invi.py

import cv2
import numpy as np
import time

capture_video = cv2.VideoCapture(0)

# give the camera to warm up
time.sleep(1)
count = 0
background = 0

#just leave the screen up and running for like 5 sec ith just background 
for i in range(60):
    return_val, background = capture_video.read()
    if return_val == False:
        continue

background = np.flip(background, axis=1)  # flipping of the frame

while (capture_video.isOpened()):
    return_val, img = capture_video.read()
    if not return_val:
        break
    count = count + 1
    img = np.flip(img, axis=1)

    # convert the image - BGR to HSV
    hsv = cv2.cvtColor(img, cv2.COLOR_BGR2HSV)
    lower_red = np.array([100, 40, 40])
    upper_red = np.array([100, 255, 255])
    mask1 = cv2.inRange(hsv, lower_red, upper_red)
    # setting the lower and upper range for mask2
    lower_red = np.array([155, 40, 40])
    upper_red = np.array([180, 255, 255])
    mask2 = cv2.inRange(hsv, lower_red, upper_red)

    # the above block of code could be replaced with
    # some other code depending upon the color of your cloth
    # i am using red you can use any R G B colour
    mask1 = mask1 + mask2

    # Refining the mask corresponding to the detected red color
    mask1 = cv2.morphologyEx(mask1, cv2.MORPH_OPEN, np.ones((3, 3),np.uint8), iterations=2)
    mask1 = cv2.dilate(mask1, np.ones((3, 3), np.uint8), iterations=1)
    mask2 = cv2.bitwise_not(mask1)

    # Generating the final output
    res1 = cv2.bitwise_and(background, background, mask=mask1)
    res2 = cv2.bitwise_and(img, img, mask=mask2)
    final_output = cv2.addWeighted(res1, 1, res2, 1, 0)

    cv2.imshow("INVISIBLE CLOAK", final_output)
    k = cv2.waitKey(10)
    if k == 27:
        break