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145 lines
5.1 KiB
Markdown
145 lines
5.1 KiB
Markdown
---
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category: tool
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tool: OpenCV
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filename: learnopencv.py
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contributors:
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- ["Yogesh Ojha", "http://github.com/yogeshojha"]
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---
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### Opencv
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OpenCV (Open Source Computer Vision) is a library of programming functions mainly aimed at real-time computer vision.
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Originally developed by Intel, it was later supported by Willow Garage then Itseez (which was later acquired by Intel).
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Opencv currently supports wide variety of languages like, C++, Python, Java etc
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#### Installation
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Please refer to these articles for installation of OpenCV on your computer.
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* Windows Installation Instructions: [https://opencv-python-tutroals.readthedocs.io/en/latest/py_tutorials/py_setup/py_setup_in_windows/py_setup_in_windows.html#install-opencv-python-in-windows]()
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* Mac Installation Instructions (High Sierra): [https://medium.com/@nuwanprabhath/installing-opencv-in-macos-high-sierra-for-python-3-89c79f0a246a]()
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* Linux Installation Instructions (Ubuntu 18.04): [https://www.pyimagesearch.com/2018/05/28/ubuntu-18-04-how-to-install-opencv]()
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### Here we will be focusing on python implementation of OpenCV
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```python
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# Reading image in OpenCV
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import cv2
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img = cv2.imread('cat.jpg')
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# Displaying the image
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# imshow() function is used to display the image
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cv2.imshow('Image',img)
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# Your first arguement is the title of the window and second parameter is image
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# If you are getting error, Object Type None, your image path may be wrong. Please recheck the pack to the image
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cv2.waitKey(0)
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# waitKey() is a keyboard binding function and takes arguement in milliseconds. For GUI events you MUST use waitKey() function.
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# Writing an image
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cv2.imwrite('catgray.png',img)
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# first arguement is the file name and second is the image
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# Convert image to grayscale
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gray_image = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
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# Capturing Video from Webcam
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cap = cv2.VideoCapture(0)
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#0 is your camera, if you have multiple camera, you need to enter their id
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while(True):
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# Capturing frame-by-frame
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_, frame = cap.read()
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cv2.imshow('Frame',frame)
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# When user presses q -> quit
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if cv2.waitKey(1) & 0xFF == ord('q'):
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break
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# Camera must be released
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cap.release()
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# Playing Video from file
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cap = cv2.VideoCapture('movie.mp4')
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while(cap.isOpened()):
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_, frame = cap.read()
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# Play the video in grayscale
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gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
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cv2.imshow('frame',gray)
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if cv2.waitKey(1) & 0xFF == ord('q'):
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break
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cap.release()
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# Drawing The Line in OpenCV
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# cv2.line(img,(x,y),(x1,y1),(color->r,g,b->0 to 255),thickness)
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cv2.line(img,(0,0),(511,511),(255,0,0),5)
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# Drawing Rectangle
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# cv2.rectangle(img,(x,y),(x1,y1),(color->r,g,b->0 to 255),thickness)
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# thickness = -1 used for filling the rectangle
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cv2.rectangle(img,(384,0),(510,128),(0,255,0),3)
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# Drawing Circle
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cv2.circle(img,(xCenter,yCenter), radius, (color->r,g,b->0 to 255), thickness)
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cv2.circle(img,(200,90), 100, (0,0,255), -1)
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# Drawing Ellipse
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cv2.ellipse(img,(256,256),(100,50),0,0,180,255,-1)
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# Adding Text On Images
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cv2.putText(img,"Hello World!!!", (x,y), cv2.FONT_HERSHEY_SIMPLEX, 2, 255)
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# Blending Images
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img1 = cv2.imread('cat.png')
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img2 = cv2.imread('openCV.jpg')
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dst = cv2.addWeighted(img1,0.5,img2,0.5,0)
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# Thresholding image
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# Binary Thresholding
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_,thresImg = cv2.threshold(img,127,255,cv2.THRESH_BINARY)
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# Adaptive Thresholding
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adapThres = cv2.adaptiveThreshold(img,255,cv2.ADAPTIVE_THRESH_GAUSSIAN_C, cv2.THRESH_BINARY,11,2)
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# Blur Image
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# Gaussian Blur
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blur = cv2.GaussianBlur(img,(5,5),0)
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# Median Blur
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medianBlur = cv2.medianBlur(img,5)
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# Canny Edge Detection
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img = cv2.imread('cat.jpg',0)
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edges = cv2.Canny(img,100,200)
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# Face Detection using Haar Cascades
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# Download Haar Cascades from https://github.com/opencv/opencv/blob/master/data/haarcascades/
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import cv2
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import numpy as np
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face_cascade = cv2.CascadeClassifier('haarcascade_frontalface_default.xml')
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eye_cascade = cv2.CascadeClassifier('haarcascade_eye.xml')
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img = cv2.imread('human.jpg')
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gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
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aces = face_cascade.detectMultiScale(gray, 1.3, 5)
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for (x,y,w,h) in faces:
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cv2.rectangle(img,(x,y),(x+w,y+h),(255,0,0),2)
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roi_gray = gray[y:y+h, x:x+w]
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roi_color = img[y:y+h, x:x+w]
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eyes = eye_cascade.detectMultiScale(roi_gray)
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for (ex,ey,ew,eh) in eyes:
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cv2.rectangle(roi_color,(ex,ey),(ex+ew,ey+eh),(0,255,0),2)
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cv2.imshow('img',img)
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cv2.waitKey(0)
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cv2.destroyAllWindows()
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# destroyAllWindows() destroys all windows.
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# If you wish to destroy specific window pass the exact name of window you created.
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```
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### Further Reading:
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* Download Cascade from [https://github.com/opencv/opencv/blob/master/data/haarcascades]()
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* OpenCV drawing Functions [https://docs.opencv.org/2.4/modules/core/doc/drawing_functions.html]()
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* An up-to-date language reference can be found at [https://opencv.org]()
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* Additional resources may be found at [https://en.wikipedia.org/wiki/OpenCV]()
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* Good OpenCv Tutorials
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* [https://opencv-python-tutroals.readthedocs.io/en/latest/py_tutorials/py_tutorials.html]()
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* [https://realpython.com/python-opencv-color-spaces]()
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* [https://pyimagesearch.com]()
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* [https://www.learnopencv.com]()
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