opencv/01. Basic.ipynb

{
 "cells": [
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# OpenCV Basic "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Import Require Packages\n",
    "import cv2 as cv\n",
    "import numpy as np\n"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Reading Images and Video"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Read image\n",
    "img = cv.imread('../Resources/Photos/cats.jpg')\n",
    "\n",
    "# show image\n",
    "cv.imshow('Cats', img)\n",
    "\n",
    "\n",
    "# Read Videos\n",
    "\n",
    "capture = cv.VideoCapture(\"./Resources/Videos/dog.mp4\")\n",
    "\n",
    "while True:\n",
    "    ret, frame = capture.read()\n",
    "\n",
    "    cv.imshow(\"Video\", frame)\n",
    "\n",
    "    if cv.waitKey(20) & 0xFF == ord(\"d\"):\n",
    "        break\n",
    "\n",
    "capture.release()\n",
    "cv.destroyAllWindows()\n"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Resizing and Rescaling Images and Video Frames"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "def rescaleFrame(frame, scale=0.75):\n",
    "    # Images, Videos and Live Video\n",
    "    width = int(frame.shape[1] * scale)\n",
    "    height = int(frame.shape[0] * scale)\n",
    "\n",
    "    dimensions = (width, height)\n",
    "\n",
    "    return cv.resize(frame, dimensions, interpolation=cv.INTER_AREA)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "def changeRes(width, height):\n",
    "    # Live video\n",
    "    capture.set(3, width)\n",
    "    capture.set(4, height)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "\n",
    "# Reading Videos\n",
    "capture = cv.VideoCapture('./Resources/Videos/dog.mp4')\n",
    "\n",
    "while True:\n",
    "    isTrue, frame = capture.read()\n",
    "\n",
    "    frame_resized = rescaleFrame(frame, scale=.2)\n",
    "\n",
    "    cv.imshow('Video', frame)\n",
    "    cv.imshow('Video Resized', frame_resized)\n",
    "\n",
    "    if cv.waitKey(20) & 0xFF == ord('d'):\n",
    "        break\n",
    "\n",
    "capture.release()\n",
    "cv.destroyAllWindows()\n"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Drawing Shapes and Placing text on images"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "\n",
    "blank = np.zeros((500, 500, 3), dtype='uint8')\n",
    "cv.imshow('Blank', blank)\n",
    "\n",
    "# 1. Paint the image a certain colour\n",
    "blank[200:300, 300:400] = 0, 0, 255\n",
    "cv.imshow('Green', blank)\n",
    "\n",
    "# 2. Draw a Rectangle\n",
    "cv.rectangle(blank, (0, 0),\n",
    "             (blank.shape[1]//2, blank.shape[0]//2), (0, 255, 0), thickness=-1)\n",
    "cv.imshow('Rectangle', blank)\n",
    "\n",
    "# 3. Draw A circle\n",
    "cv.circle(blank, (blank.shape[1]//2, blank.shape[0]//2),\n",
    "          40, (0, 0, 255), thickness=-1)\n",
    "cv.imshow('Circle', blank)\n",
    "\n",
    "# 4. Draw a line\n",
    "cv.line(blank, (100, 250), (300, 400), (255, 255, 255), thickness=3)\n",
    "cv.imshow('Line', blank)\n",
    "\n",
    "# 5. Write text\n",
    "cv.putText(blank, 'Hello, my name is Jason!!!', (0, 225),\n",
    "           cv.FONT_HERSHEY_TRIPLEX, 1.0, (0, 255, 0), 2)\n",
    "cv.imshow('Text', blank)\n",
    "\n",
    "cv.waitKey(0)\n"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 5 Essential Methods in OpenCV"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "img = cv.imread(\"./Resources/Photos/cat.jpg\")\n",
    "# cv.imshow(\"Cat\" , img)\n",
    "\n",
    "# Converting to grayscale\n",
    "gray = cv.cvtColor(img, cv.COLOR_BGR2GRAY)\n",
    "cv.imshow('Gray', gray)\n",
    "\n",
    "# Blur\n",
    "blur = cv.GaussianBlur(img, (7, 7), cv.BORDER_DEFAULT)\n",
    "cv.imshow('Blur', blur)\n",
    "\n",
    "# Edge Cascade\n",
    "canny = cv.Canny(blur, 125, 175)\n",
    "cv.imshow('Canny Edges', canny)\n",
    "\n",
    "# Dilating the image\n",
