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.image.AxesImage at 0x7ff2d2254630>"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "cv2.rectangle(blackImg,\n",
    "              pt1 = (200, 200),\n",
    "              pt2 = (300, 300),\n",
    "              color = (0, 0, 255),\n",
    "              thickness = 5)\n",
    "\n",
    "plt.imshow(blackImg)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## <code>Draw a Triangle</code>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.image.AxesImage at 0x7ff2d21b0c50>"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "vertices = np.array([[10, 450],\n",
    "                    [110, 350],\n",
    "                    [180, 450]],\n",
    "                    np.int32)\n",
    "\n",
    "pts = vertices.reshape(-1, 1, 2)\n",
    "\n",
    "cv2.polylines(blackImg,\n",
    "              [pts],\n",
    "              isClosed = True,\n",
    "              color = (100, 100, 255),\n",
    "              thickness = 3)\n",
    "\n",
    "plt.imshow(blackImg)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## <code>Filled Rectangle</code>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.image.AxesImage at 0x7ff2d21969e8>"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "cv2.rectangle(blackImg,\n",
    "              pt1 = (200, 25),\n",
    "              pt2 = (300, 150),\n",
    "              color = (0, 150, 105),\n",
    "              thickness = -1)\n",
    "\n",
    "plt.imshow(blackImg)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## <code>Filled Triangle</code>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.image.AxesImage at 0x7ff2d20f1ef0>"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "vertices = np.array([[10, 450],\n",
    "                    [110, 350],\n",
    "                    [180, 450]],\n",
    "                   np.int32)\n",
    "\n",
    "pts = vertices.reshape(-1, 1, 2)\n",
    "\n",
    "cv2.fillPoly(blackImg,\n",
    "             [pts],\n",
    "             color = (100, 100, 255))\n",
    "\n",
    "plt.imshow(blackImg)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## <code>Draw Line</code>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.image.AxesImage at 0x7ff2d20d3d30>"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "cv2.line(blackImg,\n",
    "         pt1 = (512, 0),\n",
    "         pt2 = (0, 512),\n",
    "         color = (100, 255, 100),\n",
    "         thickness = 3)\n",
    "\n",
    "plt.imshow(blackImg)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## <code>Write Text</code>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.image.AxesImage at 0x7ff2d203e320>"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1008x648 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "font = cv2.FONT_HERSHEY_SIMPLEX\n",
    "\n",
    "cv2.putText(blackImg,\n",
    "            text = 'MAR',\n",
    "            org = (210, 500),\n",
    "            fontFace = font,\n",
    "            fontScale = 3,\n",
    "            color = (100, 200, 250),\n",
    "            thickness = 3,\n",
    "            lineType = cv2.LINE_AA)\n",
    "\n",
    "plt.figure(figsize = (14, 9))\n",
    "plt.imshow(blackImg)"
   ]
  }
 ],
 "metadata": {
  "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": "3.7.3"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}