# inspiration: https://www.pyimagesearch.com/2016/03/28/measuring-size-of-objects-in-an-image-with-opencv/
from scipy.spatial import distance as dist
from imutils import perspective
from imutils import contours
import numpy as np
import cv2
import imutils


# program configuration variables

# input file
image = cv2.imread('spore-40x.png')

# pixels per um
pixelsPerMetric = 9.7

# minimum allowed spores which are measured
minSporeSize = 3

# maximum allowed spore size
maxSporeSize = 14


def midpoint(ptA, ptB):
    return ((ptA[0] + ptB [0]) * 0.5, (ptA[1] + ptB[1]) * 0.5)

# grayscale and blur it
gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
#blured = cv2.GaussianBlur(gray, (3, 3), 0)
blured = cv2.GaussianBlur(gray, (7, 7), 0)

# perform edge detection, dilation and erosion to close gaps bewteen object edges
edged = cv2.Canny(blured, 20, 100)

edged = cv2.dilate(edged, None, iterations=1)
edged = cv2.erode(edged, None, iterations=1)

cv2.imshow("Image", edged)
cv2.waitKey(0)

# find contours
cnts = cv2.findContours(edged.copy(), cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
cnts = imutils.grab_contours(cnts)

# sort contours from left to right
# pixels per petric calibration variable
(cnts, _) =  contours.sort_contours(cnts)

orig = image.copy()
# measuring all contours
for idx, c in enumerate(cnts):
    # ignore contours, whoich are not sufficient large

    # buggy
    #print(cv2.contourArea(c))
    #if cv2.contourArea(c) < 100 or cv2.contourArea(c) > 100*100:
    #    continue

    #orig = image.copy()
    box = cv2.minAreaRect(c)
    box = cv2.cv.BoxPoints(box) if imutils.is_cv2() else cv2.boxPoints(box)
    box = np.array(box, dtype='int')


    box = perspective.order_points(box)
    cv2.drawContours(orig, [box.astype("int")], -1, (0, 255, 0), 1)

    # loop over points and draw them
    for (x, y) in box:
        cv2.circle(orig, (int(x), int(y)), 2, (0, 0, 255), -1)

    # unpack the ordered bounding box, then compute the midpoint
    # between the top-left and top-right coordinates, followed by
    # the midpoint between bottom-left and bottom-right coordinates
    (tl, tr, br, bl) = box
    (tltrX, tltrY) = midpoint(tl, tr)
    (blbrX, blbrY) = midpoint(bl, br)

    # compute the midpoint between the top-left and top-right points,
    # followed by the midpoint between the top-righ and bottom-right
    (tlblX, tlblY) = midpoint(tl, bl)
    (trbrX, trbrY) = midpoint(tr, br)

    # compute the Euclidean distance between the midpoints
    dA = dist.euclidean((tltrX, tltrY), (blbrX, blbrY))
    dB = dist.euclidean((tlblX, tlblY), (trbrX, trbrY))
    # if the pixels per metric has not been initialized, then
    # compute it as the ratio of pixels to supplied metric
    # (in this case, inches)
    if pixelsPerMetric is None:
        pixelsPerMetric = 1.0#dB / 1#0.9700#args["width"]

    # compute the size of the object
    dimA = dA / pixelsPerMetric
    dimB = dB / pixelsPerMetric


    if(dimA > maxSporeSize or dimB > maxSporeSize or dimA < minSporeSize or dimB < minSporeSize):
        continue # invalid spore sizes

    # draw midpoints
    cv2.circle(orig, (int(tltrX), int(tltrY)), 2, (255, 0, 0), -1)
    cv2.circle(orig, (int(blbrX), int(blbrY)), 2, (255, 0, 0), -1)
    cv2.circle(orig, (int(tlblX), int(tlblY)), 2, (255, 0, 0), -1)
    cv2.circle(orig, (int(trbrX), int(trbrY)), 2, (255, 0, 0), -1)

    # draw lines between the midpoints
    cv2.line(orig, (int(tltrX), int(tltrY)), (int(blbrX), int(blbrY)), (255, 0, 0), 1)
    cv2.line(orig, (int(tlblX), int(tlblY)), (int(trbrX), int(trbrY)), (255, 0, 0), 1)


    # draw the object sizes on the image
    cv2.putText(orig, " {:03d}: {:2.3f} x {:2.3f} um".format(idx, dimA, dimB), (int(tltrX - 15), int(tltrY - 10)), cv2.FONT_HERSHEY_SIMPLEX, 0.4, (255, 255, 255), 1)
    #cv2.putText(orig, "{:f}px^2".format(cv2.contourArea(c)), (int(trbrX + 10), int(trbrY)), cv2.FONT_HERSHEY_SIMPLEX, 0.4, (255, 255, 255), 1)
    # cv2.putText(orig, "{:.3f}um".format(dimB), (int(trbrX + 10), int(trbrY)), cv2.FONT_HERSHEY_SIMPLEX, 0.4, (255, 255, 255), 1)

    # show the output image

    print("{:03d}: {:03.03f} um x {:03.03f} um".format(idx, dimA, dimB))
    #print(idx, dimA, "um x", dimB, "um")

cv2.imshow("Image", orig)
cv2.imwrite("output.png", orig)
cv2.waitKey(0)