def post_process1(self, image, mask):
w, h = image.size
img = cv2.cvtColor(np.asarray(image), cv2.COLOR_RGB2BGR)
contours, pmask = self.find_contours(image, mask)
result = {}
rect = order_points(contours)
if len(contours) > 500:
lt, rt, rb, lb = rect
if abs(lt[1] - rt[1]) > 5 or abs(rb[1] - lb[1]) > 5:
xb1, yb1, xb2, yb2 = lb[0], lb[1], rb[0], rb[1]
xt1, yt1, xt2, yt2 = lt[0], lt[1], rt[0], rt[1]
if abs(yb1 - yb2) > abs(yt1 - yt2):
pts1 = np.float32([lt, lb, rt, rb])
if yb1 > yb2:
pts2 = np.float32([lt, lb, rt, [rb[0], lb[1]]])
else:
pts2 = np.float32([lt, [lb[0], rb[1]], rt, rb])
M = cv2.getPerspectiveTransform(pts1, pts2)
warp_img = cv2.warpPerspective(img, M, (w, h))
else:
pts1 = np.float32([lt, lb, rt, rb])
if yt1 < yt2:
pts2 = np.float32([lt, lb, [rt[0], lt[1]], rb])
else:
pts2 = np.float32([[lt[0], rt[1]], lb, rt, rb])
M = cv2.getPerspectiveTransform(pts1, pts2)
warp_img = cv2.warpPerspective(img, M, (w, h))
result = {
'flag': 1,
'warp_M': M,
'keyboard_rect': None,
'warp_img': warp_img
}
else:
lr, rt, rb, lb = rect
sx, ex = int(min(lt[0], lb[0])), int(max(rt[0], rb[0]))
sy, ey = int(min(lt[1], rt[1])), int(max(lb[1], rb[1]))
flag, keyboard_rect = self.find_rect(pmask, sx, sy, ex, ey)
result = {
'flag': flag,
'warp_M': None,
'keyboard_rect': keyboard_rect,
'warp_img': None
}
else:
result = {
'flag': 0,
'warp_M': None,
'keyboard_rect': None,
'warp_img': None
}
return result
def post_process(self, image, mask):
w, h = image.size
img = cv2.cvtColor(np.asarray(image), cv2.COLOR_RGB2BGR)
contours, pmask = self.find_contours(image, mask)
# cv2.imwrite('./pmask.jpg',pmask)
# embed()
result = {}
if len(contours) > 500:
rect = order_points(contours)
lt, rt, rb, lb = rect
if abs(lt[1] - rt[1]) > 5 or abs(rb[1] - lb[1]) > 5:
xb1, yb1, xb2, yb2 = lb[0], lb[1], rb[0], rb[1]
xt1, yt1, xt2, yt2 = lt[0], lt[1], rt[0], rt[1]
center = (w // 2, h // 2)
if abs(yb1 - yb2) > abs(yt1 - yt2):
angle = calAngle(xb1, yb1, xb2, yb2)
M = cv2.getRotationMatrix2D(center, angle, 1)
rotated_img = cv2.warpAffine(img, M, (w, h))
else:
angle = calAngle(xt1, yt1, xt2, yt2)
M = cv2.getRotationMatrix2D(center, angle, 1)
rotated_img = cv2.warpAffine(img, M, (w, h))
result = {
'flag': 1,
'rote_M': M,
'warp_M': None,
'keyboard_rect': None,
'rotated_img': rotated_img
}
else:
lr, rt, rb, lb = rect
sx, ex = int(min(lt[0], lb[0])), int(max(rt[0], rb[0]))
sy, ey = int(min(lt[1], rt[1])), int(max(lb[1], rb[1]))
flag, keyboard_rect = self.find_rect(pmask, sx, sy, ex, ey)
result = {
'flag': flag,
'rote_M': None,
'warp_M': None,
'keyboard_rect': keyboard_rect,
'rotated_img': None
}
else:
result = {
'flag': 0,
'rote_M': None,
'warp_M': None,
'keyboard_rect': None,
'rotated_img': None
}
return result
def process2(mask):
mask = cv2.cvtColor(mask, cv2.COLOR_BGR2GRAY)
contours, pmask = find_contours(mask)
result = {}
rect = order_points(contours)
if len(contours) > 500:
lt, rt, rb, lb = rect
sx, ex = int(min(lt[0], lb[0])), int(max(rt[0], rb[0]))
sy, ey = int(min(lt[1], rt[1])), int(max(lb[1], rb[1]))
flag, keyboard_rect = find_rect(pmask, sx, sy, ex, ey)
result = {'flag': flag, 'keyboard_rect': keyboard_rect}
else:
