Invisibility Cloak -using OpenCV

How it works

Let’s Start

You need the following libraries

import cv2
import time
import numpy as np

Hue Saturation Value

H : Hue

S : Saturation

V : Value (Brightness)

##reading from the webcam
cap = cv2.VideoCapture(0)
## Allow the system to sleep for 3 seconds before the webcam starts
time.sleep(3)
count = 0
background = 0
## Capture the background in range of 60
for i in range(60):
ret, background = cap.read()
background = np.flip(background, axis=1)
## Read every frame from the webcam, until the camera is open
while (cap.isOpened()):
ret, img = cap.read()
if not ret:
break
count += 1
img = np.flip(img, axis=1)
## Convert the color space from BGR to HSV
hsv = cv2.cvtColor(img, cv2.COLOR_BGR2HSV)
## Generat masks to detect red color
lower_red = np.array([0, 125, 50])
upper_red = np.array([10, 255,255])
mask1 = cv2.inRange(hsv, lower_red, upper_red)
lower_red = np.array([170, 120, 70])
upper_red = np.array([180, 255, 255])
mask2 = cv2.inRange(hsv, lower_red, upper_red)
mask1 = mask1 + mask2
## Open and Dilate the mask image
mask1 = cv2.morphologyEx(mask1, cv2.MORPH_OPEN, np.ones((3, 3), np.uint8))
mask1 = cv2.morphologyEx(mask1, cv2.MORPH_DILATE, np.ones((3, 3), np.uint8))
## Create an inverted mask to segment out the red color from the frame
mask2 = cv2.bitwise_not(mask1)
## Segment the red color part out of the frame using bitwise and with the inverted mask
res1 = cv2.bitwise_and(img, img, mask=mask2)
## Create image showing static background frame pixels only for the masked region
res2 = cv2.bitwise_and(background, background, mask=mask1)

Full Code

Summary:

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