# Input image
image = cv2.imread('oaHUs.jpg')

# Converts to grey for better reulsts
gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)

# Converts to HSV
hsv = cv2.cvtColor(image, cv2.COLOR_BGR2HSV)

# HSV values
lower_skin = np.array([5,36,53])
upper_skin = np.array([19,120,125])

mask = cv2.inRange(hsv, lower_skin, upper_skin)

mask = cv2.erode(mask, None, iterations=2)
mask = cv2.dilate(mask, None, iterations=2)

# Finds contours
im2, cnts, hierarchy = cv2.findContours(mask.copy(), cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)

# Draws contours
for c in cnts:
    if cv2.contourArea(c) < 3000:
        continue

    (x, y, w, h) = cv2.boundingRect(c)
    cv2.rectangle(image, (x,y), (x+w,y+h), (0, 255, 0), 2)

    ## BEGIN - draw rotated rectangle
    rect = cv2.minAreaRect(c)
    box = cv2.boxPoints(rect)
    box = np.int0(box)
    cv2.drawContours(image,[box],0,(0,191,255),2)
    ## END - draw rotated rectangle

cv2.imwrite('out.png', image)