def Nonbearing_Wall(img, bearingwall_img, nonbearingwall_thre, prop):
img[img <= nonbearingwall_thre] = 0
img[img > nonbearingwall_thre] = 255
img[bearingwall_img == 0] = 255
# cv.imwrite('1.jpg', img)
kernel = np.uint8(np.ones((3, 3)))
img = cv.dilate(img, kernel)
img = cv.erode(img, kernel)
img[img == 0] = 1
label_image = measure.label(img, connectivity=1)
for region in measure.regionprops(label_image):
minr, minc, maxr, maxc = region.bbox
if region.area < 100:
img[minr:maxr, minc:maxc] = 255
continue
img[img == 1] = 0
# cv.imwrite('2.jpg', img)
kernel = np.uint8(np.ones((5, 5)))
img = cv.dilate(img, kernel)
img = cv.erode(img, kernel)
# cv.imwrite('3.jpg', img)
img = remove_corner_point.Remove_corner_point(img)
# cv.imwrite('4.jpg', img)
img, contours, hierarchy = cv.findContours(img, cv.RETR_TREE,
cv.CHAIN_APPROX_SIMPLE)
# for i in range(0,len(contours)):
# for j in range(0,len(contours[i])):
# cv.rectangle(img, (contours[i][j][0][0],contours[i][j][0][1]), (contours[i][j][0][0],contours[i][j][0][1]), (0,0,0), 1)
# cv.imwrite('5.jpg', img)
nonbearingwall = Data_struct.Wall()
nonbearingwall.set_type(1)
nonbearingwall.add_contour(contours)
nonbearingwall = Wall_division.Divide_rect_for_nonbearwall(
nonbearingwall, prop)
return img, nonbearingwall
def getRuler(ori_image, image):
img_height, img_width = image.shape
image_biaochi = copy.copy(image)
enlarge = 20
thre1 = 0.95
Ruler = Data_struct.Ruler()
topRuler_y, downRuler_y = Get_ruler.get_top_down_y(image)
#leftRuler_x,rightRuler_x=Get_ruler.get_left_right_x(image)
# pdb.set_trace()
top_pointlist, top_pointlist_y = Get_ruler.get_top_Point(
image, topRuler_y, thre1)
# print(top_pointlist)
up_diff = top_pointlist[len(top_pointlist) - 1] - top_pointlist[0]
for i in range(len(top_pointlist)):
cv2.rectangle(image_biaochi,
(top_pointlist[i] - 10, top_pointlist_y[i] - 10),
(top_pointlist[i] + 10, top_pointlist_y[i] + 10),
(50, 40, 10), 3)
#cv2.imwrite('img_biaochi.jpg', image_biaochi)
result_v, result, up_num = Find_num.get_prop2(ori_image, image, topRuler_y,
top_pointlist, topRuler_y[0],
thre1)
# =============================================================================
# if len(top_pointlist) == 2: # 只有两个端点，那是最长的标尺
# result_v, result, up_num = Find_num.get_prop2(ori_image,image, topRuler_y, top_pointlist, topRuler_y[0], thre1)
# else:
# result_v, result, up_num = Find_num.get_prop1(ori_image,image,top_pointlist_y, enlarge, top_pointlist)
# #print('改后')
# =============================================================================
#result_v, result, up_num = Find_num.get_prop1(image,top_pointlist_y, enlarge, top_pointlist)
Ruler.proportion(result_v)
Ruler.scale(result)
print("scale: ", end='')
print(Ruler.out_scale())
return Ruler, up_num, up_diff, image_biaochi
def classify(init_img,Ruler,single_door,sliding_door,thres2):
img_two_rect_win, img_two_piao_win, mincc_win, minrr_win, maxcc_win, maxrr_win, mincc_two_piao, minrr_two_piao, maxcc_two_piao, maxrr_two_piao = window.Windows_detect(init_img.copy(), Ruler.out_scale(), single_door)
list_pos=sliding_door.out_base_position()
list_slidingdoor=[]
for i in range(len(list_pos)):
a_x,a_y,b_x,b_y,dis_1,dis_2=list_pos[i]
if a_x==b_x:
list_slidingdoor.append((a_x-dis_1,a_y,b_x+dis_2,b_y))
elif a_y==b_y:
list_slidingdoor.append((a_x,a_y-dis_1,b_x,b_y+dis_2))
else:
pass
for i in range(len(list_slidingdoor)):
tmp=list_slidingdoor[i]
minrr_slidingdoor.append(tmp[1])#y坐标
mincc_slidingdoor.append(tmp[0])#x坐标
maxrr_slidingdoor.append(tmp[3])#y坐标
maxcc_slidingdoor.append(tmp[2])#x坐标
list_type=[]
list_line=[]
list_dir=[]
list_wid=[]
for i in range(len(mincc_win)):
flag=0
if abs(mincc_win[i]-maxcc_win[i])>abs(minrr_win[i]-maxrr_win[i]):
dir_win=1
else:
dir_win=0
for j in range(0,len(mincc_slidingdoor)):
