zoukankan      html  css  js  c++  java
  • opencv学习之catch blue#20190703

    Object Tracking
    Now we know how to convert BGR image to HSV, we can use this to extract a colored object. In HSV, it is more easier to represent a color than in BGR color-space. In our application, we will try to extract a blue colored object. So here is the method:

    Take each frame of the video
    Convert from BGR to HSV color-space
    We threshold the HSV image for a range of blue color
    Now extract the blue object alone, we can do whatever on that image we want.
    Below is the code which are commented in detail :

    import cv2
    import numpy as np
    cap = cv2.VideoCapture(0)
    while(1):
    # Take each frame
    _, frame = cap.read()
    # Convert BGR to HSV
    hsv = cv2.cvtColor(frame, cv2.COLOR_BGR2HSV)
    # define range of blue color in HSV
    lower_blue = np.array([110,50,50])
    upper_blue = np.array([130,255,255])
    # Threshold the HSV image to get only blue colors
    mask = cv2.inRange(hsv, lower_blue, upper_blue)
    # Bitwise-AND mask and original image
    res = cv2.bitwise_and(frame,frame, mask= mask)
    cv2.imshow('frame',frame)
    cv2.imshow('mask',mask)
    cv2.imshow('res',res)
    k = cv2.waitKey(5) & 0xFF
    if k == 27:
    break
    cv2.destroyAllWindows()

  • 相关阅读:
    852. Peak Index in a Mountain Array
    841. Keys and Rooms
    832. Flipping an Image
    821. Shortest Distance to a Character
    824. Goat Latin
    如何生成git的公钥和私钥
    学习笔记
    加快JavaScript加载和执行效率
    PO BO VO DTO POJO DAO概念及其作用
    jvm 垃圾回收区的形象说明
  • 原文地址:https://www.cnblogs.com/ax204/p/11126426.html
Copyright © 2011-2022 走看看