Part 2 Simple Hand Controller using Mediapipe

In this part, to get familiar with the hand information, you will implement a small program that will read the hands information and control the threshold filter of the image.(see https://docs.opencv.org/4.x/d7/d4d/tutorial_py_thresholding.html )

The threshold function below, takes the pixels in the images and basically set their value to zeros if they are in the range of intensity between 50 and 120.

ret, thresh = cv2.threshold(annotated_image, 50, 120, cv2.THRESH_TOZERO)

Now what we want is to use hand gesture to tune this range in real-time.

ret, thresh = cv2.threshold(annotated_image, 50+125/100*int(eDistance), 120+125/100*int(eDistance), cv2.THRESH_TOZERO)

For that we will use the distance between the tip of the thumb and the index (eDistance) Write the code to compute eDistance.

Note

Note that we use a scaling factor (125/100) that might depend on the size of your image and the distance of your hands to the screen. Feel free to adjust it to have a nice and wide range of output image as you bring your thumb and index together or apart.