if abs(mincc_slidingdoor[j]-maxcc_slidingdoor[j])>abs(minrr_slidingdoor[j]-maxrr_slidingdoor[j]):
dir_sdoor=1
else:
dir_sdoor=0
if dir_win==1 and dir_sdoor==1 and abs((mincc_win[i]+maxcc_win[i])/2-(mincc_slidingdoor[j]+maxcc_slidingdoor[j])/2)<abs(mincc_slidingdoor[j]-maxcc_slidingdoor[j])/4 and abs((minrr_win[i]+maxrr_win[i])/2-(minrr_slidingdoor[j]+maxrr_slidingdoor[j])/2)<thres2:
mincc_win[i]=min(mincc_win[i],mincc_slidingdoor[j])
maxcc_win[i]=max(maxcc_win[i],maxcc_slidingdoor[j])
minrr_win[i]=min(minrr_win[i],minrr_slidingdoor[j])
maxrr_win[i]=max(maxrr_win[i],maxrr_slidingdoor[j])
flag=1
if dir_win==0 and dir_sdoor==0 and abs((minrr_win[i]+maxrr_win[i])/2-(minrr_slidingdoor[j]+maxrr_slidingdoor[j])/2)<abs(minrr_slidingdoor[j]-maxrr_slidingdoor[j])/4 and abs((mincc_win[i]+maxcc_win[i])/2-(mincc_slidingdoor[j]+maxcc_slidingdoor[j])/2)<thres2:
mincc_win[i]=min(mincc_win[i],mincc_slidingdoor[j])
maxcc_win[i]=max(maxcc_win[i],maxcc_slidingdoor[j])
minrr_win[i]=min(minrr_win[i],minrr_slidingdoor[j])
maxrr_win[i]=max(maxrr_win[i],maxrr_slidingdoor[j])
flag=1
if abs(mincc_win[i]-maxcc_win[i])>abs(minrr_win[i]-maxrr_win[i]):
line=(int((minrr_win[i]+maxrr_win[i])/2),mincc_win[i]-1,int((minrr_win[i]+maxrr_win[i])/2),maxcc_win[i])
l_dir=0
l_wid=int(abs(minrr_win[i]-maxrr_win[i])/2)
else:
line=(minrr_win[i]-1,int((mincc_win[i]+maxcc_win[i])/2),maxrr_win[i],int((mincc_win[i]+maxcc_win[i])/2))
l_dir=0
l_wid=int(abs(mincc_win[i]-maxcc_win[i])/2)
list_type.append(flag)
list_line.append(line)
list_dir.append(l_dir)
list_wid.append(l_wid)
for i in range(len(minrr_two_piao)):
if abs(mincc_win[i]-maxcc_win[i])>abs(minrr_win[i]-maxrr_win[i]):
dir_win=1
else:
dir_win=0
tmp_img=init_img[minrr_win[i]:maxrr_win[i]+1,mincc_win[i]:maxcc_win[i]+1]/255
if dir_win==1:
sum_t_img=np.sum(tmp_img,axis=1)
list_sum_img = sum_t_img.tolist()
if list_sum(list_sum_img,0,int((len(list_sum_img)-1)/2)) < list_sum(list_sum_img,int(len(list_sum_img)/2),len(list_sum_img)-1):
l_dir=1
l_wid=abs(num_line-(minrr_win[i]-1))
else:
l_dir=2
l_wid=abs(num_line-maxrr_win[i])
else:
win_normal=Data_struct.Window()
win_normal.set_type(0)
win_bay=Data_struct.Window()
win_bay.set_type(1)
win_balcony=Data_struct.Window()
win_balcony.set_type(2)
xflip_normal=[]
xflip_bay=[]
xflip_balcony=[]
yflip_normal=[]
yflip_bay=[]
yflip_balcony=[]
id_normal=[]
id_bay=[]
id_balcony=[]
base_position_normal=[]
base_position_bay=[]
base_position_balcony=[]
#Get_owner_wall.Get_owner_wall([mincc[i],minrr[i],x3,minrr[i],0,maxrr[i]-minrr[i]],bear_wall,nonbearwall)
m = len(list_type)
for i in range(m):
if list_type[i]==0:
if abs(mincc_win[i]-maxcc_win[i])>abs(minrr_win[i]-maxrr_win[i]):
xflip_normal.append(1)
yflip_normal.append(0)
else:
xflip_normal.append(0)
yflip_normal.append(1)
base_position_normal.append((list_line[i][1],list_line[i][0],list_line[i][3],list_line[i][2],list_wid[i],list_wid[i]))
id_normal.append(Get_owner_wall.Get_owner_wall([list_line[i][1],list_line[i][0],list_line[i][3],list_line[i][2],list_wid[i],list_wid[i]],bear_wall,nonbearwall))
#base_position_normal.append((list_line[i][0],list_line[i][1],list_line[i][2],list_line[i][3],list_wid[i],list_wid[i]))
if list_type[i]==1:
if abs(mincc_win[i]-maxcc_win[i])>abs(minrr_win[i]-maxrr_win[i]):
xflip_balcony.append(1)
yflip_balcony.append(0)
else:
xflip_balcony.append(0)
yflip_balcony.append(1)
base_position_balcony.append((list_line[i][1],list_line[i][0],list_line[i][3],list_line[i][2],list_wid[i],list_wid[i]))
id_balcony.append(Get_owner_wall.Get_owner_wall([list_line[i][1],list_line[i][0],list_line[i][3],list_line[i][2],list_wid[i],list_wid[i]],bear_wall,nonbearwall))
for i in range():
if list_type[i]==2:
if list_dir[i]==1:
xflip_bay.append(1)
yflip_bay.append(0)
