代码拉取完成，页面将自动刷新
from tkinter import messagebox
from prompt_toolkit.keys import Keys
from pyparsing import unicode
import myfuncBPH
import cv2
import numpy as np
import os #获得 dir
import math
from tkinter import *
import tkinter.filedialog
import tkinter.messagebox #这个是消息框，对话框的关键
from PIL import Image# BW 扩展 ，防止 H/W>2 ,右侧出现 轮廓检测 丢失。
import math
#socket
import socket
import threading
import time
import sys
# end socket
#
#s02 original img
#s03 255 single image
#s05 BW image
#s10
#s15 getShape8b() BPH_angle_operated:
#s22 LFsubImg
#s24 LF img ,before little rotate ,
#s25 shift_right_down ,prepare for little rotete
#s26 print angle , sum
#s27 adjusted img,little rotated"
#s29 img///in getshape func now",
#s30 LF part
#s39 dsetroyAllWindows in main end .
def testStandingLying(mywidth,myheight,here_angle,count_in_BPH):
if min(mywidth, myheight) < 8 and count_in_BPH>12: #small noise size, 8,9, 10
return "no_too small"
if min(mywidth,myheight)>0:
if max(mywidth,myheight)/min(mywidth,myheight)<1.35:
return "no_like square"
if mywidth < myheight:
if here_angle>70:
return "lying"
elif here_angle<20:
return "standing"
else:
return "no_angle not >70 or <20"
else:
if here_angle > 70:
return "standing"
elif here_angle < 20:
return "lying"
else:
return "no_angle not >70 or <20"
def testLying(mywidth,myheight,here_angle):
if mywidth < myheight:
if here_angle>45:
# lying = lying + 1
lying=True
else:
# standing = standing + 1
lying=False
else:
if here_angle > 45:
#standing = standing + 1
lying = False
else:
#lying = lying + 1
lying=True
return lying
def int_to_str(int_num):
lst = []
s = ''
while int_num > 0:
num = int_num % 10
lst.append(num)
int_num //= 10
for i in lst[::-1]:
s += str(i)
return s
def FillHole(im_in):
# 复制 im_in 图像
im_floodfill = im_in.copy()
# Mask 用于 floodFill，官方要求长宽+2
h, w = im_in.shape[:2]
mask = np.zeros((h + 2, w + 2), np.uint8)
# floodFill函数中的seedPoint必须是背景
isbreak = False
for i in range(im_floodfill.shape[0]):
for j in range(im_floodfill.shape[1]):
if (im_floodfill[i][j] == 0):
seedPoint = (i, j)
isbreak = True
break
if (isbreak):
break
# 得到im_floodfill
cv2.floodFill(im_floodfill, mask, seedPoint, 255);
# 得到im_floodfill的逆im_floodfill_inv
im_floodfill_inv = cv2.bitwise_not(im_floodfill)
# 把im_in、im_floodfill_inv这两幅图像结合起来得到前景
im_out = im_in | im_floodfill_inv
return im_out
def getMaxContourImg(image):
contours, hierarchy = cv2.findContours(image,cv2.RETR_TREE,cv2.CHAIN_APPROX_SIMPLE)
contours = sorted(contours,key=lambda item:cv2.contourArea(item))
x,y,w,h=cv2.boundingRect(contours[-1]) #???????? not minAreaRect ,but just statstic state ,正姿态rect ?
subImg = image[y:y+h,x:x+w]
return subImg
# refineRoi call this func,get LF image, input is large image ,return little image!!!!!???????
# no rotate !!!
def getRoiImage(image): #here image is one BPH image??, after cv2.minAreaRect -> crop_minAreaRect rotate ,it is as large as total pic .
contours, hierarchy = cv2.findContours(image,cv2.RETR_TREE,cv2.CHAIN_APPROX_SIMPLE) #
contours = sorted(contours,key=lambda item:cv2.contourArea(item)) #all lines in one BPH,
mask = np.zeros(image.shape,np.uint8) # mask ,as large as image,,,,返回来一个给定形状和类型的用0填充的数组；
cv2.drawContours(mask,[contours[-1]],-1,255,cv2.FILLED) #
#cv2.imshow("mask img", mask)
#cv2.waitKey(0)
kernel = np.ones((3,3), np.uint8)
mask = cv2.erode(mask,kernel) # filter
x,y,w,h=cv2.boundingRect(contours[-1]) #在python中，数组的下标为-1代表数组的最后一个元素，下标为-2代表数组的倒数第二个元素，......。 ### here largest area mean LF?
ROI = mask[y:y+h,x:x+w] #large image become little image!!!!!?????
return ROI
#only LF test call this func
def refineRoi(image): #here image is LFimage, after cv2.minAreaRect -> crop_minAreaRect , rotate_clock_direct degree maybe happen!!!??? ,it is large , most is blank , little is LF .
#roiImage=image ????
roiImage=getRoiImage(image) #??? # get LF rect , not as large as total pic ,,roiImage very little pic !!!!
#cv2.imshow("input img", image) #large
##cv2.waitKey(0)
cv2.imshow("LF img,,,before adjust", roiImage) #s24
#cv2.waitKey(0)
#roiImage = (image)
center= (int(roiImage.shape[0]/2),int(roiImage.shape[1]/2)) #,roiImage very little pic !!!! shape[0] heigth shape[1] width
targetShape = (roiImage.shape[0]*10,roiImage.shape[1]*10) #dest size (rows,cols))
#targetShape = (roiImage.shape[0]*8 , roiImage.shape[1]*8 )
hmax = max(int(roiImage.shape[0] / 2), int(roiImage.shape[1] / 2)) * 1.5 # 1.414
center = (hmax, hmax)
targetShape =(int(2.3*hmax), int(2.3*hmax)) #
# 声明变换矩阵 向右平移10个像素， 向下平移30个像素
#M = np.float32([[1, 0, 10], [0, 1, 30]])
# 进行2D 仿射变换
if roiImage.shape[0]>roiImage.shape[1]: #veritical
M = np.float32([[1, 0, int(hmax),], [0, 1, 0]])
LF_looks_x_or_y="y"
my_axis=0
else: #horizenal
M = np.float32([[1, 0, 0], [0, 1, int(hmax)]])
LF_looks_x_or_y="x"
my_axis = 1
shifted = cv2.warpAffine(roiImage, M, targetShape)
cv2.imshow('shift_right_down ,prrepare for little rotete', shifted) #s25
##cv2.waitKey(0)
##
maxSum=0
index=-1
for i in range(180):#(90): # 0 to 90 degree
M = cv2.getRotationMatrix2D(center, -i, 1.0) #15 M matrix is unit , #getRotationMatrix2D(Point2f center, double angle, double scale)
rotated = cv2.warpAffine(shifted, M, targetShape) #16 仿射变换 ,LF rotated, #### cv2.warpAffine(img,M,(rows,cols))
#### cv2.warpAffine(src, M, dsize, dst=None, flags=None, borderMode=None, borderValue=None) --> dst
'''
if i%10==0:
cv2.imshow("rotate img"+str(i), rotated) #large
cv2.waitKey(0)
'''
sumCols=rotated.sum(axis=my_axis)#1) #axis=0, 表示列。axis=1, 表示行。 ##here i get sum from left to right!horrizonal sum!!!
tmp=max(sumCols)
if(tmp>maxSum): # get max of maxSum_in_some_degree , ,LF is most vertical or horizonal !!! ????/
maxSum=tmp
index=i
#print("maxcols",tmp, "i index",i,index) #s26
print("LF?? adjust angle==========================================",index)
M = cv2.getRotationMatrix2D(center, -index, 1.0) #15 M matrix , #getRotationMatrix2D(Point2f center, double angle, double scale)
#print("refineroi msg:",-index*2)
rotatedRoi = cv2.warpAffine(roiImage, M, targetShape) #16
rotatedRoi=getMaxContourImg(rotatedRoi)
cv2.imshow("adjusted img,after little rotated "+str(index)+" degree", rotatedRoi) #large #s27
##cv2.waitKey(0)
return rotatedRoi,index # index is angle operate, clock direct.
