import cv2
import numpy as np
import time
# replace the red pixels ( or undesired area ) with
# background pixels to generate the invisibility feature.
## 1. Hue: This channel encodes color information. Hue can be
# thought of an angle where 0 degree corresponds to the red color,
# 120 degrees corresponds to the green color, and 240 degrees
# corresponds to the blue color.
## 2. Saturation: This channel encodes the intensity/purity of color.
# For example, pink is less saturated than red.
## 3. Value: This channel encodes the brightness of color.
# Shading and gloss components of an image appear in this
# channel reading the videocapture video
# in order to check the cv2 version
print(cv2.__version__)
# taking video.mp4 as input.
# Make your path according to your needs
capture_video = cv2.VideoCapture("video.mp4")
# give the camera to warm up
time.sleep(1)
count = 0
background = 0
# capturing the background in range of 60
# you should have video that have some seconds
# dedicated to background frame so that it
# could easily save the background image
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
# we are reading from 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 the image - BGR to HSV
# as we focused on detection of red color
# converting BGR to HSV for better
# detection or you can convert it to gray
hsv = cv2.cvtColor(img, cv2.COLOR_BGR2HSV)
#-------------------------------------BLOCK----------------------------#
# ranges should be carefully chosen
# setting the lower and upper range for mask1
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
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 MAN", final_output)
k = cv2.waitKey(10)
if k == 27:
break