base_position_bay.append((list_line[i][1],list_line[i][0],list_line[i][3],list_line[i][2],list_wid[i],0))
id_bay.append(Get_owner_wall.Get_owner_wall([list_line[i][1],list_line[i][0],list_line[i][3],list_line[i][2],list_wid[i],0],bear_wall,nonbearwall))
elif list_dir[i]==2:
xflip_bay.append(1)
yflip_bay.append(0)
base_position_bay.append((list_line[i][1],list_line[i][0],list_line[i][3],list_line[i][2],0,list_wid[i]))
id_bay.append(Get_owner_wall.Get_owner_wall([list_line[i][1],list_line[i][0],list_line[i][3],list_line[i][2],0,list_wid[i]],bear_wall,nonbearwall))
elif list_dir[i]==3:
xflip_bay.append(0)
yflip_bay.append(1)
base_position_bay.append((list_line[i][1],list_line[i][0],list_line[i][3],list_line[i][2],list_wid[i],0))
id_bay.append(Get_owner_wall.Get_owner_wall([list_line[i][1],list_line[i][0],list_line[i][3],list_line[i][2],list_wid[i],0],bear_wall,nonbearwall))
elif list_dir[i]==4:
xflip_bay.append(0)
yflip_bay.append(1)
base_position_bay.append((list_line[i][1],list_line[i][0],list_line[i][3],list_line[i][2],0,list_wid[i]))
id_bay.append(Get_owner_wall.Get_owner_wall([list_line[i][1],list_line[i][0],list_line[i][3],list_line[i][2],0,list_wid[i]],bear_wall,nonbearwall))
else:
print('error: the dir of bay window cannot be zero')
win_normal.add_base_position(base_position_normal)
win_normal.add_Xflip(xflip_normal)
win_normal.add_Yflip(yflip_normal)
win_normal.add_windows_id(id_normal)
win_bay.add_base_position(base_position_bay)
win_bay.add_Xflip(xflip_bay)
win_bay.add_Yflip(yflip_bay)
win_bay.add_windows_id(id_bay)
win_balcony.add_base_position(base_position_balcony)
win_balcony.add_Xflip(xflip_balcony)
win_balcony.add_Yflip(yflip_balcony)
win_balcony.add_windows_id(id_balcony)
return win_normal,win_bay,win_balcony,new_img
if __name__ == "__main__":
#png_list = [ 20]
#png_list = [48,53,54,56,58,60,62,65,68,70,71,72,73,82,83,84,91,92,93,95,97,98]
#png_list = [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14,41,42,48,53,54,56,58,60,62,65,68,70,71,72,73,82,83,84,91,92,93,95,97,98]
png_list = [i for i in range(1,53)]
#png_list = [3]
for png in png_list:
print(png)
png = str(png)
Blank_room_readfilename = "KJLtest/" + str(png) + ".png"
Blank_room_outfilename = "KJLresult/" + str(png) + '/'
mkdir(Blank_room_outfilename)
Layout = Data_struct.Layout(str(png) + ".jpg")
#原图:Blank_room_img
try:
print('正在读入图片...')
Blank_room_img = cv.imread(Blank_room_readfilename, 0)
#cv.imwrite(Blank_room_outfilename + 'Original.jpg', Blank_room_img)
print('图片读入完毕...')
except:
print(png + ': ' + '读入图片' + ' Error')
continue
try:
print('图片正在进行二值化...')
#二值化后：binary_Blank_room_img
Binary_blank_room_img = Binarization.Binary(Blank_room_img, Settings.threshold)
# cv.imwrite(Blank_room_outfilename + 'Binary.jpg', Binary_blank_room_img)
def Door_detect(nonbearwall,bearwall,img,wall_img,prop):
grad_img = sobel_demo(img)
list_nonb = []
nonb_contours = nonbearwall.out_contour()
bear_contours = bearwall.out_contour()
nonb_contours = repoint.remove_re_point(nonb_contours)
bear_contours = repoint.remove_re_point(bear_contours)
for i in range(0,len(nonb_contours)):
new_contour = nonb_contours[i].reshape(len(nonb_contours[i]),len(nonb_contours[i][0][0]))
list_nonb.append(new_contour)
for i in range(0,len(bear_contours)):
new_contour = bear_contours[i].reshape(len(bear_contours[i]),len(bear_contours[i][0][0]))
list_nonb.append(new_contour)
#print(list_nonb)
res = []
for i in range(0,len(list_nonb)):
for j in range(0,len(list_nonb[i])):
center = list_nonb[i][j,:]
# if center[0] != 483 or center[1] != 185:
# continue
if res != []:
if is_exist(center,res,prop):
continue
lines = find_arc(center,grad_img,wall_img,prop)
res += lines
for k in range(0,4):
derive_center,_ = find_wall(center,k,wall_img,prop)
