Harry Potter's magical Cloak with opencv

Hi there, last few blogs were hardcore machine learning and AI. Today let’s learn something interesting, lets do some magic using computer vision. I hope you all know about Harry Potter’s ‘invisible cloak’, the one he uses to become invisible. We will see how we can do the same magic trick with the help of computer vision. I will code with python and use the opencv library.

Below is the video for your reference:

The algorithm is very simple, we will separate the foreground and background image with segmentation. And then remove the foreground object from every frame. We are using a red coloured cloth as foreground image; you can use any other color of your choice but need to tweak the code accordingly. We will use the following steps:

1. Import necessary libraries, create output video
2. Capture and store the background for every frame.
3. Detect the red coloured part in every frame.
4. Segment out the red coloured part with a mask image.
5. Generate the final magical output.

Step1: Import necessary libraries, create output video

Import the libraries. OpenCV is a library of programming functions mainly aimed at real-time computer vision. NumPy is the fundamental package for scientific computing with Python. In machine learning as we need to deal with a huge amount of data, we use NumPy, which is faster than normal array. Prepare for the output video.

Step2: Capture and store the background for every frame

The main idea is to replace the current frames’ red pixels with background pixels to generate the invisible effect. To do that first we need to store the background image for every frame.

cap.read() method is used to capture the current frame and stores the variables in ‘background’. The method also returns a Boolean True/False store in ret, if the frame is read correctly it returns Trues else false.

We are capturing the background in a for loop, so that we have several frames for background as averaging over multiple frames also reduces noise.

Step3: Detect the red coloured part in every frame

Now we will focus on detecting the red part of the image. As RGB (Red-Green-Blue) values are highly sensitive to illumination we will convert the RGB image to HSV (Hue – Saturation – Value) space. After we convert the frame to HSV space we will specify, some specific color range to detect the red color.

In general, the Hue values are distributed over a circle ranging between 0-360 degrees, but in OpenCV the range is from 0-180. And the red colour 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. And then combine the masks with a OR operator(for python + is used).

Step4: Segment out the red coloured part with a mask image

Now that we where the red part is in the frame from the mask image, we will use this mask to segment that part from the whole frame. We will do a morphology open and dilation for that.

Step5: Generate the final magical output

Finally, we will replace the pixels of the detected red coloured region with corresponding pixel values of the static background, which we saved earlier and finally generate the output which creates the magical effect.

So now you can create your own video with invisible cloak. You can download the running python code from here: full code

Hope you enjoyed the magical aspect of computer vision. Do let me know your feedback and suggestion in the comment below. Thank you