# detect orange  -adjustable upper and lower Hue threshholds, lower Saturation and Value threshholds
import numpy as np
import cv2

def nothing(x):
    pass

at = str(0)
cf = cv2.getTickFrequency()
font = cv2.FONT_HERSHEY_SIMPLEX
# create video capture, trackbars 
cam = cv2.VideoCapture(0)
cv2.namedWindow('Th')
cv2.createTrackbar('HL', 'Th',8,180,nothing)
cv2.createTrackbar('HH', 'Th',18,180,nothing)
cv2.createTrackbar('SL', 'Th',60,255,nothing)
cv2.createTrackbar('VL', 'Th',60,255,nothing)

# main loop
while(1):

    st = cv2.getTickCount()
    hl = cv2.getTrackbarPos('HL', 'Th')
    hh = cv2.getTrackbarPos('HH', 'Th')
    sl = cv2.getTrackbarPos('SL', 'Th')
    vl = cv2.getTrackbarPos('VL', 'Th')
    _, frame = cam.read()
    frame = cv2.resize(frame, (320, 240), interpolation = cv2.INTER_LINEAR)
    frame = cv2.blur(frame, (3, 3))
    hsv = cv2.cvtColor(frame, cv2.COLOR_BGR2HSV)
    thresh = cv2.inRange(hsv, np.array((hl, sl, vl)), np.array((hh, 255, 255)))
    thresh2 = thresh.copy()
    contours, hierarchy = cv2.findContours(thresh, cv2.RETR_LIST, cv2.CHAIN_APPROX_SIMPLE)
    max_area = 0
    for cnt in contours:
        
        area = cv2.contourArea(cnt)
        if area > max_area:
            max_area = area
            best_cnt = cnt
    if max_area > 0:
        M = cv2.moments(best_cnt)
        cx, cy = int(M['m10']/M['m00']), int(M['m01']/M['m00'])
        cz = int(max_area) 
        cv2.rectangle(frame, (cx - 5, cy - 5), (cx + 5, cy + 5), (0, 0, 255), 2)
        cv2.putText(frame, at, (0, 50), font, 1, (0, 0, 255), 2)
    # Show it, if key pressed is 'Esc', exit the loop
    cv2.imshow('Fr', frame)
    cv2.imshow('Th', thresh2)
    et = cv2.getTickCount()
    at = str('%.1f' % (cf / (et - st)))
    if cv2.waitKey(1) == 27:
        break

# Clean up everything before leaving
cam.release()
cv2.destroyAllWindows()