#print('derive',derive_center)
if derive_center != -1:
# continue
if res != []:
if is_exist(derive_center,res,prop):
continue
lines = find_arc(derive_center,grad_img,wall_img,prop)
res += lines
# if derive_center[0] != 446 or derive_center[1] != 178:
# continue
#print('res',res)
res = get_middle_line(res,wall_img,prop)
#print(res)
img = draw_rect(res,img)
single_base_position=[]
single_Xflip=[]
single_Yflip=[]
single_door_id=[]
res = remove_repetition(res,prop)
for i in range(len(res)):
single_base_position.append((res[i][0],res[i][1],res[i][2],res[i][3],res[i][4],res[i][5]))
single_Xflip.append(res[i][6])
single_Yflip.append(res[i][7])
single_door_id.append(Get_owner_wall.Get_owner_wall((res[i][0],res[i][1],res[i][2],res[i][3],res[i][4],res[i][5]),bearwall,nonbearwall))
single_door=Data_struct.Door()
single_door.set_type(0)
single_door.add_base_position(single_base_position)
single_door.add_Xflip(single_Xflip)
single_door.add_Yflip(single_Yflip)
single_door.add_door_id(single_door_id)
#return res,img
return single_door,img
def judge_window_type(room_img, init_img, wall_img, sliding_door, bear_wall,
nonbearwall, mincc_two_rect_win, minrr_two_rect_win,
maxcc_two_rect_win, maxrr_two_rect_win, mincc_two_piao,
minrr_two_piao, maxcc_two_piao, maxrr_two_piao, thres1,
thres2, prop, is_drawing):
new_img = cv2.cvtColor(room_img.copy(), cv2.COLOR_GRAY2RGB)
#
# init_img = Binarization.Binary(new_img,Settings.threshold)
list_pos = sliding_door.out_base_position()
list_slidingdoor = []
for i in range(len(list_pos)):
a_x, a_y, b_x, b_y, dis_1, dis_2 = list_pos[i]
if a_x == b_x:
list_slidingdoor.append((a_x - dis_1, a_y, b_x + dis_2, b_y))
elif a_y == b_y:
list_slidingdoor.append((a_x, a_y - dis_1, b_x, b_y + dis_2))
else:
pass
minrr_slidingdoor = [] #y坐标
mincc_slidingdoor = [] #x坐标
maxrr_slidingdoor = [] #y坐标
maxcc_slidingdoor = [] #x坐标
for i in range(len(list_slidingdoor)):
tmp = list_slidingdoor[i]
minrr_slidingdoor.append(tmp[1]) #y坐标
mincc_slidingdoor.append(tmp[0]) #x坐标
maxrr_slidingdoor.append(tmp[3]) #y坐标
maxcc_slidingdoor.append(tmp[2]) #x坐标
# mincc_rect, minrr_rect, maxcc_rect, maxrr_rect = Windows_decoration.get_rect_corner_position(init_img.copy(), 200, 100)
# mincc_three_rect_win, minrr_three_rect_win, maxcc_three_rect_win, maxrr_three_rect_win, img_three_rect_win, biaohao_rect = Windows_decoration.detect_three_rect_followup_windows(init_img.copy(), wall_img.copy(), mincc_rect, minrr_rect, maxcc_rect, maxrr_rect, 20, 2.0, 15, prop, 70, 300, 2.0)
# mincc_two_rect_win, minrr_two_rect_win, maxcc_two_rect_win, maxrr_two_rect_win, img_two_rect_win, biaohao_rect = Windows_decoration.detect_two_rect_windows(init_img.copy(), wall_img.copy(), biaohao_rect, mincc_rect, minrr_rect, maxcc_rect, maxrr_rect, 20, 2.0, 15, prop, 70, 300)
#
# mincc_ban, minrr_ban, maxcc_ban, maxrr_ban = Windows_decoration.get_ban_corner_position(init_img.copy(), 200, 0.3)
# mincc_three_rect_ban_win, minrr_three_rect_ban_win, maxcc_three_rect_ban_win, maxrr_three_rect_ban_win, img_three_rect_ban_win, biaohao_ban = Windows_decoration.detect_three_rect_ban_windows(init_img.copy(), mincc_ban, minrr_ban, maxcc_ban, maxrr_ban, 5, prop, 70, 300)
# mincc_two_rect_ban_win, minrr_two_rect_ban_win, maxcc_two_rect_ban_win, maxrr_two_rect_ban_win, img_two_rect_ban_win, biaohao_ban = Windows_decoration.detect_two_rect_ban_windows(init_img.copy(), wall_img.copy(), biaohao_ban, mincc_ban, minrr_ban, maxcc_ban, maxrr_ban, 5, prop, 70, 300)
#
# mincc_piao, minrr_piao, maxcc_piao, maxrr_piao = Windows_decoration.get_piao_corner_position(init_img.copy(), 200, 0.4)
# mincc_three_piao, minrr_three_piao, maxcc_three_piao, maxrr_three_piao, img_three_piao_win, biaohao_piao = Windows_decoration.detect_three_piao_windows(init_img.copy(), mincc_piao, minrr_piao, maxcc_piao, maxrr_piao, 5, 10, prop, 70, 300)
# mincc_two_piao, minrr_two_piao, maxcc_two_piao, maxrr_two_piao, img_two_piao_win, biaohao_piao = Windows_decoration.detect_two_piao_windows(init_img.copy(), wall_img.copy(), biaohao_piao, mincc_piao, minrr_piao, maxcc_piao, maxrr_piao, 5, 10, prop, 70, 300)
#
#img_two_rect_win, img_two_piao_win, mincc_two_rect_win, minrr_two_rect_win, maxcc_two_rect_win, maxrr_two_rect_win, mincc_two_piao, minrr_two_piao, maxcc_two_piao, maxrr_two_piao = window.Windows_detect(init_img.copy(), 1/prop, single_door)
mincc_three_rect_win = []
minrr_three_rect_win = []
maxcc_three_rect_win = []
maxrr_three_rect_win = []
mincc_three_rect_ban_win = []
minrr_three_rect_ban_win = []
maxcc_three_rect_ban_win = []
maxrr_three_rect_ban_win = []
mincc_three_piao = []
minrr_three_piao = []
maxcc_three_piao = []
maxrr_three_piao = []
mincc_two_rect_ban_win = []
minrr_two_rect_ban_win = []
maxcc_two_rect_ban_win = []
maxrr_two_rect_ban_win = []
mincc_win = []
minrr_win = []
maxcc_win = []
maxrr_win = []
two_mincc_win = []
two_minrr_win = []
two_maxcc_win = []
two_maxrr_win = []
for i in range(len(mincc_three_rect_win)):
mincc_win.append(mincc_three_rect_win[i])
minrr_win.append(minrr_three_rect_win[i])
maxcc_win.append(maxcc_three_rect_win[i])
maxrr_win.append(maxrr_three_rect_win[i])
for i in range(len(mincc_three_rect_ban_win)):
mincc_win.append(mincc_three_rect_ban_win[i])
minrr_win.append(minrr_three_rect_ban_win[i])
maxcc_win.append(maxcc_three_rect_ban_win[i])
maxrr_win.append(maxrr_three_rect_ban_win[i])
for i in range(len(mincc_three_piao)):
mincc_win.append(mincc_three_piao[i])
minrr_win.append(minrr_three_piao[i])
maxcc_win.append(maxcc_three_piao[i])
maxrr_win.append(maxrr_three_piao[i])
#两层
for i in range(len(mincc_two_rect_win)):
two_mincc_win.append(mincc_two_rect_win[i])
two_minrr_win.append(minrr_two_rect_win[i])
two_maxcc_win.append(maxcc_two_rect_win[i])
two_maxrr_win.append(maxrr_two_rect_win[i])
for i in range(len(mincc_two_rect_ban_win)):
two_mincc_win.append(mincc_two_rect_ban_win[i])
two_minrr_win.append(minrr_two_rect_ban_win[i])
two_maxcc_win.append(maxcc_two_rect_ban_win[i])
two_maxrr_win.append(maxrr_two_rect_ban_win[i])
for i in range(len(mincc_two_piao)):
two_mincc_win.append(mincc_two_piao[i])
two_minrr_win.append(minrr_two_piao[i])
two_maxcc_win.append(maxcc_two_piao[i])
two_maxrr_win.append(maxrr_two_piao[i])
###############################
tmp_mincc_win = mincc_win.copy()
tmp_minrr_win = minrr_win.copy()
tmp_maxcc_win = maxcc_win.copy()
tmp_maxrr_win = maxrr_win.copy()
for i in range(len(mincc_slidingdoor)):
tmp_mincc_win.append(mincc_slidingdoor[i])
tmp_minrr_win.append(minrr_slidingdoor[i])
tmp_maxcc_win.append(maxcc_slidingdoor[i])
tmp_maxrr_win.append(maxrr_slidingdoor[i])
for j in range(len(two_mincc_win)):
mincc_win.append(two_mincc_win[j])
minrr_win.append(two_minrr_win[j])
maxcc_win.append(two_maxcc_win[j])
maxrr_win.append(two_maxrr_win[j])
###############################
# new_img = draw_rect(filename,two_mincc_win,two_minrr_win,two_maxcc_win,two_maxrr_win,(0,0,255))
# cv2.imwrite('my_img.jpg', new_img)
# aaaa=[]
# for i in range(len(mincc_win)):
# aaaa.append([mincc_win[i],minrr_win[i],maxcc_win[i],maxrr_win[i]])
list_type = []
list_line = []
list_dir = [] ## 0：占位符 1：上 2：下 3：左 4：右
list_wid = []
for i in range(0, len(mincc_win)):
if abs(mincc_win[i] - maxcc_win[i]) > abs(minrr_win[i] - maxrr_win[i]):
dir_win = 1
else:
dir_win = 0
tmp = 0 #0:普通窗 1:阳台 2：飘窗 -1:删除
line = (-1, -1, -1, -1)
l_dir = 0
l_wid = -1
#长宽太小删除窗户
if max(abs(mincc_win[i] - maxcc_win[i]),
abs(minrr_win[i] - maxrr_win[i])) < 375 * prop:
tmp = -1
###############