# image is as large as total picture, but only one BPH appear!!!!(if reziseRATE ==1)
def getShape8b(image, BPH_angle_operated,BPHcx,BPHcy,width,height):
cv2.imshow("getShape8b() BPH_angle_operated:"+str(BPH_angle_operated), image) #s15
##cv2.waitKey(0)
H,W=image.shape
#image=image[int(0.03*H):int(0.97*H),int(0.03*W):int(0.97*W)]
#contours, hierarchy = cv2.findContours(image,cv2.RETR_TREE,cv2.CHAIN_APPROX_SIMPLE)
#contours, hierarchy = cv2.findContours(image, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
contours, hierarchy = cv2.findContours(image, cv2.RETR_LIST, cv2.CHAIN_APPROX_SIMPLE) # here contours ,is all lines inner one BPH,(in image ,only one BPH appear!!!)
num2=len(contours)
print("in this BPH, len(contours)",num2,",H W",H,W)
##got BPH size:
maxh=0
maxw=0
for item in contours: # here contours ,is all lines inner one BPH,(in image ,only one BPH appear!!!), here item is one line of one BPH.
# mini Area ,!!!! rect is more rilyable
temp_rect = cv2.minAreaRect(item)
temp_width = int(temp_rect[1][0])
temp_height = int(temp_rect[1][1])
if temp_width >maxw:
maxw=temp_width
if temp_height >maxh:
maxh=temp_height
##end got BPH size, maxh maxw,
#################erase noise
erased=False
href=maxh/30 # /10可以，/15 20 30 可以
#####if href>penWidth???
print(maxh,maxw,href)
for item in contours: # here contours ,is all lines inner one BPH,(in image ,only one BPH appear!!!), here item is one line of one BPH.
# get the rect image, test and erase ,H h n u N -> ||
(x, y, w, h) = cv2.boundingRect(item)
if max(w,h)<maxw*7/10:# LF 不要参与erase ,防止 LF短线被误擦!!!!!!!!!!!!!!!!!!!!!!!
(mm, nn, ss) = myfuncBPH.eraseBPHnoise(image[y:y + h, x:x + w], 1, href)
if ss == "erased":
erased = True
cv2.imshow('now:after erase HhnuN', image)
#cv2.waitKey(0)
# end get,test
if erased==True:#再发现一遍轮廓，
contours, hierarchy = cv2.findContours(image, cv2.RETR_LIST,
cv2.CHAIN_APPROX_SIMPLE) # here contours ,is all lines inner one BPH,(in image ,only one BPH appear!!!)
num2 = len(contours)
print("after erase HhnuN , in this BPH, len(contours)", num2, ",H W", H, W)
###################end erase
shapeType="0"#L F
shapeState="x_left" # b7 at x_left .
shapecx_BPHcx=0
shapecy_BPHcy=0
mybitindex=0
#prepeare to get pen width ,bit_size_reference
pen_width=0
#temp_min=[[0] for i in range(len(contours))]
temp_min = [0] *(len(contours)) # here contours ,is all lines inner one BPH,(in image ,only one BPH appear!!!)
temp_all_height= [0] *(len(contours))
temp_is_noise=[0] *(len(contours))
temp_index=0
if len(contours) < 9: # here contours ,is all lines inner one BPH,(in image ,only one BPH appear!!!)
# 可能1像素 宽的 笔画。
print("maybe sub too thin, inner, sub less than 9")
return 1024
for item in contours: # here contours ,is all lines inner one BPH,(in image ,only one BPH appear!!!), here item is one line of one BPH.
# mini Area ,!!!! rect is more rilyable
temp_rect = cv2.minAreaRect(item)
temp_width = int(temp_rect[1][0])
temp_height = int(temp_rect[1][1])
temp_min[temp_index ] = min(temp_height ,temp_width ) #min(h,w)
temp_all_height[temp_index]=temp_height
if min(temp_height ,temp_width )>0:
if max(temp_rect[1][0]/temp_rect[1][1],temp_rect[1][1]/temp_rect[1][0])<1.5: #if max(h/w,w/h)<1.5
#if max(temp_width/temp_height,temp_height/temp_width)<1.5:#太接近 方块 ，就是 噪点 ，不是 笔画？？
temp_is_noise[temp_index]=1
else:
temp_is_noise[temp_index] = 0
if min(temp_height, temp_width) ==0:
temp_is_noise[temp_index] = 1
temp_index+=1
#to get pen_width
temp_index=0
pen_width1=1
pen_width2=1
for iji in range (0, len(contours) ): # here contours ,is all lines inner one BPH,(in image ,only one BPH appear!!!),
if temp_is_noise[iji]==0: #随意, 不是噪点 就可以。
pen_width1=temp_min[iji] #min(h,w)
pen_width2=pen_width1
max_height=temp_all_height[0]
for item in contours: # here contours ,is all lines inner one BPH,(in image ,only one BPH appear!!!), here item is one line of one BPH.
if temp_min[temp_index]<=pen_width1 and temp_is_noise[temp_index]==0:
#pen_width2 倒数第二小的pen_width,在上边这行，必须小于等于，不能用小于。当8个 比特线 测试宽度 相等，可能会出错。
#倒数第二小，希望可以过滤 一些干扰？？
pen_width2 = pen_width1
pen_width1=temp_min[temp_index]
if temp_all_height[temp_index]>max_height:
max_height=temp_all_height[temp_index] #max_height
temp_index+=1
pen_width=pen_width2
#得到 判断 是 比特线的 依据之一： 宽度小于它 ，就是 比特线，是画刷笔宽度乘以参数：大约2.5-3.5
bit_size_width_reference = int(pen_width * 3)
print("pen_width", pen_width, ",bit_size_width_reference", bit_size_width_reference)
# use (get LF_height) or use max contour_height ,then get bit_size_reference比特最小高度(似乎，可以 过滤 小噪点)/
# 注意， 用 LF突起 高度 也可 实现， 因为 带 外 整体 边界 ， 所以 暂时 不用之。暂时 用max_height得到 这些 参考。
#bit_size_min_reference参数：0.075接近LF突起高度了，不要再小了，再小成点了。
#bit_size_max_reference参数：0.6 就差不多要与LF接触了，不要再大了
bit_size_min_reference=int(max_height*0.0715207)
bit_size_max_reference = int(max_height * 0.61)
print("bit_size_min_reference",bit_size_min_reference,",bit_size_max_reference",bit_size_max_reference)
#bit_two_state_size_reference比特二态中间分界值
bit_two_state_size_reference = int(max_height * 0.3389)#0.389
print("bit_two_state_size_reference", bit_two_state_size_reference)
#end prepare, ok
##########
##########
#test lines in this BPH
mybyteb_x=[([0] * 2) for i in range(8)]
mybyteb_y = [([0] * 2) for i in range(8)]
mem_LF_state=""
testsuccess = "no" #mark,,:
itis = [(["no"]) for i in range(3200)] # "bit" "LF",,,,#200 ,noise count maybe more than 100, so use 200!!!!!!! if camera is 1920 1200 , so more than 200, so use 1200!
