Ever heard about the cloak of invisibility?

If you are a potterhead, you can definitely recollect how Harry used it to deceive others in times of need.

Requirements

python3 or Anaconda should be installed opencv2 should be installed numpy should be installed

Download the invisibilitinator.py file from this repo Open the terminal and go the directory where it's saved Enter the command python pydeceive.py Your webcam will turn on in a few seconds Please don't stay in front of the camera for some time Now come back with your magic cloak[default:red] and see the magic happen When you are done playing press Esc to quit and the clip would be saved in the same directory

Firstly lets understand how to access our camera: To record a video import cv2

cap = cv2.VideoCapture(0)

if not cap.isOpened(): raise IOError("Cannot open webcam")

while True: ret, frame = cap.read() frame = cv2.resize(frame, None, fx=0.5, fy=0.5, interpolation=cv2.INTER_AREA) cv2.imshow('Input', frame)

k = cv2.waitKey(1)
if k == 27:
    break

cap.release() cv2.destroyAllWindows() OpenCV provides a very simple interface to this.(I am using the in-built webcam of my laptop) import cv2 To capture a video, you need to create a VideoCapture object. Its argument can be either the device index or the name of a video file. Device index is just the number to specify which camera. Normally one camera will be connected (as in my case). So I simply pass 0 (or -1). You can select the second camera by passing 1 and so on. cap = cv2.VideoCapture(0) Once it's created, we start an infinite loop and keep reading frames from the webcam until we encounter a keyboard interrupt while True: ret, frame = cap.read() Here, ret is a Boolean value returned by the read function, and it indicates whether or not the frame was captured successfully. If the frame is captured correctly, it's stored in the variable frame

As we know, the ASCII value of Esc is 27. Once we encounter it, we break the loop and release the video capture object. The line cap.release() is important because it gracefully closes the webcam

    if k == 27:
         break

cap.release() cv2.destroyAllWindows() Sometimes, cap may not have initialized the capture. In that case, this code shows error. You can check whether it is initialized or not by the method cap.isOpened(). If it is True, OK. Otherwise open it using cap.open() if not cap.isOpened(): raise IOError("Cannot open webcam") Saving a video We create a VideoWriter object with following parameters for this:

First we specify the output file name (eg: output.avi). Second we specify the FourCC code. - FourCC is a 4-byte code used to specify the video codec. - The list of available codes can be found in fourcc.org. - It is platform dependent Third we specify the number of frames per second (fps) and frame size should be passed. Lastly we specify the isColor flag. If it is True, encoder expect color frame, otherwise it works with grayscale frame fourcc = cv2.VideoWriter_fourcc(*'XVID') out = cv2.VideoWriter('wizard_cloack.avi' , fourcc, 20.0, (640,480)) Extracting our background We will replace the current frame pixels corresponding to the cloth with the background pixels to generate the effect of an invisibility cloak. For this we need to store the frame of a static background background = 0 for i in range(30): ret, background = cap.read() As the background is static we could have used a single capture. However at times the image captured is a bit dark compared to when multiple frames are captured. Thus capturing multiple images of static background with a for loop is more preferrble Averaging over multiple frames also reduces noise Detecting the our magical cloak By default we are using a red color cloak for our magic trick For an RGB (Red-Green-Blue) image we can simply threshold the R channel and get our mask. However this is not effective since the RGB values are highly sensitive to illumination. Although our cloak would be of red color,there might be certain parts where, due-to shadow, Red channel values of the corresponding pixels are quite low and we could be exposed! Thus we transform the color space of our image from RGB to HSV (Hue – Saturation – Value) hsv=cv2.cvtColor(img, cv2.COLOR_BGR2HSV)

The Hue values are actually distributed over a circle (range between 0-360 degrees) but in OpenCV to fit into 8bit value the range is from 0-180. The red color is represented by 0-30 as well as 150-180 values.

We use the range 0-10 and 170-180 to avoid detection of skin as red. For the saturation(S) values a high range of 120-255 is used because as our cloak would be of highly saturated red color. For the value parameter(V),the lower rangeis 70 so that we can detect red color in the wrinkles of the cloth as well

# Forming mask 1 for red range_1
lower_red = np.array([0,120,70])
upper_red = np.array([10,255,255])
mask1 = cv2.inRange(hsv, lower_red, upper_red)

# Forming mask 2 for red range_2
lower_red = np.array([170,120,70])
upper_red = np.array([180,255,255])
mask2 = cv2.inRange(hsv,lower_red,upper_red)

Now we combine masks generated for both the red color ranges by doing an pixel-wise OR operation mask1 = mask1 + mask2 Segmenting out our magic cloak and making us invisible The pixel values of the detected red color region are replaced with corresponding pixel values of the static background and an augmented output is generated which creates the magical effect. We use bitwise_and operation first to create an image with pixel values, corresponding to the detected region, equal to the pixel values of the static background and then add the output to the image from which we had segmented out the red cloak

Creating an inverted mask to segment out the cloak from the frame mask2 = cv2.bitwise_not(mask1) Segmenting the cloak out of the frame using bitwise_and and with the inverted mask layer1 = cv2.bitwise_and(background, background, mask=mask1) Creating an image showing static background frame pixels only for the masked region layer2 = cv2.bitwise_and(img, img, mask=mask2) Finally combining the layers to make us invisible final_output = cv2.addWeighted(layer1 , 1, layer2 , 1, 0)