def __init__(self, resize):
self.image = MainCVClass(resize).image
self.accum_edged = np.zeros(self.image.shape[:2], dtype="uint8")
for chan in cv2.split(self.image):
chan = cv2.medianBlur(chan, 11)
edged = cv2.Canny(chan, 50, 200)
self.accum_edged = cv2.bitwise_or(self.accum_edged, edged)
cv2.imshow('edged map', self.accum_edged)
cv2.waitKey(0)
def __init__(self, resize):
self.image = MainCVClass(resize).image
self.boundaries = [([5, 5, 100], [80, 80, 200]),
([86, 31, 4], [220, 88, 50]),
([25, 146, 190], [62, 174, 250]),
([103, 86, 65], [145, 133, 128]),
([10, 30, 60], [140, 180, 250])]
def __init__(self, resize):
self.image = MainCVClass(resize).image
self.gray = []
self.current_contour_gray = []
self.current_contour_color = []
self.edged = []
self.ANSWER_KEY = {0: 1, 1: 4, 2: 0, 3: 3, 4: 1}
def __init__(self, resize):
self.image = MainCVClass(resize).image
cv2.imshow('image', self.image)
cv2.waitKey(0)
def __init__(self, resize):
self.image = MainCVClass(resize).image
class OpenCVTest:
def __init__(self, resize):
self.image = MainCVClass(resize).image
self.accum_edged = np.zeros(self.image.shape[:2], dtype="uint8")
for chan in cv2.split(self.image):
chan = cv2.medianBlur(chan, 11)
edged = cv2.Canny(chan, 50, 200)
self.accum_edged = cv2.bitwise_or(self.accum_edged, edged)
cv2.imshow('edged map', self.accum_edged)
cv2.waitKey(0)
def sort_contours(self, contours, method="left-to-right"):
reverse = False
i = 0
if method == "right-to-left" or method == "bottom-to-top":
reverse = True
if method == "top-to-bottom" or method == "left-to-right":
i = 1
bounding_boxes = [cv2.boundingRect(contour) for contour in contours]
(contours, bounding_boxes) = zip(*sorted(zip(contours, bounding_boxes),
key=lambda b: b[1][i],
reverse=reverse))
return (contours, bounding_boxes)
def draw_contour(self, image, i, c):
M = cv2.moments(c)
cX = int(M["m10"] / M["m00"])
cY = int(M["m01"] / M["m00"])
cv2.putText(image, "#{}".format(i + 1), (cX - 20, cY),
cv2.FONT_HERSHEY_SIMPLEX, 1.0, (255, 255, 255), 2)
return image
def sorting_contours(self):
contours = cv2.findContours(self.accum_edged.copy(), cv2.RETR_EXTERNAL,
cv2.CHAIN_APPROX_SIMPLE)
contours = imutils.grab_contours(contours)
contours = sorted(contours, key=cv2.contourArea, reverse=True)[:5]
orig = self.image.copy()
for (i, c) in enumerate(contours):
orig = self.draw_contour(orig, i, c)
cv2.imshow("unsorted", orig)
cv2.waitKey(0)
(contours,
bounding_boxes) = self.sort_contours(contours,
method=self.args["method"])
for (i, c) in enumerate(contours):
self.draw_contour(self.image, i, c)
cv2.imshow("sorted", self.image)
cv2.waitKey(0)
class OpenCVTest():
def __init__(self, resize):
self.image = MainCVClass(resize).image
def show_image(self):
cv2.imshow("Image", self.image)
cv2.waitKey(0)
def turn_image_to_gray(self, show):
gray = cv2.cvtColor(self.image, cv2.COLOR_BGR2GRAY)
if show:
cv2.imshow("Gray", gray)
cv2.waitKey(0)
else:
return gray
def edge_datection(self):
edged = cv2.Canny(self.turn_image_to_gray(False), 30, 150)
cv2.imshow("edged", edged)
cv2.waitKey(0)
return edged
def thresholding(self):
thresh = cv2.threshold(self.turn_image_to_gray(False), 225, 255,
cv2.THRESH_BINARY_INV)[1]
cv2.imshow("Thresh", thresh)
cv2.waitKey(0)
return thresh
def find_contours(self):
cnts = cv2.findContours(self.edge_datection().copy(),
cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