##############
print("getShape8b() ,method of crossBand ,prepare: ")
inCrossBandX=[(["no"]) for i in range(3200)] # for "in" "out"
inCrossBandY = [(["no"]) for i in range(3200)] # for "in" "out"
centerX=[([0]) for i in range(3200)]
centerY = [([0]) for i in range(3200)]
largestOneCenterX=0
largestOneCenterY = 0
largestH=0
largestW = 0
herei = 0
for item in contours: # here item is one line of one BPH. maybe 11 12
myrect = cv2.minAreaRect(item)
centerX[herei]= int(myrect[0][0])
centerY[herei] = int(myrect[0][1])
mywidth = int(myrect[1][0]) # ?? width
myheight = int(myrect[1][1]) # heigth
#here_angle = -myrect[2] # -90 -10...
if myheight > largestH:
largestH=myheight
largestW= mywidth
largestOneCenterX=int(myrect[0][0])
largestOneCenterY = int(myrect[0][1])
herei = herei + 1
print("contours count ===================================================" + str(len(contours)))
herei = 0
bandLeft= largestOneCenterX-largestW/6
bandRight= largestOneCenterX + largestW / 6
bandTop = largestOneCenterY - largestH / 6
bandBottom = largestOneCenterY + largestH / 6
xBandCount=0
yBandCount=0
crossBandCount=0
or_xy_BandCount=0
and_xy_BandCount = 0
for item in contours: # here item is one line of one BPH. maybe 11 12
if centerX[herei]> bandLeft and centerX[herei]< bandRight:
inCrossBandY[herei] ="in"
yBandCount += 1
print("in-x band")
if centerY[herei]> bandTop and centerY[herei]< bandBottom:
inCrossBandX[herei] ="in"
xBandCount += 1
print("in-y band")
if inCrossBandX[herei] == "in" and inCrossBandY[herei] =="in":
and_xy_BandCount+=1
print("in both xy band happened")
if inCrossBandX[herei] == "in" or inCrossBandY[herei] =="in":
or_xy_BandCount+=1
print("in either xy band happened")
herei = herei + 1
print("kkkkkkkkk len(contours)=", len(contours)," xBandCount=", xBandCount, "yBandCount=" , yBandCount ,"or_xy_BandCount=",or_xy_BandCount,"and_xy_BandCount=",and_xy_BandCount,)
#crossband prepare ok
########### "standing" "lying" test :
print("getShape8b() ,method of standing lying :")
standing = 0#count
lying = 0 #count
LFislying = True
theirResult= [(["no"]) for i in range(3200)] # for "standing" "lying" i in range(200) i= 0 1 2 ....199
herei=0
for item in contours: # here item is one line of one BPH. maybe 11 12
myrect = cv2.minAreaRect(item)
mywidth = int(myrect[1][0]) # ?? width
myheight = int(myrect[1][1]) # heigth
here_angle=-myrect[2] # -90 -10...
result=testLying(mywidth,myheight,here_angle)
r2= testStandingLying(mywidth,myheight,here_angle,len(contours)) #if len(contours) <=12 , not test thiness of line
print("contours count ==================================================="+str(len(contours)))
#theirResult[herei] =r2
if r2 == "lying" and (inCrossBandY[herei] == "in"):
theirResult[herei] =r2
elif r2 == "standing" and (inCrossBandX[herei] == "in"):
theirResult[herei] =r2
#
if r2=="lying" and (inCrossBandY[herei]=="in"):
lying = lying + 1
elif r2=="standing" and (inCrossBandX[herei]=="in"):
standing = standing + 1
#if r2!="no":
# print(mywidth, myheight, here_angle,standing,lying,"r2=",r2)
print("w",mywidth, "H",myheight,"angle=", here_angle,"standingCount=",standing,"lyingCount=", lying, "r2=", r2)
herei = herei + 1
######################################
## refresh testsuccess , standing>10 LFislying>10,, may happen!!!!!!!!! many little noise
if standing==8 and lying==1:
testsuccess="ok"
LFislying = True
elif standing == 1 and lying == 8:
testsuccess = "ok"
LFislying = False
else:
testsuccess="no"
if standing == 8 and lying >1 and lying<8:
testsuccess = "bit_ok"
LFislying = True
elif standing > 1 and standing<8 and lying == 8:
testsuccess = "bit_ok"
LFislying = False
elif standing == 1 and lying >8:
testsuccess = "LF_ok"
LFislying = False
elif standing >8 and lying == 1:
testsuccess = "LF_ok"
LFislying = True
elif min(standing,lying) ==0 or max(standing,lying)<8:
testsuccess="fail"
# refresh itis[]
if testsuccess=="ok":
for ii in range(3200):
if LFislying == True:
if theirResult[ii]=="lying":
itis[ii]="LF"
if theirResult[ii]=="standing":
itis[ii]="bit"
if LFislying == False:
if theirResult[ii] == "lying":
itis[ii] = "bit"
if theirResult[ii] == "standing":
itis[ii] = "LF"
if testsuccess == "bit_ok": #LF still need test
for ii in range(3200):
if LFislying == True:
if theirResult[ii] == "standing":
itis[ii] = "bit"
if LFislying == False:
if theirResult[ii] == "lying":
itis[ii] = "bit"
if testsuccess=="LF_ok": #bit still need test
for ii in range(3200):
if LFislying == True:
if theirResult[ii]=="lying":
itis[ii]="LF"
if LFislying == False:
if theirResult[ii] == "standing":
itis[ii] = "LF"
print("zzzzzzzzzzzzzz len(contours)=", len(contours), "standing=",standing,"lying=",lying,"LFislying=",LFislying, "testsuccess=", testsuccess)
print(itis)
###################
###################
#go on test ,another mother ,line width test,
print("getShape8b() ,method of line_width :")
if testsuccess == "bit_ok":
ii = 0
for item in contours: # here item is one line of one BPH. maybe 11 12
myrect = cv2.minAreaRect(item)
mywidth = int(myrect[1][0]) # ?? width
myheight = int(myrect[1][1]) # heigth
myx = int(myrect[0][0]) # center x
myy = int(myrect[0][1]) # center y
# angle????myrect[2]
print("w h", mywidth, myheight, "cx cy", myx, myy)
heremin = min(mywidth, myheight)
heremax = max(mywidth, myheight)
print(heremin, bit_size_width_reference, "?> ", heremax, heremin, "DIV ?>3 ,if.. then LF found")
if LFislying == True:
if theirResult[ii] == "lying":
if (heremin >= int(bit_size_width_reference)) and ((heremax / heremin) > 3): # ???????heremin >= bit_size_width_reference???? = may happen when BPH is 45degree
itis[ii] = "LF"
else:
if theirResult[ii] == "standing":
if (heremin >= int(bit_size_width_reference)) and ((heremax / heremin) > 3): # ???????heremin >= bit_size_width_reference???? = may happen when BPH is 45degree
itis[ii] = "LF"
ii = ii + 1
#
itisLFCnt=0
for ii in range(3200):
if itis[ii] == "LF":
itisLFCnt=itisLFCnt+1
#refresh testsuccess
if itisLFCnt==1:
testsuccess="ok"
elif testsuccess == "LF_ok":
ii = 0
for item in contours: # here item is one line of one BPH. maybe 11 12
myrect = cv2.minAreaRect(item)
mywidth = int(myrect[1][0]) # ?? width
myheight = int(myrect[1][1]) # heigth
myx = int(myrect[0][0]) # center x
myy = int(myrect[0][1]) # center y
# angle????myrect[2]
print("w h", mywidth, myheight, "cx cy", myx, myy)
heremin = min(mywidth, myheight)
heremax = max(mywidth, myheight)
print(heremin, bit_size_width_reference, "?> ", heremax, heremin, "DIV ?>3 ,if.. then LF found")
if LFislying == True:
if theirResult[ii] == "standing":
if heremin <= bit_size_width_reference and heremax >= bit_size_min_reference and heremax <= bit_size_max_reference:
itis[ii] = "bit"
else:
if theirResult[ii] == "lying":
if heremin <= bit_size_width_reference and heremax >= bit_size_min_reference and heremax <= bit_size_max_reference:
itis[ii] = "bit"
ii=ii+1
#
itisbitCnt = 0
for ii in range(3200):
if itis[ii] == "bit":
itisbitCnt = itisbitCnt + 1
# refresh testsuccess
if itisbitCnt == 8:
testsuccess = "ok"
#end the test : line width test,
'''
###################
# go on test ,another mother ,in_crossBand test ,
print("getShape8b() ,method of in_crossBand :")
if testsuccess == "bit_ok":
ii = 0
for item in contours: # here item is one line of one BPH. maybe 11 12
if LFislying == True:
if theirResult[ii] == "lying":
if inCrossBandY[ii]=="in":
itis[ii] = "LF"
else:
if theirResult[ii] == "standing":
if inCrossBandX[ii]=="in":
itis[ii] = "LF"
ii = ii + 1
#
itisLFCnt = 0
for ii in range(3200):
if itis[ii] == "LF":
itisLFCnt = itisLFCnt + 1
# refresh testsuccess
if itisLFCnt == 1:
testsuccess = "ok"
print ("in_crossBand test,do it ,ok")
elif testsuccess == "LF_ok":
ii = 0
for item in contours: # here item is one line of one BPH. maybe 11 12
if LFislying == True:
if theirResult[ii] == "standing":
if inCrossBandX[ii]=="in":
itis[ii] = "bit"
else:
if theirResult[ii] == "lying":
if inCrossBandY[ii]=="in":
itis[ii] = "bit"
ii = ii + 1
#
itisbitCnt = 0
for ii in range(3200):
if itis[ii] == "bit":
itisbitCnt = itisbitCnt + 1
# refresh testsuccess
if itisbitCnt == 8:
testsuccess = "ok"
print("in_crossBand test,do it ,ok")
#end the test :in_crossBand test ,
'''
if testsuccess=="fail":
print("find bit0-bit7 ,LF ,fail")
## success, goon ,bit x y location ,LF shape
if testsuccess == "ok":
print("getShape8b(),successs, find bit0-bit7 ,LF ")
mybitindex =0
ii = 0
for item in contours: # here item is one line of one BPH. maybe 11 12
myrect = cv2.minAreaRect(item)
mywidth = int(myrect[1][0]) # ?? width
myheight = int(myrect[1][1]) # heigth
myx = int(myrect[0][0]) # center x
myy = int(myrect[0][1]) # center y
# angle????myrect[2]
print("w h", mywidth, myheight, "cx cy", myx, myy)
heremin = min(mywidth, myheight)
heremax = max(mywidth, myheight)
# to get bit Value (prepare)
if itis[ii]=="bit":
print("get bit value ,bit loaction X y")
if mybitindex < 8:
if heremax >= bit_two_state_size_reference:
# 二态系统之大感觉 态
mybyteb_x[mybitindex][1] = 1
mybyteb_y[mybitindex][1] = 1
if heremax < bit_two_state_size_reference:
# 二态系统 之 弱小感觉 态
mybyteb_x[mybitindex][1] = 0
mybyteb_y[mybitindex][1] = 0
mybyteb_x[mybitindex][0] = myx
mybyteb_y[mybitindex][0] = myy
print("bit index", mybitindex, "，bit value", mybyteb_x[mybitindex][1])
print(" ")
mybitindex += 1
if itis[ii] == "LF":
print("test LF shape, LF state....")