result = {'flag': 0, 'keyboard_rect': None}
return result
def post_process2(self, image, mask):
w, h = image.size
img = cv2.cvtColor(np.asarray(image), cv2.COLOR_RGB2BGR)
contours, pmask = self.find_contours(image, mask)
result = {}
rect = order_points(contours)
if len(contours) > 500:
lt, rt, rb, lb = rect
sx, ex = int(min(lt[0], lb[0])), int(max(rt[0], rb[0]))
sy, ey = int(min(lt[1], rt[1])), int(max(lb[1], rb[1]))
flag, keyboard_rect = self.find_rect(pmask, sx, sy, ex, ey)
result = {'flag': flag, 'keyboard_rect': keyboard_rect}
else:
result = {'flag': 0, 'keyboard_rect': None}
return result
def main(index, image):
height, width, channels = image.shape;
gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
gray = cv2.GaussianBlur(gray, (7, 7), 0)
image = cv2.copyMakeBorder(image, 5, 5, 5, 5, cv2.BORDER_CONSTANT, value=[0,0,0])
gray = cv2.copyMakeBorder(gray, 5, 5, 5, 5, cv2.BORDER_CONSTANT, value=[0,0,0])
edged = cv2.Canny(gray, 50, 100)
cv2.imshow("test", edged)
cv2.waitKey(0);
contours, hierarchy = cv2.findContours(edged.copy(), cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)
height = edged.shape[0]
width = edged.shape[1]
MAX_COUNTOUR_AREA = (width - 10) * (height - 10)
maxAreaFound = MAX_COUNTOUR_AREA * 0.3 #object 크기는 이미지 전체의 30% 이상이어야 함.
#colors = ((0, 0, 255), (240, 0, 159), (255, 0, 0), (255, 255, 0))
rectList = [];
for cnt in contours:
if cv2.contourArea(cnt) <= maxAreaFound:
continue
box = cv2.minAreaRect(cnt)
box = cv2.boxPoints(box)
box = np.array(box, dtype="int")
rect = order_points(box)
if len(rectList) == 0:
rectList.append(rect)
else:
count = 0;
listLength = len(rectList)
isNotSameArea = True;
for oneRectInList in rectList:
if 0.99 * cv2.contourArea(rect) <= cv2.contourArea(oneRectInList) <= 1.01 * cv2.contourArea(rect):
isNotSameArea = False;
break;
if(isNotSameArea):
rectList.append(rect)
sortedRect = sorted(rectList, key=lambda oneRect: cv2.contourArea(oneRect), reverse=True)
#print(sortedRect)
roi = None
if(len(sortedRect) == 1):
roi = sortedRect[0]
else:
roi = sortedRect[1]
pts = np.array(roi, dtype = "float32")
warped = four_point_transform(image, pts)
if index != 0:
warped = random_noise(warped, 100)
warped = image_rotation(warped)
cv2.imshow("Warped", warped)
cv2.waitKey(0)
print(dhash(Image.fromarray(warped.astype('uint8'), 'RGB')))
def main(index, image):
height, width, channels = image.shape
gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
gray = cv2.GaussianBlur(gray, (7, 7), 0)
gray = cv2.GaussianBlur(gray, (7, 7), 0)
edged = cv2.Canny(gray, 30, 80) # 50 ,100
kernel = np.array([[0, 1, 0], [1, 1, 1], [0, 1, 0]], np.uint8)
edged = cv2.dilate(edged, kernel, iterations=5)
edged = cv2.erode(edged, kernel, iterations=5)
image = cv2.copyMakeBorder(image,
1,
1,
1,
1,
cv2.BORDER_CONSTANT,
value=[0, 0, 0])
edged = cv2.copyMakeBorder(edged,
1,
1,
1,
1,
cv2.BORDER_CONSTANT,
value=[1, 1, 1])
contours, hierarchy = cv2.findContours(edged.copy(), cv2.RETR_TREE,
cv2.CHAIN_APPROX_SIMPLE)
height = edged.shape[0]
width = edged.shape[1]
MAX_COUNTOUR_AREA = (width - 2) * (height - 2)
maxAreaFound = MAX_COUNTOUR_AREA * 0.35 #object 크기는 이미지 전체의 30% 이상이어야 함.
