import cv2
import numpy as np

# Capture device number
cap = cv2.VideoCapture(1)

# Set capture resolution
cap.set(cv2.CAP_PROP_FRAME_WIDTH, 1280)
cap.set(cv2.CAP_PROP_FRAME_HEIGHT, 720)
max_count = 1

# Text
font = cv2.FONT_HERSHEY_SIMPLEX
org = (50, 50)
org2 = (50, 90)
fontScale = 1
color = (255, 0, 0)
thickness = 2

# Subwindow size
scale = 6

# Main loop
while True:
    #Grab frame
    ret, src = cap.read()

    # Get sub window size
    center = (int(src.shape[0]/2),int(src.shape[1]/2))
    upper_left = (int(center[1] - src.shape[1]/scale),int(center[0] - src.shape[0]/scale))
    lower_right = (int(center[1] + src.shape[1]/scale),int(center[0] + src.shape[0]/scale))

    # Color conversion
    gray = cv2.cvtColor(src[upper_left[1]:lower_right[1],upper_left[0]:lower_right[0]], cv2.COLOR_BGR2GRAY)
    # Edge detection
    sobel = cv2.Sobel(gray, cv2.CV_8U, 1, 0, ksize=3)
    # Thresholding operation
    t, thresh = cv2.threshold(sobel, 200, 255, cv2.THRESH_BINARY)
    count = np.sum(sobel)
    if count > max_count:
        max_count = count

    # Text rendering
    src = cv2.putText(src, 'Max: {}'.format(int(max_count/10000)), org, font, fontScale,
                      color, thickness, cv2.LINE_AA)
    src = cv2.putText(src, 'Current: {:.2f}%'.format((count/max_count)*100 - 0.01), org2, font, fontScale,
                      color, thickness, cv2.LINE_AA)
    # Subwindow Outline
    src = cv2.rectangle(src, pt1=upper_left, pt2=lower_right, color=(36,255,12), thickness=1)

    #Display of results
    cv2.imshow('tresh', thresh)
    cv2.imshow('src', src)
    cv2.imshow('sobel', sobel)

    # Frame waiting and logic loop    
    k = cv2.waitKey(10)
    if k == 27: #Escape key to escape
        break
    elif k == 32: # Spacebar to reset count
        max_count = 1