    "dilated = cv.dilate(canny, (7, 7), iterations=3)\n",
    "cv.imshow('Dilated', dilated)\n",
    "\n",
    "# Eroding\n",
    "eroded = cv.erode(dilated, (7, 7), iterations=3)\n",
    "cv.imshow('Eroded', eroded)\n",
    "\n",
    "# Resize\n",
    "resized = cv.resize(img, (500, 500), interpolation=cv.INTER_CUBIC)\n",
    "cv.imshow('Resized', resized)\n",
    "\n",
    "# Cropping\n",
    "cropped = img[50:200, 200:400]\n",
    "cv.imshow('Cropped', cropped)\n",
    "\n",
    "cv.waitKey(0)  # Wait for a key press\n",
    "cv.destroyAllWindows()  # Close all OpenCV windows\n"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Image Transformations\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "import cv2 as cv\n",
    "import numpy as np\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "img = cv.imread('./Resources/Photos/park.jpg')\n",
    "cv.imshow('Park', img)\n",
    "\n",
    "# Translation\n",
    "\n",
    "\n",
    "def translate(img, x, y):\n",
    "    transMat = np.float32([[1, 0, x], [0, 1, y]])\n",
    "    dimensions = (img.shape[1], img.shape[0])\n",
    "    return cv.warpAffine(img, transMat, dimensions)\n",
    "\n",
    "# -x --> Left\n",
    "# -y --> Up\n",
    "# x --> Right\n",
    "# y --> Down\n",
    "\n",
    "\n",
    "translated = translate(img, -100, 100)\n",
    "cv.imshow('Translated', translated)\n",
    "cv.waitKey(0)  # Wait for a key press\n",
    "cv.destroyAllWindows()  # Close all OpenCV windows\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Rotation\n",
    "def rotate(img, angle, rotPoint=None):\n",
    "    (height, width) = img.shape[:2]\n",
    "\n",
    "    if rotPoint is None:\n",
    "        rotPoint = (width//2, height//2)\n",
    "\n",
    "    rotMat = cv.getRotationMatrix2D(rotPoint, angle, 1.0)\n",
    "    dimensions = (width, height)\n",
    "\n",
    "    return cv.warpAffine(img, rotMat, dimensions)\n",
    "\n",
    "\n",
    "rotated = rotate(img, -45)\n",
    "cv.imshow('Rotated', rotated)\n",
    "\n",
    "rotated_rotated = rotate(img, -90)\n",
    "cv.imshow('Rotated Rotated', rotated_rotated)\n",
    "\n",
    "cv.waitKey(0)  # Wait for a key press\n",
    "cv.destroyAllWindows()  # Close all OpenCV windows\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Resizing\n",
    "resized = cv.resize(img, (500, 500), interpolation=cv.INTER_CUBIC)\n",
    "cv.imshow('Resized', resized)\n",
    "\n",
    "# Flipping\n",
    "flip = cv.flip(img, -1)\n",
    "cv.imshow('Flip', flip)\n",
    "\n",
    "# Cropping\n",
    "cropped = img[200:400, 300:400]\n",
    "cv.imshow('Cropped', cropped)\n",
    "\n",
    "\n",
    "cv.waitKey(0)  # Wait for a key press\n",
    "cv.destroyAllWindows()  # Close all OpenCV windows\n"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Contour Detection"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "img = cv.imread('../Resources/Photos/cats.jpg')\n",
    "cv.imshow('Cats', img)\n",
    "\n",
    "blank = np.zeros(img.shape, dtype='uint8')\n",
    "cv.imshow('Blank', blank)\n",
    "\n",
    "gray = cv.cvtColor(img, cv.COLOR_BGR2GRAY)\n",
    "cv.imshow('Gray', gray)\n",
    "\n",
    "blur = cv.GaussianBlur(gray, (5, 5), cv.BORDER_DEFAULT)\n",
    "cv.imshow('Blur', blur)\n",
    "\n",
    "canny = cv.Canny(blur, 125, 175)\n",
    "cv.imshow('Canny Edges', canny)\n",
    "\n",
    "# ret, thresh = cv.threshold(gray, 125, 255, cv.THRESH_BINARY)\n",
    "# cv.imshow('Thresh', thresh)\n",
    "\n",
    "contours, hierarchies = cv.findContours(\n",
    "    canny, cv.RETR_LIST, cv.CHAIN_APPROX_SIMPLE)\n",
    "print(f'{len(contours)} contour(s) found!')\n",
    "\n",
    "cv.drawContours(blank, contours, -1, (0, 0, 255), 1)\n",
    "cv.imshow('Contours Drawn', blank)\n",
    "\n",
    "cv.waitKey(0)\n",
    "cv.destroyAllWindows()  # Close all OpenCV windows\n"
   ]
  }
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