##cv2.waitKey(0)
LFrect = cv2.minAreaRect(
item) # here item is one line of one BPH. (LF) #because LF is not well like square ,minAreaRect get the not correct angle LFrect[2]
# crop_minAreaRect( image ,LFrect,MYresizeRATE) ,mean :clear other _lines of one BPH.only LF appear!!!! image, black white total pic.
# crop_minAreaRect include 转角 clock_direct_operate_angle (rect[2] ) rotate!!
# LFsubImg,_ = crop_minAreaRect(image,LFrect,2)
LFsubImg= crop_minAreaRect(image, LFrect, 1) # LFsubImg as large as total pic if resizeRATE ==1,
cv2.imshow("LFsubImg ", LFsubImg) #s22
##cv2.waitKey(0)
LF_operate_angle = -LFrect[2] # LFrect[2] is nagtive
print("LF_operate_angle", LF_operate_angle)
if (LFsubImg is not None):
# after crop_minAreaRect rotate, get LFsubImg , is not correct enough!!! so go on adjust,refineRoi : max of max of sum vertical horizonal????????? ,adjust_angle, rotate it !
# now LFsubImg is equal_rect ???why,because after crop_minAreaRect ,u get it
LFsubImg_adjust, LF_adjust_angle_operated = refineRoi(
LFsubImg) # ????什么用？ rotate ,test 0 to 180 degree ,(because LF is not well like square ,minAreaRect get the not correct angle LFrect[2],,,so go on ,adjust LF angle!!!! very little ,near 0 degree or near 180
# now LFsubImg_adjust is smallest_rect ???why refineRoi -> getRoiImage() ->findContours
print(" LF_operate_angle in minAreaRect", LF_operate_angle)
print("LF_adjust_angle_operated in refineRoi ", LF_adjust_angle_operated)
print("BPH_angle_operated", BPH_angle_operated)
shapeType, shapeState = get_LF_Shape(LFsubImg_adjust,pen_width) # LFsubImg: LF line itself ,very small pic.!!!???
print("LF shapeType shapeState from getshape", shapeType, shapeState)
print("now get the real LFstate:")
if LF_adjust_angle_operated > 170: # near 180
if shapeState == "x_left": # mean b7 is at left
shapeState = "x_right"
elif shapeState == "x_right": # mean b7 is at right
shapeState = "x_left"
elif shapeState == "y_up": # mean b7 is at up
shapeState = "y_down"
elif shapeState == "y_down": # mean b7 is at down
shapeState = "y_up"
print("LF shapeType shapeState", shapeType, shapeState)
#cv2.waitKey(0)
if LF_operate_angle > 70: # near 90
if shapeState == "x_left": # mean b7 is at left
shapeState = "y_down"
elif shapeState == "x_right": # mean b7 is at right
shapeState = "y_up"
elif shapeState == "y_up": # mean b7 is at up
shapeState = "x_left"
elif shapeState == "y_down": # mean b7 is at down
shapeState = "x_right"
mem_LF_state = shapeState # it must before " if BPH_angle_operated ....exe"
print("LF shapeType shapeState", shapeType, shapeState)
print("mem LF shapeState", mem_LF_state)
# now LFstate is saying , with the BPH_rotated envirenment.
''' no use????
if BPH_angle_operated > 70: # near BPH_angle_operated is when BPH crop....
if shapeState == "x_left": # mean b7 is at left
shapeState = "y_down"
elif shapeState == "x_right": # mean b7 is at right
shapeState = "y_up"
elif shapeState == "y_up": # mean b7 is at up
shapeState = "x_left"
elif shapeState == "y_down": # mean b7 is at down
shapeState = "x_right"
print("LF shapeType shapeState", shapeType, shapeState)
'''
LFshapex_BPHcx = LFrect[0][0] - BPHcx
LFshapey_BPHcy = LFrect[0][1] - BPHcy
print('LFshape is: ', shapeType, 'LFshapex_BPHcx', LFshapex_BPHcx, 'LFshapey_BPHcy', LFshapey_BPHcy)
ii=ii+1
print("bbbprepera okokokokokkokokokokokokokokokok")
'''
'''
#排序：(after prepare ,go on)
#依据 x坐标 排序8个比特
# 坐标 是 BPH rotated 后的，哦!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!shapeState 是 BPH rotated 后的!!!!
print("now sort,////////shapeState=",shapeState, " mem_LF_state=", mem_LF_state)
mybyteb=[0]*8
temp= mem_LF_state #shapeState is not acurecy
if temp == "x_left": # mean b7 is at left
mybyteb_x.sort()
for bi in range(0, 8):
mybyteb[bi] = mybyteb_x[bi][1]
elif temp == "x_right": # mean b7 is at right
mybyteb_x.sort(reverse=True)
for bi in range(0, 8):
mybyteb[bi] = mybyteb_x[bi][1]
elif temp == "y_up": # mean b7 is at up
mybyteb_y.sort()
for bi in range(0, 8):
mybyteb[bi] = mybyteb_y[bi][1]
elif temp == "y_down": # mean b7 is at down
mybyteb_y.sort(reverse=True)
for bi in range(0, 8):
mybyteb[bi] = mybyteb_y[bi][1]
print("mybyteb after sort", mybyteb, " cx-bitV ",mybyteb_x," cy-bitV ", mybyteb_y)
#计算8个比特位的各个位代表值 之和，得到字节之值。
mybytev=0
# for ii in range(0, 8): 实际是 0 1 2 3 4 5 6 7 不带8不带最后一个 ，这个与vb不同。
for ii in range(0, 8):
if (mybyteb[ii]==1):
mybytev+=2**(7-ii)
print("mybytev:",mybytev)
#增256：是 两个突起，像F。
if (shapeType=='F'):
mybytev +=256
#若出错， 就用512表示
if mybitindex!=8:
mybytev=512
return mybytev
# for LF check, L or F ,getShape8b call this func
def get_LF_Shape(image,penWidth):#image is LFimage, #not as large as total pic if resizeRATE ==1,!!!!! but LF line itself ,very small pic.