# t_img=init_img[minrr_win[i]-1:maxrr_win[i]+1,mincc_win[i]-1:maxcc_win[i]+1]
# my_sum1=np.sum(t_img,axis=1)
# my_list_img1 = my_sum1.tolist()
#
# my_sum2=np.sum(t_img,axis=0)
# my_list_img2 = my_sum2.tolist()
#窗户短边太长，删除
# if my_list_img1[0]==0 and my_list_img1[len(my_list_img1)-1]==0 and my_list_img2[0]==0 and my_list_img2[len(my_list_img2)-1]==0:
# a,b=t_img.shape
# if min(a,b)>750*prop:
# tmp=-1
#################
#检测阳台
for j in range(0, len(mincc_slidingdoor)):
if abs(mincc_slidingdoor[j] -
maxcc_slidingdoor[j]) > abs(minrr_slidingdoor[j] -
maxrr_slidingdoor[j]):
dir_sdoor = 1
else:
dir_sdoor = 0
# print(abs((minrr_win[i]+maxrr_win[i])/2-(minrr_slidingdoor[j]+maxrr_slidingdoor[j])/2))
# print(thres2)
if dir_win == 1 and dir_sdoor == 1 and abs(
(mincc_win[i] + maxcc_win[i]) / 2 -
(mincc_slidingdoor[j] + maxcc_slidingdoor[j]) / 2
) < abs(mincc_slidingdoor[j] - maxcc_slidingdoor[j]) / 4 and abs(
(minrr_win[i] + maxrr_win[i]) / 2 -
(minrr_slidingdoor[j] + maxrr_slidingdoor[j]) / 2) < thres2:
tmp = 1
mincc_win[i] = min(mincc_win[i], mincc_slidingdoor[j])
maxcc_win[i] = max(maxcc_win[i], maxcc_slidingdoor[j])
minrr_win[i] = min(minrr_win[i], minrr_slidingdoor[j])
maxrr_win[i] = max(maxrr_win[i], maxrr_slidingdoor[j])
# print(abs((mincc_win[i]+maxcc_win[i])/2-(mincc_slidingdoor[j]+maxcc_slidingdoor[j])/2))
# print(thres2)
if dir_win == 0 and dir_sdoor == 0 and abs(
(minrr_win[i] + maxrr_win[i]) / 2 -
(minrr_slidingdoor[j] + maxrr_slidingdoor[j]) / 2
) < abs(minrr_slidingdoor[j] - maxrr_slidingdoor[j]) / 4 and abs(
(mincc_win[i] + maxcc_win[i]) / 2 -
(mincc_slidingdoor[j] + maxcc_slidingdoor[j]) / 2) < thres2:
tmp = 1
mincc_win[i] = min(mincc_win[i], mincc_slidingdoor[j])
maxcc_win[i] = max(maxcc_win[i], maxcc_slidingdoor[j])
minrr_win[i] = min(minrr_win[i], minrr_slidingdoor[j])
maxrr_win[i] = max(maxrr_win[i], maxrr_slidingdoor[j])
#################
#检测飘窗
if tmp == 0 and tmp != -1:
if dir_win == 1:
tmp_img = init_img[:, mincc_win[i] - 1:maxcc_win[i] + 1] / 255
sum_t_img = np.sum(tmp_img, axis=1)
list_sum_img = sum_t_img.tolist()
if list_sum_img[minrr_win[i] -
1] == 0 and list_sum_img[maxrr_win[i]] == 0:
if check_line(
init_img, (minrr_win[i] - 1, mincc_win[i] - 1),
(minrr_win[i] - 1, maxcc_win[i]),
-1, thres1)[0] or check_line(
init_img, (maxrr_win[i], mincc_win[i] - 1),
(maxrr_win[i], maxcc_win[i]), 1, thres1)[0]:
num_line = max(
check_line(init_img,
(minrr_win[i] - 1, mincc_win[i] - 1),
(minrr_win[i] - 1, maxcc_win[i]), -1,
thres1)[1],
check_line(init_img,
(maxrr_win[i], mincc_win[i] - 1),
(maxrr_win[i], maxcc_win[i]), 1,
thres1)[1])
if num_line >= maxrr_win[i]:
l_dir = 1
l_wid = abs(num_line - (minrr_win[i] - 1))
if num_line < minrr_win[i] - 1:
l_dir = 2
l_wid = abs(num_line - maxrr_win[i])
tmp = 2
line = (num_line, mincc_win[i] - 1, num_line,
maxcc_win[i])
if list_sum_img[minrr_win[i] -
1] == 0 and list_sum_img[maxrr_win[i]] > 0:
new_pointA, new_pointB = get_new_points(
init_img, (maxrr_win[i], mincc_win[i] - 1),
(maxrr_win[i], maxcc_win[i]))
if check_line(init_img, new_pointA, new_pointB, 1,
thres1)[0]:
num_line = check_line(init_img, new_pointA, new_pointB,
1, thres1)[1]
l_dir = 1
l_wid = abs(num_line - (minrr_win[i] - 1))
tmp = 2
line = (num_line, mincc_win[i] - 1, num_line,
maxcc_win[i])
if list_sum_img[minrr_win[i] -
1] > 0 and list_sum_img[maxrr_win[i]] == 0:
new_pointA, new_pointB = get_new_points(
init_img, (minrr_win[i] - 1, mincc_win[i] - 1),
(minrr_win[i] - 1, maxcc_win[i]))
if check_line(init_img, new_pointA, new_pointB, -1,
thres1)[0]:
num_line = check_line(init_img, new_pointA, new_pointB,
-1, thres1)[1]
l_dir = 2
l_wid = abs(num_line - maxrr_win[i])
tmp = 2
line = (num_line, mincc_win[i] - 1, num_line,
maxcc_win[i])
else:
tmp_img = init_img[minrr_win[i] - 1:maxrr_win[i] + 1, :] / 255
