Blending images – OpenCV 3.4 with python 3 Tutorial 6
Beginners Opencv, Tutorials
0
Source code:
[python]
import cv2
import numpy as np
img1 = cv2.imread("road.jpg")
img2 = cv2.imread("car.jpg")
img2_gray = cv2.cvtColor(img2, cv2.COLOR_BGR2GRAY)
ret, mask = cv2.threshold(img2_gray, 240, 255, cv2.THRESH_BINARY)
mask_inv = cv2.bitwise_not(mask)
road = cv2.bitwise_and(img1, img1, mask=mask)
car = cv2.bitwise_and(img2, img2, mask=mask_inv)
result = cv2.add(road, car)
cv2.imshow("img1", img1)
cv2.imshow("img2", img2)
cv2.imshow("road background", road)
cv2.imshow("car no background", car)
cv2.imshow("mask", mask)
cv2.imshow("mask inverse", mask_inv)
cv2.imshow("result", result)
cv2.waitKey(0)
cv2.destroyAllWindows()
[/python]
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Opencv Beginner Tutorial
- 1) Loading images
- 2) Loading Video and Webcam
- 3) Drawing and writing on images
- 4) Basic operations on images
- 5) Add images and Threshold
- 6) Blending images
- 7) Bitwise Operators
- 8) Trackbars
- 9) Object detection using HSV Color space
- 10) Basic Thresholding
- 11) Histograms
- 12) Basic geometric transformations
- 13) Perspective transformation
- 14) Affine transformation
- 15) Adaptive thresholding5
- 16) Smoothing images
- 17) Morphological transformation
- 18) Edge detection
- 19) Find and Draw Contours
- 20) Template matching
- 21) Lines detection with Hough Transform
- 22) Corners detection
- 23) Image Pyramids
- 24) Image Pyramids (Blending and reconstruction)
- 25) Feature detection (SIFT, SURF, ORB)
- 26) Feature Matching (Brute-Force)
- 27) Mouse Events
- 28) Histogram and Back Projection
- 29) Object tracking with Mean-shift
- 30) Object tracking with Camshift
- 31) Optical Flow with Lucas-Kanade method
- 32) Background Subtraction
- 33) k-Nearest Neighbour classification
- 34) Object tracking using Homography
- 35) Fourier Transform
- 36) Knn handwritten digits recognition
- 37) Face detection using Haar Cascades
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