# import required libraries
import cv2
import sys

# read the input image
img = cv2.imread('hires_test.png')


if not img:
    print("unable to read image")
    sys.exit(-1)

print("read done")

# convert the image to grayscale
gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
print("convert to gray done")

# apply thresholding on the gray image to create a binary image
ret,thresh = cv2.threshold(gray,127,255,0)

# find the contours
contours, hierarchy = cv2.findContours(thresh,cv2.RETR_TREE,cv2.CHAIN_APPROX_SIMPLE)

areas = list()

for cnt in contours:
    #print(cv2.contourArea(cnt))
    areas.append(cv2.contourArea(cnt))

areas.sort(reverse=True)

#print(areas)

if (len(areas) >= 5):
    outer = areas[0]
    inter_min = areas[4]
    print("Outer area: " + str(outer))
    print("Inner area: " + str(inter_min))

    index = 0

    for cnt in contours:
        area = cv2.contourArea(cnt)
        if( (area < outer) and (area >= inter_min)):
            # compute the bounding rectangle of the contour
            x,y,w,h = cv2.boundingRect(cnt)
            # draw the bounding rectangle
            #imgView = cv2.rectangle(img,(x,y),(x+w,y+h),(0,255,0),2)

            x = x + 5
            y = y + 5
            w = w - 10
            h = h - 10 

            crop_img = img[y:y+h, x:x+w]
            #cv2.imshow("cropped", crop_img)
            cv2.imwrite("export_"+str(index)+".png", crop_img)
            index = index + 1
            #cv2.waitKey(0)

# display the image with bounding rectangle drawn on it
#imgDownscaled = cv2.resize(imgView, (410, 876)) 
#cv2.imshow("Bounding Rectangle", imgDownscaled)
#cv2.waitKey(0)
#cv2.destroyAllWindows()