def rectangularize(imgpath):
img = cv2.imread(imgpath, cv2.IMREAD_UNCHANGED)
orig = img.copy()
img = cv2.resize(img, (0,0), fx=0.1, fy=0.1)
gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
gray = cv2.GaussianBlur(gray, (5,5), 0)
edged = cv2.Canny(gray, 75, 200)
(a, contours, b) = cv2.findContours(edged.copy(), cv2.RETR_LIST, cv2.CHAIN_APPROX_SIMPLE)
contours = sorted(contours, key=cv2.contourArea, reverse = True)[:5]
ctrs = None
for c in contours:
peri = cv2.arcLength(c, True)
approx = cv2.approxPolyDP(c, 0.02 * peri, True)
if len(approx) == 4:
ctrs = approx * 10
break
# cv2.imshow('outline', img)
# cv2.waitKey(0)
# cv2.destroyAllWindows()
xd = wrap_rectangular(orig, ctrs)
cv2.drawContours(img, [ctrs], -1, (255,0,0), 2)
_, buf = cv2.imencode('.jpg', xd)
return buf.tobytes()
(a, contours, b) = cv2.findContours(edged.copy(), cv2.RETR_LIST, cv2.CHAIN_APPROX_SIMPLE)
contours = sorted(contours, key=cv2.contourArea, reverse = True)[:5]
ctrs = None
for c in contours:
peri = cv2.arcLength(c, True)
approx = cv2.approxPolyDP(c, 0.02 * peri, True)
if len(approx) == 4:
ctrs = approx
break
# cv2.imshow('outline', img)
# cv2.waitKey(0)
# cv2.destroyAllWindows()
xd = wrap_rectangular(img, ctrs)
cv2.drawContours(img, [ctrs], -1, (255,0,0), 2)
cv2.imshow('outline', xd)
cv2.imshow('img', img)
cv2.waitKey(0)
cv2.destroyAllWindows()