#??? if H>W else:
H, W = image.shape # shape: height width channels
print("LF: H W",H,W)
#cv2.imshow("before half ", image)
#cv2.waitKey(0)
LFstate=""
LFvalue=""
'''
################
image22 = image[0:H//2, :] ##get upon part
#cv2.imshow("upon half ", image22)
#cv2.waitKey(0)
contours, hierarchy = cv2.findContours(image22, cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)
#contours, hierarchy = cv2.findContours(image22, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
num = len(contours)
################
image22 = image[H // 2:H, :] ##get down part
#cv2.imshow("down half ", image22)
#cv2.waitKey(0)
contours, hierarchy = cv2.findContours(image22, cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)
num2=len(contours)
#print("LF",num)
if(num==1)&(num2==1):
LFvalue= "L"
else:
LFvalue= "F"
####
'''
cv2.imshow("img///in getshape func now,after little adjust", image) # 29
##cv2.waitKey(0)
image22 = image[0:H // 2, 0:W//2] ##get up left part
cv2.imshow("LF part :up left", image22) #s30
##cv2.waitKey(0)
contours, hierarchy = cv2.findContours(image22, cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)
# contours, hierarchy = cv2.findContours(image22, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
num_up_left=0
print("up left???????????????????????????"+str(len(contours)))
for item in contours:# noise , very little noise , maybe 4 ||||| long part of "L" "F", handwrite, not too line_like , so thin part will into the Neighbourhood empty quarter zone.
(x, y, w, h) = cv2.boundingRect(item) ## 找出轮廓包围的矩形框
print((W,H) ,penWidth,w, h)
#if max(item.shape[0],item.shape[1]) > min(H,W)/3 and min( w, h)> penWidth/2 :
if max(w,h) > min(H, W) / 3 and min(w, h) > penWidth / 2:
num_up_left +=1
#num_up_left = len(contours)
image22 = image[H // 2:H, 0:W // 2] ##get down left part
cv2.imshow("LF part :down left", image22)
##cv2.waitKey(0)
contours, hierarchy = cv2.findContours(image22, cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)
# contours, hierarchy = cv2.findContours(image22, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
num_down_left = 0
print("down left???????????????????????????" + str(len(contours)))
for item in contours: # noise
(x, y, w, h) = cv2.boundingRect(item) ## 找出轮廓包围的矩形框
print((W,H), penWidth, w, h)
#if max(item.shape[0], item.shape[1]) > min(H, W) / 3 and min( w, h)> penWidth/2 :
if max(w, h) > min(H, W) / 3 and min(w, h) > penWidth / 2:
num_down_left += 1
#num_down_left = len(contours)
image22 = image[0:H // 2, W // 2:W] ##get up right part
cv2.imshow("LF part :up right", image22)
##cv2.waitKey(0)
contours, hierarchy = cv2.findContours(image22, cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)
# contours, hierarchy = cv2.findContours(image22, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
num_up_right = 0
print("up right???????????????????????????" + str(len(contours)))
for item in contours: # noise
(x, y, w, h) = cv2.boundingRect(item) ## 找出轮廓包围的矩形框
print((W,H), penWidth, w, h)
#if max(item.shape[0], item.shape[1]) > min(H, W) / 3 and min( w, h)> penWidth/2 :
if max(w, h) > min(H, W) / 3 and min(w, h) > penWidth / 2:
num_up_right += 1
#num_up_right = len(contours)
image22 = image[H // 2:H, W // 2:W] ##get down right part
cv2.imshow("LF part :down right", image22)
##cv2.waitKey(0)
contours, hierarchy = cv2.findContours(image22, cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)
# contours, hierarchy = cv2.findContours(image22, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
num_down_right = 0
print("down right???????????????????????????" + str(len(contours)))
for item in contours: # noise
(x, y, w, h) = cv2.boundingRect(item) ## 找出轮廓包围的矩形框
print((W,H), penWidth, w, h)
#if max(item.shape[0], item.shape[1]) > min(H, W) / 3 and min( w, h)> penWidth/2 :
if max(w, h) > min(H, W) / 3 and min(w, h) > penWidth / 2:
num_down_right += 1
#num_down_right = len(contours)
#print("ul dl ur dr", num_up_left,num_down_left, num_up_right,num_down_right ,)
#cv2.waitKey(0)
if H < W: #lying
if num_up_left+num_down_left>=2 :
LFstate = "x_left"
else:
LFstate = "x_right"
else: #standing
if num_up_left +num_up_right >= 2:
LFstate = "y_up"
else:
LFstate = "y_down"
#########
if H < W: # lying
if num_up_left + num_down_left == 2:
LFvalue = "L"
elif num_up_left + num_down_left > 2:
LFvalue = "F"
elif num_up_right + num_down_right == 2:
LFvalue = "L"
elif num_up_right + num_down_right > 2:
LFvalue = "F"
else: # standing
if num_up_left + num_up_right == 2:
LFvalue = "L"
elif num_up_left + num_up_right > 2:
LFvalue = "F"
if num_down_left + num_down_right == 2:
LFvalue = "L"
elif num_down_left + num_down_right > 2:
LFvalue = "F"
#########
print("LFvalue, LFstate: ", LFvalue, LFstate )
print("num_up_left, num_up_right ",num_up_left, num_up_right)
print("num_down_left, num_down_right", num_down_left ,num_down_right)
#cv2.waitKey(0)
return LFvalue, LFstate
# here imagBW is total pic , rect is for one BPH(or LF)(rect:center_x center_y w h angle), if resizeRATE==1: return is as large as total pic (imageBW) , without other BPH only this BPH appear.!!!!
# include 转角 clock_direct_operate_angle (rect[2] ) rotate!!
def crop_minAreaRect(imageBW, rect,resizeRATE):
#resizeRATE 用 2 ，3 ，4 ， 5,6， 7， 8..越大越慢
box = cv2.boxPoints(rect)
box = np.int0(box)
retW,retH=rect[1] #???????H ,w
H,W=imageBW.shape
rectCenter = rect[0]
angle = rect[2]#??-90 -80 -10...