sum_t_img = np.sum(tmp_img, axis=0)
list_sum_img = sum_t_img.tolist()
if list_sum_img[mincc_win[i] -
1] == 0 and list_sum_img[maxcc_win[i]] == 0:
if check_line(init_img,
(minrr_win[i] - 1, mincc_win[i] - 1),
(maxrr_win[i], mincc_win[i] - 1), -1,
thres1)[0] or check_line(
init_img,
(minrr_win[i] - 1, maxcc_win[i] + 1),
(maxrr_win[i] + 1, maxcc_win[i] + 1), 1,
thres1)[0]:
num_line = max(
check_line(init_img,
(minrr_win[i] - 1, mincc_win[i] - 1),
(maxrr_win[i], mincc_win[i] - 1), -1,
thres1)[1],
check_line(init_img,
(minrr_win[i] - 1, maxcc_win[i] + 1),
(maxrr_win[i] + 1, maxcc_win[i] + 1), 1,
thres1)[1])
if num_line >= maxcc_win[i]:
l_dir = 3
l_wid = abs(num_line - (mincc_win[i] - 1))
if num_line < mincc_win[i] - 1:
l_dir = 4
l_wid = abs(num_line - maxcc_win[i])
tmp = 2
line = (minrr_win[i] - 1, num_line, maxrr_win[i],
num_line)
if list_sum_img[mincc_win[i] -
1] == 0 and list_sum_img[maxcc_win[i]] > 0:
new_pointA, new_pointB = get_new_points(
init_img, (minrr_win[i] - 1, maxcc_win[i]),
(maxrr_win[i], maxcc_win[i]))
if check_line(init_img, new_pointA, new_pointB, 1,
thres1)[0]:
num_line = check_line(init_img, new_pointA, new_pointB,
1, thres1)[1]
l_dir = 3
l_wid = abs(num_line - (mincc_win[i] - 1))
tmp = 2
line = (minrr_win[i] - 1, num_line, maxrr_win[i],
num_line)
if list_sum_img[mincc_win[i] -
1] > 0 and list_sum_img[maxcc_win[i]] == 0:
new_pointA, new_pointB = get_new_points(
init_img, (minrr_win[i] - 1, mincc_win[i] - 1),
(maxrr_win[i], mincc_win[i] - 1))
if check_line(init_img, new_pointA, new_pointB, -1,
thres1)[0]:
num_line = check_line(init_img, new_pointA, new_pointB,
-1, thres1)[1]
l_dir = 4
l_wid = abs(num_line - maxcc_win[i])
tmp = 2
line = (minrr_win[i] - 1, num_line, maxrr_win[i],
num_line)
##################
if tmp == 0 or tmp == 1:
if abs(mincc_win[i] - maxcc_win[i]) > abs(minrr_win[i] -
maxrr_win[i]):
line = (int(
(minrr_win[i] + maxrr_win[i]) / 2), mincc_win[i] - 1,
int((minrr_win[i] + maxrr_win[i]) / 2), maxcc_win[i])
l_dir = 0
l_wid = int(abs(minrr_win[i] - maxrr_win[i]) / 2)
else:
line = (minrr_win[i] - 1, int(
(mincc_win[i] + maxcc_win[i]) / 2), maxrr_win[i],
int((mincc_win[i] + maxcc_win[i]) / 2))
l_dir = 0
l_wid = int(abs(mincc_win[i] - maxcc_win[i]) / 2)
list_type.append(tmp)
list_line.append(line)
list_dir.append(l_dir)
list_wid.append(l_wid)
###画图
m = len(list_type)
for i in range(m):
if list_type[i] == 0:
(a_x, a_y, b_x, b_y) = list_line[i]
cv2.line(new_img, (a_y, a_x), (b_y, b_x), (255, 255, 0), 6)
if a_x == b_x:
a_x -= list_wid[i]
b_x += list_wid[i]
elif a_y == b_y:
a_y -= list_wid[i]
b_y += list_wid[i]
cv2.rectangle(new_img, (a_y, a_x), (b_y, b_x), (0, 0, 255), 3)
if list_type[i] == 1:
(a_x, a_y, b_x, b_y) = list_line[i]
cv2.line(new_img, (a_y, a_x), (b_y, b_x), (255, 255, 0), 6)
if a_x == b_x:
a_x -= list_wid[i]
b_x += list_wid[i]
elif a_y == b_y:
a_y -= list_wid[i]
b_y += list_wid[i]
cv2.rectangle(new_img, (a_y, a_x), (b_y, b_x), (0, 255, 0), 3)
if list_type[i] == 2:
(a_x, a_y, b_x, b_y) = list_line[i]
cv2.line(new_img, (a_y, a_x), (b_y, b_x), (255, 255, 0), 6)
if list_dir[i] == 1:
a_x -= list_wid[i]
if list_dir[i] == 2:
b_x += list_wid[i]
if list_dir[i] == 3:
a_y -= list_wid[i]
if list_dir[i] == 4:
b_y += list_wid[i]
cv2.rectangle(new_img, (a_y, a_x), (b_y, b_x), (255, 0, 0), 3)
if is_drawing == 1:
cv2.imwrite('window_type.jpg', new_img)
#########
###存储结构体
win_normal = Data_struct.Window()
win_normal.set_type(0)
win_bay = Data_struct.Window()
win_bay.set_type(1)
win_balcony = Data_struct.Window()
win_balcony.set_type(2)
xflip_normal = []
xflip_bay = []
xflip_balcony = []
yflip_normal = []
yflip_bay = []
yflip_balcony = []
id_normal = []
id_bay = []
id_balcony = []
base_position_normal = []
base_position_bay = []
base_position_balcony = []
