HarryPotterInvisibleCloak.py

# Importing required libraries
import cv2
import time
from matplotlib import pyplot as plt
import numpy as np

# Preparation for writing the output video
video = cv2.VideoWriter_fourcc(*'XVID')
out = cv2.VideoWriter('output.avi', video, 20.0, (640, 480))

# Capturing the initial frame from the webCam
cap = cv2.VideoCapture(0)

# Allowing the system to sleep for 3 seconds before the webCam starts
time.sleep(3)
count = 0
background = 0

# Capturing the background in range of 60
for i in range(60):
    ret, background = cap.read()
background = np.flip(background, axis=1)

# Reading every frame from the webCam, until the camera is open
for count in range(1):
    while cap.isOpened():
        ret, img = cap.read()
        if not ret:
            break
        count += 1
        img = np.flip(img, axis=1)

        # Converting the color space from BGR to HSV
        hsv = cv2.cvtColor(img, cv2.COLOR_BGR2HSV)

        # Generating masks to detect red color in the frame
        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)

        mask1 = mask1 + mask2

        # Opening and Dilating 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))

        # Creating an inverted mask to segment out the red color from the frame
        mask2 = cv2.bitwise_not(mask1)

        # Segmenting the red color part out of the frame using bitwise and with the inverted mask
        res1 = cv2.bitwise_and(img, img, mask=mask2)

        # Creating image showing static background frame pixels only for the masked region
        res2 = cv2.bitwise_and(background, background, mask=mask1)
        
        print("Vector Resultant (res1)> " + str(res1))
        print("Vector Resultant (res2)> " + str(res2))
        # Generating the final output
        finalOutput = cv2.addWeighted(res1, 1, res2, 1, 0)
        out.write(finalOutput)
        
        # print("Final Vector Integral Value> " + str(finalOutput))
        # rate = getScreenBufferRate(np.sum(finalOutput))
        # print("Sigmoid Threshold Rate (Red Index)> " + str(rate))
        
        cv2.imshow("magic", finalOutput)
        cv2.waitKey(1)

    cap.release()
    out.release()
    cv2.destroyAllWindows()
    break

plt.hist2d(finalOutput, finalOutput)
plt.show()
# def getScreenBufferRate(seed):
#     return sigmoid(seed)

# def sigmoid(x):
#     return (1 / (1 + np.exp(-x)))