print("mask")
mask=np.zeros(imageBW.shape,np.uint8) # new, fill with 0
cv2.drawContours(mask,[box],-1,255,cv2.FILLED)
ROI = cv2.bitwise_and(imageBW,mask) # and operate
print("mask ok")
#下面 转角angle (rect[2] ) ，可能，目的， 出图是：图案顺时针 转 rect[2]成 0度的样子?? angle大约等于 -45，-90 ，0
M = cv2.getRotationMatrix2D(rectCenter, angle, 1.0)
#截图，减少计算，提速
#hy0= int(rect[0][1]-max(rect[1][0],rect[1][1])/2)-1
#if hy0<0:
# hy0=0
#hy1= int(rect[0][1]+max(rect[1][0],rect[1][1])/2)+1
#
#hx0= int(rect[0][0]-max(rect[1][0],rect[1][1])/2)-1
#if hx0<0:
# hx0=0
#hx1 = int(rect[0][0] + max(rect[1][0],rect[1][1])/2)+1
#cv2.imshow("BWzzzz" + str(hy0) + str(hy1) + str(hx0) + str(hx1), imageBW)
#cv2.waitKey(0)
#rect[1][0], rect[1][1] H,W////// rect[0][0], rect[0][1] center, x y same as (left top)///// rect[2] angle - singal
thta=-rect[2]/360*2*math.pi
outsideW=(rect[1][1])*math.cos(thta)+(rect[1][0])*math.sin(thta)
outsideH=(rect[1][1]) * math.sin(thta) + (rect[1][0]) * math.cos(thta)
outsideRadius=int((outsideW*outsideW+ outsideH* outsideH)**0.5 /2) # square
"""
hy0 = int(rect[0][1] - outsideH / 2) - 1
if hy0 < 0:
hy0 = 0
hy1= int(rect[0][1] + outsideH / 2) +1
hx0 = int(rect[0][0] - outsideW / 2) - 1
if hx0 < 0:
hx0 = 0
hx1 = int(rect[0][0] + outsideW / 2) + 1
"""
hy0 = int(rect[0][1] - outsideRadius) - 1
if hy0 < 0:
hy0 = 0
hy1 = int(rect[0][1] + outsideRadius) + 1
hx0 = int(rect[0][0] - outsideRadius) - 1
if hx0 < 0:
hx0 = 0
hx1 = int(rect[0][0] + outsideRadius) + 1
#cv2.imshow("BWaaa"+str(math.cos(60))+ "W H:"+str(outsideW)+" "+str(outsideH),imageBW)
#cv2.waitKey(0)
#cv2.imshow("BWabbbb" + str(hy0)+" " + str(hy1) +" "+ str(hx0)+" " + str(hx1), imageBW)
#cv2.waitKey(0)
#lossless rotate enbalbe
cropped = ROI[hy0:hy1, hx0:hx1] # 裁剪坐标为[y0:y1, x0:x1] #ROI（region of interest）——感兴趣区域。
#cv2.imshow("cropped" , cropped)
#cv2.waitKey(0)
#
#ret = cv2.warpAffine(ROI, M, (H*resizeRATE,W * resizeRATE)) #这个太慢， 计算的任务太多，没必要,但是它是无损的？计算取整损耗？
#HH=max(rect[1][0],rect[1][1])
#WW=HH
#M = cv2.getRotationMatrix2D((HH/2,WW/2), angle, 1.0)
#ret = cv2.warpAffine(cropped, M, (H * resizeRATE, W * resizeRATE))#这个快，
#return ret,0 #add90happened
# ret = cv2.warpAffine(ROI, M, (H*resizeRATE,W * resizeRATE)) #这个太慢， 计算的任务太多，没必要,但是它是无损的？计算取整损耗？
HH=outsideRadius*2
WW=HH
M = cv2.getRotationMatrix2D((outsideRadius,outsideRadius), angle, 1.0)
ret = cv2.warpAffine(cropped, M,(HH,WW))## (HH * resizeRATE, WW * resizeRATE))#这个快， resizeRATE?????? useless
#cv2.imshow("ret"+str(resizeRATE), ret)
#cv2.waitKey(0)
return ret
def main(resizecode,imageRGB,showDialog):
print( "opencv version ",cv2.__version__)
#imageRGB = cv2.imread('test.jpg')
#root = tkinter.Tk()
#root.withdraw() # 隐藏
#root.update() # 隐藏
#对话框，可能 不太支持 汉字。
#picfilename=tkinter.filedialog.askopenfilename(defaultextension = '.jpg',filetypes = [('all files', '.*'), ('jpg files', '.jpg')],initialdir= os.getcwd(),initialfile = 'test.jpg')
#####picfilename = tkinter.filedialog.askopenfilename( initialdir=os.getcwd())
#####imageRGB = cv2.imread( picfilename)
# 放大
if resizecode!="normal":
size = imageRGB.shape
h, w = size[0], size[1]
if h*w>1000000: #############???????????????????????????????????????????????????????????????????
scale =0.25#0.5# 2#3
else:
scale=2
new_w, new_h = int(w * scale), int(h * scale)
imageRGB = cv2.resize(imageRGB, (new_w, new_h),interpolation=cv2.INTER_CUBIC)
print("resize happened")
#放大结束，没起作用？ 起作用了。
#图片尺寸
sp=imageRGB.shape
print("imagesize",sp[1],"*",sp[0])
mypicH=sp[0]
mypicW=sp[1]
kernel = cv2.getStructuringElement(cv2.MORPH_RECT, (3, 3))
# 腐蚀图像
erodeded =cv2.erode(imageRGB, kernel)
# eroded = cv2.erode(erodeded, kernel)
# 显示腐蚀后的图像
##cv2.imshow("Eroded Image", erodeded);
# 膨胀图像 腐蚀图像
################### # dilated = cv2.dilate(imageRGB, kernel)
# 显示膨胀后的图像
# cv2.imshow("Dilated Image", dilated);
# 原图像
# cv2.imshow("Origin", imageRGB) #s02
#cv2.waitKey(0)
image = cv2.cvtColor(erodeded, cv2.COLOR_BGR2GRAY)
#image = cv2.cvtColor(dilated, cv2.COLOR_BGR2GRAY)
# image = cv2.cvtColor(imageRGB,cv2.COLOR_BGR2GRAY)
image = 255-image
# 图像
cv2.imshow("255-single", image) #s03
# cv2.waitKey(0)
#(100,255 软件 出图 ，笔画色彩 淡薄 ，可 试 这个，；但是 对于 软件出图 然后拍照 屏幕，却 什么 都 识别 不出。)
# (软件出图)70,255 （软件出图 然后 拍照屏幕 ,160 255；但是 软件 出图 的 色彩 淡薄的，却容易 不识别 。)
_, BW = cv2.threshold(image, 160, 255, cv2.THRESH_BINARY )
#_,BW = cv2.threshold(image,160,255,cv2.THRESH_BINARY | cv2.THRESH_OTSU)
#_, BW = cv2.threshold(image, 160, 255, cv2.THRESH_OTSU)
#BW=FillHole(BW22)
#cv2.imshow("BW", BW)
#cv2.waitKey(100)
#素描图：
imgG = cv2.GaussianBlur(image, (3, 3), 0)
dst = cv2.Canny(imgG, 180, 180) # 图片卷积——》th
#BW=dst
#素描之二
#imgInfo = image.shape
#height = imgInfo[0]
#width = imgInfo[1]
# sobel 1 算子模版 2 图片卷积 3 阈值判决
# [1 2 1 [ 1 0 -1
# 0 0 0 2 0 -2
# -1 -2 -1 ] 1 0 -1 ]
# [1 2 3 4] [a b c d] a*1+b*2+c*3+d*4 = dst
#dst = np.zeros((height, width, 1), np.uint8)#创建
#gray=image
#print("okokokokok")
#for i in range(0, height - 2):
# for j in range(0, width - 2):
# gy = gray[i, j] * 1 + gray[i, j + 1] * 2 + gray[i, j + 2] * 1 - gray[i + 2, j] * 1 - gray[
# i + 2, j + 1] * 2 - gray[i + 2, j + 2] * 1
# gx = gray[i, j] + gray[i + 1, j] * 2 + gray[i + 2, j] - gray[i, j + 2] - gray[i + 1, j + 2] * 2 - gray[
# i + 2, j + 2]
# grad = math.sqrt(gx * gx + gy * gy)
# if grad > 100:
# dst[i, j] = 0
# else:
# dst[i, j] = 255
#BW=dst
#print("ok12121212")
#防止 照片太像条幅，导致画面右侧 轮廓检测 丢失 （不知为什么 ， cv2.findContours ）
if mypicW/mypicH>2: #画面 增高
img1=Image.fromarray(BW)
# 创建一个新的图片对象
newmypicH=int(mypicW/2)
img2 = Image.new('RGB', (mypicW, newmypicH), (0, 0, 0))
# 圈出需要复制的图片框(这里其实是复制img整个图片)
box1 = (0, 0, mypicW, mypicH)
# 按圈出的框复制图片
region = img1.crop(box1)
img2.paste(region, (0, 0))
BW2= np.array(img2)
BW = cv2.cvtColor(BW2, cv2.COLOR_BGR2GRAY)
cv2.imshow("BW,height enlarge ,",BW)
cv2.waitKey(100)
mypicH = newmypicH
else:
cv2.imshow("BW", BW) #s05
cv2.waitKey(100)
#BPH检测开始
#contours, hierarchy = cv2.findContours(BW,cv2.RETR_TREE,cv2.CHAIN_APPROX_SIMPLE)
contours, hierarchy = cv2.findContours(BW,cv2.RETR_EXTERNAL,cv2.CHAIN_APPROX_SIMPLE) #here:contours is all BPH s.
number=0
success_bph=0
print("total bph may be:",len(contours))
bhp_height=0
mycache_x_y_v_LF= [([0] * 4) for i in range(len(contours))]
mycache_BPHheight= [([0]) for i in range(len(contours))]
linestartmem=[0]*len(contours)
nextlinestartmem=[0]*len(contours)
for item in contours: #here:contours is all BPH s.
