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‎.ipynb_checkpoints/Lecture 2.4 - Reading, writing and displaying images-checkpoint.ipynb

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{
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"cells": [
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## Hi and welcome to your first code along lesson!\n",
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"\n",
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"#### Reading, writing and displaying images with OpenCV"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"Let's start by importing the OpenCV libary "
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]
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},
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{
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"cell_type": "code",
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"execution_count": 1,
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"metadata": {},
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"outputs": [],
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"source": [
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"# Press CTRL + ENTER to run this line\n",
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"# You should see an * between the [ ] on the left\n",
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"# OpenCV takes a couple seconds to import the first time\n",
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"\n",
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"import cv2"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {
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"collapsed": true
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},
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"outputs": [],
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"source": []
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},
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{
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"cell_type": "code",
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"execution_count": 2,
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"metadata": {
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"collapsed": true
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},
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"outputs": [],
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"source": [
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"# Now let's import numpy\n",
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"# We use as np, so that everything we call on numpy, we can type np instead\n",
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"# It's short and looks neater\n",
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"\n",
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"import numpy as np "
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"Let's now load our first image"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 2,
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"metadata": {},
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"outputs": [],
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"source": [
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"# We don't need to do this again, but it's a good habit\n",
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"import cv2 \n",
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"\n",
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"# Load an image using 'imread' specifying the path to image\n",
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"input = cv2.imread('./images/input.jpg')\n",
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"\n",
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"# Our file 'input.jpg' is now loaded and stored in python \n",
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"# as a varaible we named 'image'\n",
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"\n",
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"# To display our image variable, we use 'imshow'\n",
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"# The first parameter will be title shown on image window\n",
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"# The second parameter is the image varialbe\n",
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"cv2.imshow('Hello World', input)\n",
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"\n",
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"# 'waitKey' allows us to input information when a image window is open\n",
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"# By leaving it blank it just waits for anykey to be pressed before \n",
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"# continuing. By placing numbers (except 0), we can specify a delay for\n",
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"# how long you keep the window open (time is in milliseconds here)\n",
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"cv2.waitKey()\n",
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"\n",
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"# This closes all open windows \n",
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"# Failure to place this will cause your program to hang\n",
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"cv2.destroyAllWindows()"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {
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"collapsed": true
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},
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"outputs": [],
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"source": [
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"# Same as above without the extraneous comments\n",
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"\n",
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"import cv2 \n",
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"\n",
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"input = cv2.imread('./images/input.jpg')\n",
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"\n",
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"cv2.imshow('Hello World', input)\n",
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"cv2.waitKey(0)\n",
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"cv2.destroyAllWindows()"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"### Let's take a closer look at how images are stored"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 16,
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"metadata": {
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"collapsed": true
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},
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"outputs": [],
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"source": [
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"# Import numpy\n",
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"import numpy as np"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 15,
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"(830L, 1245L, 3L)\n"
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]
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}
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],
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"source": [
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"print input.shape"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"#### Shape gives the dimensions of the image array\n",
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"\n",
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"The 2D dimensions are 830 pixels in high bv 1245 pixels wide.\n",
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"The '3L' means that there are 3 other components (RGB) that make up this image."
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]
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},
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{
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"cell_type": "code",
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"execution_count": 17,
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"Height of Image: 830 pixels\n",
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"Width of Image: 1245 pixels\n"
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]
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}
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],
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"source": [
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"# Let's print each dimension of the image\n",
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"\n",
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"print 'Height of Image:', int(input.shape[0]), 'pixels'\n",
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"print 'Width of Image: ', int(input.shape[1]), 'pixels'"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"### How do we save images we edit in OpenCV?"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 18,
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"True"
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]
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},
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"execution_count": 18,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"# Simply use 'imwrite' specificing the file name and the image to be saved\n",
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"cv2.imwrite('output.jpg', input)\n",
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"cv2.imwrite('output.png', input)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {
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"collapsed": true
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},
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"outputs": [],
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"source": []
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {
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"collapsed": true
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},
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"outputs": [],
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"source": []
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {
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"collapsed": true
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},
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"outputs": [],
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"source": []
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {
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"collapsed": true
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},
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"outputs": [],
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"source": []
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {
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"collapsed": true
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},
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"outputs": [],
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"source": []
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}
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],
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"metadata": {
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"kernelspec": {
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"display_name": "Python 2",
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"language": "python",
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"name": "python2"
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},
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"language_info": {
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"codemirror_mode": {
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"name": "ipython",
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"version": 2
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},
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"file_extension": ".py",
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"mimetype": "text/x-python",
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython2",
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"version": "2.7.14"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 1
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}

‎.ipynb_checkpoints/Lecture 2.5 - Grayscaling-checkpoint.ipynb

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{
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"cells": [
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## Grayscaling\n",
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"\n",
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"#### Grayscaling is process by which an image is converted from a full color to shades of grey (black & white)\n",
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"\n",
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"In OpenCV, many functions grayscale images before processing. This is done because it simplifies the image, acting almost as a noise reduction and increasing processing time as there is less information in the image.\n",
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"\n",
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"### Let convert our color image to greyscale"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 1,
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"metadata": {},
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"outputs": [],
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"source": [
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"import cv2\n",
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"\n",
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"# Load our input image\n",
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"image = cv2.imread('./images/input.jpg')\n",
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"cv2.imshow('Original', image)\n",
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"cv2.waitKey()\n",
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"\n",
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"# We use cvtColor, to convert to grayscale\n",
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"gray_image = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)\n",
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"\n",
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"cv2.imshow('Grayscale', gray_image)\n",
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"cv2.waitKey()\n",
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"cv2.destroyAllWindows()"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 8,
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"metadata": {},
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"outputs": [],
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"source": [
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"#Another method faster method\n",
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"# The third argument of 0 makes it greyscale\n",
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"img = cv2.imread('./images/input.jpg',0)\n",
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"\n",
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"cv2.imshow('Grayscale', img)\n",
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"cv2.waitKey()\n",
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"cv2.destroyAllWindows()"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": []
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}
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],
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"metadata": {
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"kernelspec": {
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"display_name": "Python 2",
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"language": "python",
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"name": "python2"
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},
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"language_info": {
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"codemirror_mode": {
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"name": "ipython",
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"version": 2
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},
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"file_extension": ".py",
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"mimetype": "text/x-python",
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython2",
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"version": "2.7.14"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 1
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}

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