This mission demonstrates how to create an “invisible cloak” impact the usage of OpenCV in Python. The concept is based on covering and historical past subtraction strategies to make a specific coloration disappear and reveal the heritage in its place. This fun and creative application of OpenCV showcases actual-time photo processing and computer vision concepts.

How to Create Invisible Cloak using OpenCV in Python

Step 1:  Import the OpenCV library for image processing and NumPy for dealing with arrays, that is vital for developing masks and acting pixel manipulations.

import cv2
import numpy as np

Step 2: Use the webcam to capture a static history frame. Flipping the image horizontally guarantees the ideal orientation of the background.

cap = cv2.VideoCapture(0)
for i in range(30):
    ret, background = cap.read()
background = cv2.flip(background, 1)

Step 3: Continuously seize frames from the webcam for actual-time video processing. Each frame is flipped horizontally to preserve alignment with the heritage:

while cap.isOpened():
    ret, frame = cap.read()
    if not ret:
        break
    frame = cv2.flip(frame, 1)

Step 4: Convert the body to the HSV color area and outline the color variety for the cloak (e.G., purple). Create masks to isolate the desired color inside this variety.

hsv = cv2.cvtColor(frame, cv2.COLOR_BGR2HSV)
lower_red = np.array([0, 120, 70])
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)
mask = mask1 + mask2

Step 5: Apply morphological alterations to put off noise from the mask, making sure better segmentation of the cloak area.

mask = cv2.morphologyEx(mask, cv2.MORPH_OPEN, np.ones((3, 3), np.uint8))
mask = cv2.morphologyEx(mask, cv2.MORPH_DILATE, np.ones((3, 3), np.uint8))

Step 6: Use the mask to extract the background where the cloak appears. Combine it with the relaxation of the frame (except the cloak place) to create the final output.

cloak = cv2.bitwise_and(background, background, mask=mask)
inverse_mask = cv2.bitwise_not(mask)
rest = cv2.bitwise_and(frame, frame, mask=inverse_mask)
final_output = cv2.addWeighted(cloak, 1, rest, 1, 0)

Step 7: Display the final output in a window. The user can exit the program by pressing the ‘q’ key. Release the webcam and close all OpenCV windows.

cv2.imshow('Invisible Cloak', final_output)
if cv2.waitKey(1) & 0xFF == ord('q'):
    break
cap.release()
cv2.destroyAllWindows()

OUTPUT:

When the program runs, the region of the cloak becomes invisible, revealing the captured background in its place. This effect works in real-time using your webcam.