#最小外接矩形 cv2.minAreaRect
rect = cv2.minAreaRect(item) #here rect is for one BPH , width (rect[1][0]), height=int(rect[1][1]),angle rect[2],,, center_x ,rect[0][0], center_y rect[0][1],
#box = cv2.boxPoints(rect)
#box = np.int0(box)
width=int(rect[1][0])
height=int(rect[1][1])
#bph_height=height#不准 可能 某行 用小BPH , 某行 用大BPH , 所以 ，下面 做 更多判断。
cx=int(rect[0][0]) #BPHcx BPH centrel x
cy=int(rect[0][1]) #BPHcy BPH centrel y
#?????? 过滤 ，10似乎 太小 ，用 30.
if(min(width,height)>30 and rect[1][0]<mypicH and rect[1][1]<mypicH):
number+=1
#cv2.drawContours(imageRGB,[box],-1,(0,0,255))
#boundingRect=cv2.boundingRect(item)
print('this BPH angle ============================================================== ',rect[2])
print("this BPH xywha",rect[0][0],rect[0][1],rect[1][0],rect[1][1],rect[2])
bwh,bww=BW.shape
print("before call getshape8b,the total pic :BW",bww,bwh)
print("before call getshape8b,this one BPH,the minAreaRect whxy", width,height,cx,cy)
if min(width,height)<100 :#太小的BPH，要多放大。VB画的 大约是68宽度的,
MYresizeRATE=3
#elif min(width,height)>200:
# MYresizeRATE = 6
else:
MYresizeRATE=2
if min(width, height) > 1000: #太大的BPH,不要放大了
MYresizeRATE = 1
# crop_minAreaRect(BW,rect,MYresizeRATE) ,mean :clear other BPH.!!!! BW, black white total pic.
# crop_minAreaRect include 转角 clock_direct_operate_angle (rect[2] or rect[2]+90) rotate!! if minArea_rect retW<retH: +90 happened
subImg= crop_minAreaRect(BW,rect,MYresizeRATE) #here rect is for one BPH, here subImg is as large as total pic without other BPH, only this BPH appear.!!!!
bwh2, bww2 = subImg.shape
print("before call getshape8b,the cleared_sub pic without other BPH , as large as total pic :subimg w h", bww2, bwh2)
if(subImg is not None): #rect[2] is -signal
shapetype8b = getShape8b(subImg,-rect[2],cx,cy ,width,height) #here rect is for one BPH, here subImg is as large as total pic without other BPH, only this BPH appear.!!!!
if(shapetype8b<256): #find BPH with L
mycache_x_y_v_LF[success_bph][0] =cx
mycache_x_y_v_LF[success_bph][1] = cy
mycache_x_y_v_LF[success_bph][2] = shapetype8b
mycache_x_y_v_LF[success_bph][3]=1
mycache_BPHheight[success_bph]=height #判断是BPH ,赋值bph_height， 这样比较准，（还 存在 问题， 若 多个 BPH不 一样高，怎么办？？？）?????????????????????????????
success_bph+=1
print("success to get a BPH,sum=",success_bph)
if ((shapetype8b >= 256)and (shapetype8b <512)): #find BPH with F
mycache_x_y_v_LF[success_bph][0] = cx
mycache_x_y_v_LF[success_bph][1] = cy
mycache_x_y_v_LF[success_bph][2] = shapetype8b-256
mycache_x_y_v_LF[success_bph][3] = 2
mycache_BPHheight[success_bph] = height # 判断是BPH ,赋值bph_height， 这样比较准，（还 存在 问题， 若 多个 BPH不 一样高，怎么办？？？）???????????????????????????????
success_bph += 1
print("success to get a BPH,sum=", success_bph)
if (shapetype8b == 512):
print("fail to get a BPH")
print(" ")
print(" ")
# break
print("test: ",number," BPH sum=",success_bph)
print(" mycache_x_y_v_LF", mycache_x_y_v_LF)
#sort
mycache_v = [0] * (success_bph)
mycache_LF = [0] * (success_bph)
print("")
print("my sort:")
mycache_iii= [0]* (success_bph)
mycache_iiiiii= [0] * (success_bph)
tempx=0
memiii=0
tempy=0
hereindex = 0
heremax_y=0
#暂时 用第一个y乘以2 ，够大了，。
heremin_y= mycache_x_y_v_LF[0][1]*2
tempy=heremin_y
#得 整体 最小y
for iii in range(0, (success_bph)):
if tempy> mycache_x_y_v_LF[iii][1]:
tempy=mycache_x_y_v_LF[iii][1]
memiii=iii
bph_height=mycache_BPHheight[memiii]
print("min y i have got,memiii tempy ",memiii ,tempy )
print(" ")
heremin_y=tempy
memdelta2 =heremin_y
linestart=0
nextlinestart=0
lines=0
hereindex=0
while hereindex<success_bph:
#这个y 接近的 各个点 ，组成 一行line， 保存，也得到nextlinestart
for iii in range(0, (success_bph)):
#print("iii",iii)
delta=mycache_x_y_v_LF[iii][1]-tempy
if delta<(bph_height/2) and delta>=0:
#print("iii-hereindex",hereindex)
mycache_iiiiii[hereindex] = iii
hereindex+=1
print(iii)
print("okok",bph_height/2)
nextlinestart= hereindex
linestartmem[lines]=linestart
nextlinestartmem[lines]=nextlinestart
#line ,x 排序
print ("linestart, nextlinestart",linestart,nextlinestart)
for jjj in range(linestart, nextlinestart):
#print(jjj,"jjj")
for jj in range(linestart, nextlinestart-1):
#print("jj",jj)
if mycache_x_y_v_LF[mycache_iiiiii[jj]][0] >mycache_x_y_v_LF[mycache_iiiiii[jj+1]][0]:
hi=mycache_iiiiii[jj]
mycache_iiiiii[jj]=mycache_iiiiii[jj+1]
mycache_iiiiii[jj+1]=hi
for jjj in range(linestart, nextlinestart ):
print("x=", mycache_x_y_v_LF[mycache_iiiiii[jjj]][0],"y=", mycache_x_y_v_LF[mycache_iiiiii[jjj]][1], "v=",mycache_x_y_v_LF[mycache_iiiiii[jjj]][2],"line=",lines)
linestart = nextlinestart
lines += 1
memy=tempy
memdelta2=10000 #heremax_y
#得 剩余之 最小 y,赋值给tempy
for iii in range(0, (success_bph)):
delta2= mycache_x_y_v_LF[ iii][1]-memy
#print("mdelta2",memdelta2,"bph h",bph_height)
if delta2>(bph_height/2):
if delta2<memdelta2:
memdelta2=delta2
memiii=iii
tempy = mycache_x_y_v_LF[ iii][1]
bhp_height = mycache_BPHheight[memiii]
print("memiii tempy(min y for this time) ", memiii, tempy)
# redo,get mycache_v mycache_LF ,again
for ij in range(0, (success_bph)):
mycache_v[ij]= mycache_x_y_v_LF[mycache_iiiiii[ij]][2]
mycache_LF[ij]=mycache_x_y_v_LF[mycache_iiiiii[ij]][3]
#测试打印
print(" ")
print("bph count:",success_bph ,",lines count:",lines)
print("after sort，mycache_v", mycache_v, "mycache_LF", mycache_LF)
## for return !!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!
myba_hex_str=""
myLF_hex_str=""
l = [hex(int(i)) for i in mycache_v]
myba_hex_str=" ".join(l)
ll=[hex(int(i)) for i in mycache_LF]
myLF_hex_str = " ".join(ll)
print( "mycache_v HEX:," ," ".join(l))
print("mycache_LF HEX:,", " ".join(ll))
#`o substitute :
substitutestring=bytearray([0x30]*(success_bph*2))
someb=b'0'
someb2=b'0'
someb3=b'0'
for ijk in range(0,success_bph):
someb= mycache_v[ijk]
someb2=(someb & 15)
someb2=someb2 |96
someb3=(someb>>4)
someb3 = someb3 | 96
substitutestring[ijk*2] =someb3
substitutestring[ijk * 2+1] = someb2
print(" `o_substitutestring:",substitutestring.decode())
print("show string ##############################################")
str1 = ['0'] * (success_bph)
for ii in range(0, success_bph):
str1[ii] = chr(mycache_v[ii])
str11 = ''.join('%s' % id for id in str1)
print(str11)
#
print("show bytearray ##############################################")
myba=bytearray([0x30]*success_bph)
myba=bytearray(mycache_v)
print("myba",myba)
# draw, mark mark mark mark mark mark mark mark mark mark mark mark mark mark mark mark mark mark
location_str=""
for iii in range(0, (success_bph)):
drawx = mycache_x_y_v_LF[iii][0]
drawy = mycache_x_y_v_LF[iii][1]
##for return !!!!!!!!!!!!!!!!!!!!!!!!