#Get_owner_wall.Get_owner_wall([mincc[i],minrr[i],x3,minrr[i],0,maxrr[i]-minrr[i]],bear_wall,nonbearwall)
m = len(list_type)
for i in range(m):
if list_type[i] == 0:
if abs(mincc_win[i] - maxcc_win[i]) > abs(minrr_win[i] -
maxrr_win[i]):
xflip_normal.append(1)
yflip_normal.append(0)
else:
xflip_normal.append(0)
yflip_normal.append(1)
base_position_normal.append(
(list_line[i][1], list_line[i][0], list_line[i][3],
list_line[i][2], list_wid[i], list_wid[i]))
id_normal.append(
Get_owner_wall.Get_owner_wall([
list_line[i][1], list_line[i][0], list_line[i][3],
list_line[i][2], list_wid[i], list_wid[i]
], bear_wall, nonbearwall))
#base_position_normal.append((list_line[i][0],list_line[i][1],list_line[i][2],list_line[i][3],list_wid[i],list_wid[i]))
if list_type[i] == 1:
if abs(mincc_win[i] - maxcc_win[i]) > abs(minrr_win[i] -
maxrr_win[i]):
xflip_balcony.append(1)
yflip_balcony.append(0)
else:
xflip_balcony.append(0)
yflip_balcony.append(1)
base_position_balcony.append(
(list_line[i][1], list_line[i][0], list_line[i][3],
list_line[i][2], list_wid[i], list_wid[i]))
id_balcony.append(
Get_owner_wall.Get_owner_wall([
list_line[i][1], list_line[i][0], list_line[i][3],
list_line[i][2], list_wid[i], list_wid[i]
], bear_wall, nonbearwall))
if list_type[i] == 2:
if list_dir[i] == 1:
xflip_bay.append(1)
yflip_bay.append(0)
base_position_bay.append(
(list_line[i][1], list_line[i][0], list_line[i][3],
list_line[i][2], list_wid[i], 0))
id_bay.append(
Get_owner_wall.Get_owner_wall([
list_line[i][1], list_line[i][0], list_line[i][3],
list_line[i][2], list_wid[i], 0
], bear_wall, nonbearwall))
elif list_dir[i] == 2:
xflip_bay.append(1)
yflip_bay.append(0)
base_position_bay.append(
(list_line[i][1], list_line[i][0], list_line[i][3],
list_line[i][2], 0, list_wid[i]))
id_bay.append(
Get_owner_wall.Get_owner_wall([
list_line[i][1], list_line[i][0], list_line[i][3],
list_line[i][2], 0, list_wid[i]
], bear_wall, nonbearwall))
elif list_dir[i] == 3:
xflip_bay.append(0)
yflip_bay.append(1)
base_position_bay.append(
(list_line[i][1], list_line[i][0], list_line[i][3],
list_line[i][2], list_wid[i], 0))
id_bay.append(
Get_owner_wall.Get_owner_wall([
list_line[i][1], list_line[i][0], list_line[i][3],
list_line[i][2], list_wid[i], 0
], bear_wall, nonbearwall))
elif list_dir[i] == 4:
xflip_bay.append(0)
yflip_bay.append(1)
base_position_bay.append(
(list_line[i][1], list_line[i][0], list_line[i][3],
list_line[i][2], 0, list_wid[i]))
id_bay.append(
Get_owner_wall.Get_owner_wall([
list_line[i][1], list_line[i][0], list_line[i][3],
list_line[i][2], 0, list_wid[i]
], bear_wall, nonbearwall))
else:
print('error: the dir of bay window cannot be zero')
win_normal.add_base_position(base_position_normal)
win_normal.add_Xflip(xflip_normal)
win_normal.add_Yflip(yflip_normal)
win_normal.add_windows_id(id_normal)
win_bay.add_base_position(base_position_bay)
win_bay.add_Xflip(xflip_bay)
win_bay.add_Yflip(yflip_bay)
win_bay.add_windows_id(id_bay)
win_balcony.add_base_position(base_position_balcony)
win_balcony.add_Xflip(xflip_balcony)
win_balcony.add_Yflip(yflip_balcony)
win_balcony.add_windows_id(id_balcony)
# wins=[]
# m = len(list_type)
# for i in range(m):
# if list_type[i]!=-1:
# win=Data_struct.Window()
# f_t=0
# if abs(mincc_win[i]-maxcc_win[i])>abs(minrr_win[i]-maxrr_win[i]):
# f_t=0
# else:
# f_t=1
# win.set_orientation(f_t)
# win.set_wid(list_wid[i])
# win.set_line(list_line[i])
# win.set_dir(list_dir[i])
# win.set_position(mincc_win[i],minrr_win[i],maxcc_win[i],minrr_win[i],maxcc_win[i],maxrr_win[i],mincc_win[i],maxrr_win[i])
# if list_type[i]==1:
# win.set_type(2)
# if list_type[i]==2:
# win.set_type(1)
# if list_type[i]==0:
# win.set_type(0)
# wins.append(win)
return win_normal, win_bay, win_balcony, new_img