# import the necessary packages
from picamera.array import PiRGBArray
from picamera import PiCamera
import time
import cv2
import numpy as np

 
# initialize the camera and grab a reference to the raw camera capture
camera = PiCamera()
camera.resolution = (640, 480)
camera.framerate = 32
rawCapture = PiRGBArray(camera, size=(640, 480))
camera.awb_mode='fluorescent'
camera.exposure_mode='fixedfps'


 
# allow the camera to warmup
time.sleep(0.1)
 
# capture frames from the camera
for frame in camera.capture_continuous(rawCapture, format="bgr", use_video_port=True):
    # grab the raw NumPy array representing the image, then initialize the timestamp
    # and occupied/unoccupied text
    image = frame.array

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

    # define range of blue color in HSV
##    lower_blue = np.array([110,50,50])
##    upper_blue = np.array([130,255,255])

    # define range of blue color in HSV
    lower_blue = np.array([80,50,60])
    upper_blue = np.array([255,255,255])

    # Threshold the HSV image to get only blue colors
    mask = cv2.inRange(hsv, lower_blue, upper_blue)

    # Bitwise-AND mask and original image
    res = cv2.bitwise_and(image,image, mask= mask)

    #Croping the mask image around a ROI
    crop_mask=mask[50:600, 50:600]

    #close the image tho clean the mask
    kernel=np.ones((3,3), np.uint8)
    close_crop_mask=cv2.morphologyEx(crop_mask, cv2.MORPH_CLOSE, kernel)
    
    cv2.imshow('frame',image)
    cv2.imshow('mask',mask)
    cv2.imshow('close_crop_mask',close_crop_mask)
    cv2.imshow('res',res)
    k = cv2.waitKey(5) & 0xFF

    # clear the stream in preparation for the next frame
    rawCapture.truncate(0)

    if k == 2:
        break