Invisibility Cloak Using OpenCV | Python Project

import cv2

import numpy as np

import time

# replace red pixels (or unwanted area) with
# background pixels to create invisibility function.

## 1. Hue: This channel encodes color information. Hue can be
# thought angle where 0 degrees corresponds to red
# 120 degrees corresponds to green and 240 degrees
# matches blue.

## 2. Saturation: this channel encodes the intensity / purity of the color.
# For example, pink is less saturated, than red.

## 3. Meaning: This channel encodes the brightness of the color .
# Shading and gloss components of the image appear in this
# video image reader

# to check the cv2 version

print (cv2 .__ version__)

# taking video.mp4 as input
# Make your own path according to your needs

capture_video = cv2.VideoCapture ( "video.mp4" )

# let the camera warm up

time.sleep ( 1 )

count = 0

background = 0

# capture the background in the 60 range
# you have there should be a video that has a few seconds
# outlined with a background frame so that
# can easily save background image

for i in range ( 60 ):

return_val, background = capture_video.read ()

if return_val = = False :

continue

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

# we read from the video

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 image - BGR to HSV

# how we focused on red detection

# convert BGR to HSV for better

# detection or you can convert it to gray

hsv = cv 2.cvtColor (img, cv2.COLOR_BGR2HSV)

# ------------------------------------- BLOCK ----------- ----------------- #

# ranges should be chosen carefully

# setting the lower and upper ranges for mask1

lower_red = np.array ([ 100 , 40 , 40 ])

upper_red = np.array ([ 100 , 255 , 255 ])

mask1 = cv2.inRange (hsv, lower_red, upper_red)

# set low and high 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 code block can be replaced with

# different code depending on the color of your fabric

mask1 = mask1 + mask2

# Refine the mask to match the detected red

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)

# Generate the final result

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 MAN" , final_output)

k = cv2.waitKey ( 10 )

if k = = 27 :

break