OpenCV Getting Started-Copy1.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Hello\n",
      "30\n"
     ]
    }
   ],
   "source": [
    "# Introduction \n",
    "\n",
    "print(\"Hello\")\n",
    "a = 10\n",
    "b = 20\n",
    "print(a+b)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "# OpenCV\n",
    "import cv2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(540, 570, 3)\n"
     ]
    }
   ],
   "source": [
    "# Read and Display an Image using Python\n",
    "\n",
    "\n",
    "\n",
    "img = cv2.imread(\"Images/b1.png\")\n",
    "\n",
    "#convert from BGR to RGB Color Space\n",
    "img = cv2.cvtColor(img,4)\n",
    "print(img.shape)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "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": [
    "import matplotlib.pyplot as plt\n",
    "\n",
    "plt.imshow(img)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[[1 2 3]\n",
      " [4 5 6]]\n",
      " Numpy array shape  (2, 3)\n"
     ]
    }
   ],
   "source": [
    "import numpy as np\n",
    "\n",
    "a = np.array([[1,2,3],\n",
    "             [4,5,6]])\n",
    "print(a)\n",
    "print(\" Numpy array shape \",a.shape)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(100, 200, 3)\n"
     ]
    }
   ],
   "source": [
    "# OS - (Operating System) -> Access different files on your system\n",
    "\n",
    "\n",
    "import os\n",
    "\n",
    "image_names = os.listdir(\"Images\")\n",
    "\n",
    "animals = []\n",
    "for f in image_names:\n",
    "    if(f.endswith(\".png\")):\n",
    "        #print(f)\n",
    "        file_path = \"Images/\" + f\n",
    "        img = cv2.imread(file_path)\n",
    "        img = cv2.cvtColor(img,cv2.COLOR_BGR2RGB)\n",
    "        img = cv2.resize(img,(100,100))\n",
    "        animals.append(img)\n",
    "        \n",
    "# Make a collage\n",
    "\n",
    "border = np.zeros((10,200,3),dtype='uint8')\n",
    "\n",
    "\n",
    "animal_12 = np.hstack((animals[0],animals[1]))\n",
    "animal_34 = np.hstack((animals[2],animals[3]))\n",
    "collage = np.vstack((animal_12,border,animal_34))\n",
    "plt.imshow(collage)\n",
    "plt.show()\n",
    "\n",
    "\n",
    "print(animal_12.shape)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "False"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "s = \"Hello\"\n",
    "s.endswith(\"lle\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "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": [
    "# Image Collage\n",
    "\n",
    "red = np.zeros((50,50,3),dtype='int')\n",
    "red[ : , : ,0] = 220\n",
    "\n",
    "green = np.zeros((50,50,3),dtype='int')\n",
    "green[ : , : ,1] = 250\n",
    "\n",
    "\n",
    "plt.imshow(red)\n",
    "plt.show()\n",
    "\n",
    "plt.imshow(green)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "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": [
    "red_green = np.hstack((red,green))\n",
    "green_red = red_green[ : , : : -1, :]\n",
    "img = np.vstack((red_green,green_red))\n",
    "plt.imshow(img)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([20, 15, 10])"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "a = np.array((10,15,20))\n",
    "a[: :-1]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "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": "3.7.2"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}