cnts = imutils.grab_contours(cnts)
output = self.image.copy()
for c in cnts:
cv2.drawContours(output, [c], -1, (240, 0, 159), 3)
text = "founded {} objects".format(len(cnts))
cv2.putText(output, text, (10, 25), cv2.FONT_HERSHEY_SIMPLEX, 0.7,
(240, 0, 159), 2)
cv2.imshow("Countours", output)
cv2.waitKey(0)
def erosion(self):
mask = self.thresholding().copy()
mask = cv2.erode(mask, None, iterations=5)
cv2.imshow("Eroded", mask)
cv2.waitKey(0)
def dilation(self):
mask = self.thresholding().copy()
mask = cv2.dilate(mask, None, iterations=5)
cv2.imshow("Eroded", mask)
cv2.waitKey(0)
def masking(self):
mask = self.thresholding().copy()
output = cv2.bitwise_and(self.image, self.image, mask=mask)
cv2.imshow("Output", output)
cv2.waitKey(0)
def __init__(self, resize):
self.image = MainCVClass(resize).image
self.ratio = self.image.shape[0] / 500
self.orig = self.image.copy()
class DocScan:
def __init__(self, resize):
self.image = MainCVClass(resize).image
self.ratio = self.image.shape[0] / 500
self.orig = self.image.copy()
def get_edget(self):
gray = cv2.cvtColor(self.image, cv2.COLOR_BGR2GRAY)
gray = cv2.GaussianBlur(gray, (5, 5), 0)
th3 = cv2.adaptiveThreshold(gray, 255, cv2.ADAPTIVE_THRESH_GAUSSIAN_C,
cv2.THRESH_BINARY, 11, 2)
# th3 = cv2.threshold(gray, 0, 255, cv2.THRESH_BINARY + cv2.THRESH_OTSU)[1]
edged = cv2.Canny(th3, 80, 200)
edged_for_watching = imutils.resize(edged.copy(), height=500)
# cv2.imshow('gray', gray)
cv2.imshow('th3', imutils.resize(th3, height=1000))
cv2.imshow('edged', imutils.resize(edged, height=1000))
cv2.waitKey(0)
return th3
def get_contours(self):
contours = cv2.findContours(self.get_edget().copy(), cv2.RETR_LIST,
cv2.CHAIN_APPROX_SIMPLE)
contours = imutils.grab_contours(contours)
contours = sorted(contours, key=cv2.contourArea, reverse=True)[:5]
screen_contour = np.array([])
for contour in contours:
peri = cv2.arcLength(contour, True)
approx = cv2.approxPolyDP(contour, 0.02 * peri, True)
print(len(approx))
if len(approx) == 4:
screen_contour = approx
cv2.drawContours(self.image, [screen_contour], -1, (0, 255, 0),
2)
# break
# current_contour = cv2.boundingRect(screen_contour)
# print(current_contour)
# current_contour = self.image[current_contour[0]:current_contour[1], current_contour[2]:current_contour[3]]
# current_contour = imutils.resize(current_contour, height=1000)
# print(self.image.shape)
# M = cv2.getPerspectiveTransform(screen_contour, np.float32([0, 0], []))
# current_contour = (self.image, M)
current_contour = imutils.resize(four_point_transform(
self.image, screen_contour.reshape(4, 2)),
height=1000)
gray_current_contour = cv2.cvtColor(current_contour,
cv2.COLOR_BGR2GRAY)
gray_current_contour = cv2.GaussianBlur(gray_current_contour, (5, 5),
0)
gray_current_contour = cv2.Canny(gray_current_contour, 70, 200)
cv2.imshow('outline', imutils.resize(self.image, height=1000))
cv2.imshow('current_contour', current_contour)
cv2.imshow('gray_current_contour', gray_current_contour)
cv2.waitKey(0)
return screen_contour
def rotate_image(self):
warped = four_point_transform(self.orig,
self.get_contours().reshape(4, 2))
warped = cv2.cvtColor(warped, cv2.COLOR_BGR2GRAY)
T = threshold_local(warped, 11, offset=10, method='gaussian')
warped = (warped > T).astype('uint8') * 255
cv2.imshow('warped', imutils.resize(warped, height=1000))
cv2.waitKey(0)