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import numpy as np
import matplotlib.pyplot as plt
import cv2

# load a image
img = cv2.imread('../images/14.jpg', -1)

print('Image shape ', img.shape)

# cv2.imshow('Image ',img)

#show what going on
plt.axis("off")
plt.imshow(cv2.cvtColor(img, cv2.COLOR_BGR2RGB))
plt.show()


    

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# convert to HSV color space, this will produce better color filtering
imgHSV = cv2.cvtColor(img, cv2.COLOR_BGR2HSV)

#threshold on low range of HSV red
low_redl = np.array([0, 135, 135])
low_redh = np.array([15, 255, 255])
imgThreshLow = cv2.inRange(imgHSV, low_redl, low_redh)

#threshold on high range of HSV red
high_redl = np.array([159, 135, 135])
high_redh = np.array([179, 255, 255])
imgThreshHigh = cv2.inRange(imgHSV, high_redl, high_redh)

#combine low range red thresh and high range red thresh
imgThresh = cv2.bitwise_or(imgThreshLow, imgThreshHigh)


#show what going on
plt.axis("off")
plt.imshow(imgThresh, cmap='Greys_r')
plt.show()


    

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imgThreshSmoothed = imgThresh.copy()

#open image (erode, then dilate)
kernel = np.ones((3, 3), np.uint8)
imgThreshSmoothed = cv2.erode(imgThresh, kernel, iterations=1)
imgThreshSmoothed = cv2.dilate(imgThreshSmoothed, kernel, iterations=1)
#Gaussian blur
imgThreshSmoothed = cv2.GaussianBlur(imgThreshSmoothed, (5, 5), 0)

plt.axis("off")

plt.imshow(imgThreshSmoothed, cmap='Greys_r')
plt.show()


    

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imgCanny = cv2.Canny(imgThreshSmoothed,160,80)

plt.axis("off")

plt.imshow(imgCanny, cmap='Greys_r')
plt.show()


    

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image, contours, hierarchy = cv2.findContours(imgCanny,cv2.RETR_EXTERNAL,cv2.CHAIN_APPROX_SIMPLE)
print('len(contours)',len(contours))
#plt.axis("off")
plt.imshow(imgCanny, cmap='Greys_r')
#plt.imshow(image, cmap='Greys_r')
plt.show()


    

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listOfContours = []
if len(contours) != 0:
    for cnt in contours:
        epsilon = 6.7 # something to play with to fine tune
        # print'epsilon',epsilon
        listOfContours.append(cv2.approxPolyDP(cnt, epsilon, True))

imghull2 = img.copy()
cv2.drawContours(imghull2, listOfContours, -1, (0,255,0), 3)

#show what going on
plt.axis("off")
plt.imshow(cv2.cvtColor(imghull2, cv2.COLOR_BGR2RGB))
plt.show()


    

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#is img polluted?
plt.axis("off")
plt.imshow(cv2.cvtColor(img, cv2.COLOR_BGR2RGB))
plt.show()
def convexHullIsPointingUp(hull):
    x, y, w, h = cv2.boundingRect(hull)

    aspectRatio = float(w) / h
    print(x, y, w, h, aspectRatio)
    if aspectRatio > 0.9:
        print('>0.9')
        return False

    listOfPointsAboveCenter = []
    listOfPointsBelowCenter = []

    intYcenter = y + h / 2
    print(intYcenter)

    # step through all points in convex hull
    for point in hull:
        # and add each point to
        # list of points above or below vertical center as applicable
        if point[0][1] < intYcenter:
            listOfPointsAboveCenter.append(point)

        if point[0][1] >= intYcenter:
            listOfPointsBelowCenter.append(point)

    intLeftMostPointBelowCenter = listOfPointsBelowCenter[0][0][0]
    intRightMostPointBelowCenter = listOfPointsBelowCenter[0][0][0]

    # determine left most point below center
    for point in listOfPointsBelowCenter:

            if point[0][0] < intLeftMostPointBelowCenter:
                intLeftMostPointBelowCenter = point[0][0]

        # determine right most point below center
    for point in listOfPointsBelowCenter:
        if point[0][0] >= intRightMostPointBelowCenter:
            intRightMostPointBelowCenter = point[0][0]

        # step through all points above center
    for point in listOfPointsAboveCenter:
        if point[0][0] < intLeftMostPointBelowCenter or \
         point[0][0] > intRightMostPointBelowCenter:
            return False

    # if we get here, shape has passed pointing up check
    return True


    

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print ('convexHull =', len(listOfContours))
listOfCones = []
for contour in listOfContours:
        hull = cv2.convexHull(contour)
        # print 'convexHull',len(temp)
        if (len(hull) >= 3 and len(hull) <= 10):
            print ('Lets check to see if this one pointing up')
        else:
            continue

        if convexHullIsPointingUp(hull):
            print ('Yes, ', hull, ' is Point up')
            listOfCones.append(hull)
            
print ('Number of Cones', len(listOfCones))


    

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imghull = img.copy()
cv2.drawContours(imghull, listOfCones, -1, (0, 255, 0), 3)
#show what going on
plt.axis("off")
plt.imshow(cv2.cvtColor(imghull, cv2.COLOR_BGR2RGB))
plt.show()


    

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