threshold

import os
import cv2
def threshold(img, thresh=128, maxval=255, type=cv2.THRESH_BINARY):
    if len(img.shape) == 3:
        img = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
    threshed = cv2.threshold(img, thresh, maxval, type)[1]
    return threshed

def find_contours(img):
    kernel   = cv2.getStructuringElement(cv2.MORPH_ELLIPSE, (11,11))
    morphed  = cv2.morphologyEx(img, cv2.MORPH_CLOSE, kernel)
    cv2.imshow("morphed",morphed)
    cv2.waitKey(0)     
    contours = cv2.findContours(morphed, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
    for i in range(len(contours)):
        #cv2.drawContours(immask,[contours[i]],-1,(x+np.random.randint(0, 30),x+np.random.randint(0, 30),x+np.random.randint(0, 30)),cv2.FILLED)
        cv2.drawContours(morphed,[contours[i]],-1,(0,0,0),cv2.FILLED)
    import pdb
    pdb.set_trace()   
    cv2.imshow("morphed2",morphed)
    cv2.waitKey(0)   
    return contours[-2]

def mask_from_contours(ref_img, contours):
    mask = numpy.zeros(ref_img.shape, numpy.uint8)
    mask = cv2.drawContours(mask, contours, -1, (255,255,255), -1)
    return cv2.cvtColor(mask, cv2.COLOR_BGR2GRAY)

def dilate_mask(mask, kernel_size=11):
    kernel  = numpy.ones((kernel_size,kernel_size), numpy.uint8)
    dilated = cv2.dilate(mask, kernel, iterations=1)
    return dilated
   
img=cv2.imread("1110_3_1_X_537_Y_1700_qly_100_fail_13d17h46m24s.bmp",0)
imgray = cv2.cvtColor(img, cv2.COLOR_GRAY2BGR)
img=imgray
thresh=threshold(imgray)
threshcontours=find_contours(thresh)
mask= mask_from_contours(img, contours)
mask= dilate_mask(mask, 50)
crop= cv2.bitwise_or(img, img, mask=mask)