Persist Colors

persist.py

#import cv2 for computer vision
#import numpy to make blank images
import cv2, numpy as np

#capture source video
cap = cv2.VideoCapture('/home/acer/Desktop/colorspace/bxx.MP4')
#define

#define orange
orange = 0,145,155,255,255,255

#takes and image and color range, returns a mask,
#and an image that has colors only from within the color range
def only_color(imgc, (h,s,v,h1,s1,v1)):
    #convert image to hsv
    hsv = cv2.cvtColor(imgc, cv2.COLOR_BGR2HSV)
    #convert values to arrays
    lower, upper = np.array([h,s,v]), np.array([h1,s1,v1])
    #find the colors that are within the range of the lower and upper bounds
    mask = cv2.inRange(hsv, lower, upper)
    #use the bitwise and function to mask origional image
    res = cv2.bitwise_and(imgc, imgc, mask=mask)
    return res, mask

#create matte image that contains all the orange in the video
orange_bg = np.zeros((720,1280,3), np.uint8)
zeros = np.zeros_like(orange_bg)

#loop that reads each frame of video
while True:
    #read image
    _, img = cap.read()
    #get the orange only parts of the image
    orange_parts, mask = only_color(img, orange)
    #mask out that part of the orange_bg image
    mask = cv2.bitwise_not(mask)
    orange_bg = cv2.bitwise_and(orange_bg, orange_bg, mask=mask)
    #add the orange back
    orange_bg = cv2.add(orange_bg, orange_parts)
    #mask out the orange_bg portion of the image
    gray = cv2.cvtColor(orange_bg, cv2.COLOR_BGR2GRAY)
    _, mask = cv2.threshold(gray, 1, 255, cv2.THRESH_BINARY)
    mask = cv2.bitwise_not(mask)
    img = cv2.bitwise_and(img, img, mask=mask)
    img = cv2.add(img, orange_bg)
    #show the image and wait
    cv2.imshow('img', cv2.resize(img, (640,480)))
    k=cv2.waitKey(1)
    if k==27: break
    
#release the video to avoid memory leaks, and close the window
cap.release()
cv2.destroyAllWindows()