image = cv2.imread(args["image"])
gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
cnts = utils.get_contours(gray)
cnt = max(cnts, key=cv2.contourArea)
hull = cv2.convexHull(cnt)
# cv2.drawContours(image,[hull],0, (255,0,0),2)
# cv2.imshow("Outline", image)
# cv2.waitKey()
rect = cv2.minAreaRect(hull)
box = np.int0(cv2.boxPoints(rect))
# cv2.drawContours(image,[box],0, (0,0,255),2)
# cv2.imshow("Outline", image)
# cv2.waitKey()
approx = cv2.approxPolyDP(hull, 0.02 * cv2.arcLength(hull, True), True)
print (len(approx))
if len(approx) == 4:
box = approx.reshape(4,2)
print "Poly approximation"
output = transform.four_point_transform(image, box)
cv2.imshow("Output", output)
cv2.waitKey()
cv2.destroyAllWindows()
cv2.imwrite("unwarped_presentation.jpg", output)
image = cv2.imread(args["image"])
gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
cnts = utils.get_contours(gray)
cnt = max(cnts, key=cv2.contourArea)
hull = cv2.convexHull(cnt)
# cv2.drawContours(image,[hull],0, (255,0,0),2)
# cv2.imshow("Outline", image)
# cv2.waitKey()
rect = cv2.minAreaRect(hull)
box = np.int0(cv2.boxPoints(rect))
# cv2.drawContours(image,[box],0, (0,0,255),2)
# cv2.imshow("Outline", image)
# cv2.waitKey()
approx = cv2.approxPolyDP(hull, 0.02 * cv2.arcLength(hull, True), True)
print(len(approx))
if len(approx) == 4:
box = approx.reshape(4, 2)
print "Poly approximation"
output = transform.four_point_transform(image, box)
cv2.imshow("Output", output)
cv2.waitKey()
cv2.destroyAllWindows()
cv2.imwrite("unwarped_presentation.jpg", output)
approx = cv2.approxPolyDP(c, 0.02 * peri, True)
# if our approximated contour has four points, then we
# can assume that we have found our screen
if len(approx) == 4:
screenCnt = approx
break
# show the contour (outline) of the piece of paper
print "STEP 2: Find contours of paper"
# cv2.drawContours(image, [screenCnt], -1, (0, 255, 0), 2)
# cv2.imshow("Outline", image)
# cv2.waitKey(0)
# cv2.destroyAllWindows()
# apply the four point transform to obtain a top-down
# view of the original image
warped = four_point_transform(orig, screenCnt.reshape(4, 2) * ratio)
# convert the warped image to grayscale, then threshold it
# to give it that 'black and white' paper effect
warped = cv2.cvtColor(warped, cv2.COLOR_BGR2GRAY)
warped = utils.adaptive_threshold(warped)
warped = warped.astype("uint8")
# show the original and scanned images
print "STEP 3: Apply perspective transform"
# cv2.imshow("Original", utils.image_resize(orig, height = 650))
cv2.imshow("Scanned", utils.image_resize(warped, height=650))
cv2.waitKey(0)
# if our approximated contour has four points, then we
# can assume that we have found our screen
if len(approx) == 4:
screenCnt = approx
break
# show the contour (outline) of the piece of paper
print "STEP 2: Find contours of paper"
# cv2.drawContours(image, [screenCnt], -1, (0, 255, 0), 2)
# cv2.imshow("Outline", image)
# cv2.waitKey(0)
# cv2.destroyAllWindows()
# apply the four point transform to obtain a top-down
# view of the original image
warped = four_point_transform(orig, screenCnt.reshape(4, 2) * ratio)
# convert the warped image to grayscale, then threshold it
# to give it that 'black and white' paper effect
warped = cv2.cvtColor(warped, cv2.COLOR_BGR2GRAY)
warped = utils.adaptive_threshold(warped)
warped = warped.astype("uint8")
# show the original and scanned images
print "STEP 3: Apply perspective transform"
# cv2.imshow("Original", utils.image_resize(orig, height = 650))
cv2.imshow("Scanned", utils.image_resize(warped, height=650))
cv2.waitKey(0)