rectList = []
for cnt in contours:
box = cv2.minAreaRect(cnt)
box = cv2.boxPoints(box)
box = np.array(box, dtype="int")
if cv2.contourArea(box) <= maxAreaFound:
continue
rect = order_points(box)
if len(rectList) == 0:
rectList.append(rect)
else:
count = 0
listLength = len(rectList)
isNotSameArea = True
for oneRectInList in rectList:
if 0.99 * cv2.contourArea(rect) <= cv2.contourArea(
oneRectInList) <= 1.01 * cv2.contourArea(rect):
isNotSameArea = False
break
if (isNotSameArea):
rectList.append(rect)
sortedRect = sorted(rectList,
key=lambda oneRect: cv2.contourArea(oneRect),
reverse=True)
roi = None
if (len(sortedRect) == 1):
roi = sortedRect[0]
else:
roi = sortedRect[1]
pts = np.array(roi, dtype="float32")
warped = four_point_transform(image, pts)
if index != 0:
warped = random_noise(warped, 200)
warped = image_rotation(warped)
print(dhash(Image.fromarray(warped.astype('uint8'), 'RGB')))
def main():
filePath = sys.argv[1]
image = cv2.imread(filePath)
#image = cv2.imread("sample4.jpg")
height, width, channels = image.shape;
gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
gray = cv2.GaussianBlur(gray, (7, 7), 0)
gray = cv2.GaussianBlur(gray, (7, 7), 0)
edged = cv2.Canny(gray, 30, 80) # 30, 80
kernel = np.array([[0,1,0], [1,1,1], [0,1,0]], np.uint8)
edged = cv2.dilate(edged, kernel, iterations=5)
edged = cv2.erode(edged, kernel, iterations=5)
image = cv2.copyMakeBorder(image, 1, 1, 1, 1, cv2.BORDER_CONSTANT, value=[0,0,0])
edged = cv2.copyMakeBorder(edged, 1, 1, 1, 1, cv2.BORDER_CONSTANT, value=[1,1,1])
#cv2.imshow("test", edged)
#cv2.waitKey(0);
contours, hierarchy = cv2.findContours(edged.copy(), cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)
height = edged.shape[0]
width = edged.shape[1]
#print(image.shape)
MAX_COUNTOUR_AREA = (width - 2) * (height - 2)
maxAreaFound = MAX_COUNTOUR_AREA * 0.35 # 오브젝트 크기는 이미지 전체의 35% 이상이어야 함.
#testContourArea = MAX_COUNTOUR_AREA * 0.01; # 0.01# 0.05
#print(MAX_COUNTOUR_AREA)
colors = ((0, 0, 255), (240, 0, 159), (255, 0, 0), (255, 255, 0))
rectList = [];
for cnt in contours:
box = cv2.minAreaRect(cnt)
box = cv2.boxPoints(box)
box = np.array(box, dtype="int")
#if cv2.contourArea(box) <= maxAreaFound or cv2.contourArea(cnt) <= testContourArea :
# continue
#print(cv2.contourArea(box), " <-> ", (MAX_COUNTOUR_AREA-cv2.contourArea(box)))
#if cv2.contourArea(box) <= maxAreaFound and cv2.contourArea(cnt) <= (MAX_COUNTOUR_AREA-cv2.contourArea(box))*0.5 :
# continue
#print(cv2.contourArea(box), " <-> ", cv2.contourArea(cnt))
if cv2.contourArea(box) <= maxAreaFound:
continue
#box = cv2.minAreaRect(cnt)
#box = cv2.boxPoints(box)
#box = np.array(box, dtype="int")
rect = order_points(box)
if len(rectList) == 0:
rectList.append(rect)
else:
count = 0;
listLength = len(rectList)
isNotSameArea = True;
for oneRectInList in rectList:
if 0.99 * cv2.contourArea(rect) <= cv2.contourArea(oneRectInList) <= 1.01 * cv2.contourArea(rect):
isNotSameArea = False;
break;
if(isNotSameArea):
#print(cv2.contourArea(rect), "," ,(cv2.contourArea(rect)/MAX_COUNTOUR_AREA) * 100)
rectList.append(rect)
sortedRect = sorted(rectList, key=lambda oneRect: cv2.contourArea(oneRect), reverse=True)
#print(sortedRect)
roi = None
#사각형이 아예 안나오는 경우 버그 생길 수 있음.
if(len(sortedRect) == 1):
roi = sortedRect[0]
else:
roi = sortedRect[1]
pts = np.array(roi, dtype = "float32")
warped = four_point_transform(image, pts)
#print(warped.shape)
#cv2.imshow("Warped", warped)
#cv2.waitKey(0)
print(dhash(Image.fromarray(warped.astype('uint8'), 'RGB')))