location_str+=int_to_str(drawx)+" "+int_to_str(drawy)+";"
htstr=hex(mycache_x_y_v_LF[iii][2]) # 类似 0xEF 的 样子 ，0xf 0xf0 0x0 0xff，
if len(htstr)==3:
htstr='0'+htstr[2:3]
htstr=htstr.upper()
else:
htstr = htstr[2:4].upper()
drawstr=htstr
# 起点和终点的坐标
ptStart = (drawx, drawy)
ptEnd = (drawx + 10, drawy + 10)
point_color = (0, 255, 0) # BGR
thickness = 1
lineType = 4
# cv2.line(imageRGB, ptStart, ptEnd, point_color, thickness, lineType)
# 十六进制串 在图片添加文字，参数为，图片，绘制文字，位置，字体类型，字体大小，颜色，线条类型
font = cv2.FONT_HERSHEY_SIMPLEX
cv2.putText(imageRGB, drawstr, (drawx, drawy), font, 1, (0, 0, 127), 1)
if mycache_x_y_v_LF[iii][3]==2:
cv2.putText(imageRGB, drawstr, (drawx+5, drawy+5), font, 1, (0, 0, 127), 1)
# char ascii
hb = bytearray([0] * 1)
hb[0] = mycache_x_y_v_LF[iii][2]
drawchr_ascii = hb.decode("ASCII", 'ignore')
cv2.putText(imageRGB, drawchr_ascii, (drawx, drawy + 20), font, 1, (0, 127, 0), 1)
#cv2.imshow("original,HEX chr pair,ASCII chr, "+picfilename, imageRGB)
cv2.imshow("original,HEX chr pair,ASCII chr, " , imageRGB)
#markedImg=imageRGB
print("show all string ##############################################")
print("as ASCII charcode,print:") # 'gb2312' 'gbk' 'utf-8' 'utf-16'
myba2str = myba.decode("ASCII", 'replace')#'ignore')
print(myba2str)
print(" ")
print("as utf_8 charcode,print:")
#for return!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!
suppose_str_utf_8=""
myba2str=myba.decode("UTF-8",'replace')#'ignore')
suppose_str_utf_8= myba2str
print(myba2str)
print(" ")
#tkinter.messagebox.showinfo(str(success_bph)+',as utf-8,', myba2str)
print("as GBK charcode,print:") # 'gb2312' 'gbk' 'utf-8' 'utf-16'
myba2str = myba.decode('GBK','replace')#'ignore')
print(myba2str)
print(" ")
#tkinter.messagebox.showinfo('提示,as GBK,', myba2str)
print("as unicode LE charcode,print:") # 'gb2312' 'gbk' 'utf-8' 'utf-16'
myba2str = myba.decode('utf_16_le', 'replace')#'ignore') # 'ignore' 'strict' 'replace' 'xmlcharrefreplace'
print(myba2str)
print(" ")
print("as unicode BE charcode,print:") # 'gb2312' 'gbk' 'utf-8' 'utf-16'
myba2str = myba.decode('utf_16_be','replace')# 'ignore') # 'ignore' 'strict' 'replace' 'xmlcharrefreplace'
print(myba2str)
print("show in lines @@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@ ")
linestr=['0123']*lines
for kk in range(0, lines):
str1 = ['0'] * (nextlinestartmem[kk] - linestartmem[kk])
myba2 = bytearray([0x30] * (nextlinestartmem[kk] - linestartmem[kk]))
tempindex = 0
for ii in range(linestartmem[kk], nextlinestartmem[kk]):
myba2[tempindex] = mycache_v[ii]
tempindex += 1
# myba.append(mycache_v[ii])
linestr[kk] = myba2.decode("ASCII", 'ignore')
print("linestr as ASCII ", linestr[kk])
for kk in range(0, lines):
myba2 = bytearray([0x30] * (nextlinestartmem[kk] - linestartmem[kk]))
tempindex = 0
for ii in range(linestartmem[kk], nextlinestartmem[kk]):
myba2[tempindex] = mycache_v[ii]
tempindex += 1
linestr[kk] = myba2.decode("GBK", 'replace')#'strict')#'ignore')
print("linestr as GBK ", linestr[kk])
hstr = ''
for kk in range(0, lines):
hstr = hstr + linestr[kk] + '''\n'''
if showDialog=="dialog":
tkinter.messagebox.showinfo(str(success_bph) + ',as GBK,', hstr)
for kk in range(0, lines):
myba2 = bytearray([0x30] * (nextlinestartmem[kk] - linestartmem[kk]))
tempindex = 0
for ii in range(linestartmem[kk], nextlinestartmem[kk]):
myba2[tempindex] = mycache_v[ii]
tempindex += 1
linestr[kk] = myba2.decode("UTF_8", 'replace')#'strict')#'ignore')
print("linestr as UTF_8 ", linestr[kk])
hstr=''
for kk in range(0, lines):
hstr=hstr+linestr[kk]+'''\n'''
if showDialog == "dialog":
tkinter.messagebox.showinfo(str(success_bph) + ',as utf-8,', hstr)
for kk in range(0, lines):
myba2 = bytearray([0x30] * (nextlinestartmem[kk] - linestartmem[kk]))
tempindex = 0
for ii in range(linestartmem[kk], nextlinestartmem[kk]):
myba2[tempindex] = mycache_v[ii]
tempindex += 1
linestr[kk] = myba2.decode("UTF_16_LE", 'replace')# 'ignore')
print("linestr as UTF_16_LE ", linestr[kk])
for kk in range(0, lines):
myba2 = bytearray([0x30] * (nextlinestartmem[kk] - linestartmem[kk]))
tempindex = 0
for ii in range(linestartmem[kk], nextlinestartmem[kk]):
myba2[tempindex] = mycache_v[ii]
tempindex += 1
linestr[kk] = myba2.decode("UTF_16_BE", 'replace')#'ignore')
print("linestr as UTF_16_BE", linestr[kk])
print(resizecode+" ok!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!")
myall = str(success_bph)+"|"+"imagesize_w_h "+str(sp[1])+" "+str(sp[0])+"|"+location_str+"|" +myba_hex_str+"|"+myLF_hex_str+"|"+suppose_str_utf_8
print(myall)
print(" ")
print(" ")
print(" ")
# root=tkinter.Tk()
#root.withdraw()#隐藏
#root.update()#隐藏
#root.visible=0
#txt=tkinter.messagebox.askyesno(success_bph,"ok?")
#root.destroy()
#cv2.waitKey(55000)
#cv2.destroyAllWindows() #s39
print("all pictures clear , !!!!!!!!!!!!!!!!!!!!!!!!!!!!!, u can input # upon line , so not clear ,u can see detail! search #s39 ,...")
return success_bph,"imagesize_w_h "+str(sp[1])+" "+str(sp[0]),location_str, myba_hex_str,myLF_hex_str,suppose_str_utf_8,imageRGB#markedImg
# socket
if __name__ == "__main__":
###################### capture
cap = cv2.VideoCapture(0,cv2.CAP_DSHOW) #if not 0 ,you can try 700
print("capture初始化成功！")
#savedpath = r'd:\\py\\'
savedpath = os.getcwd()+'\\'
print(savedpath )
isExists = os.path.exists(savedpath)
if not isExists:
os.makedirs(savedpath)
print('path of %s is build' % (savedpath))
else:
print('path of %s already exist and rebuild' % (savedpath))
ret, frame = cap.read()
cameraFound=True
shoot = True
if ret==False:
shoot=False
cameraFound =False
print("camera 0 or 700 not found")
herecnt=1000#30 10 # delay 10 seconds,to form video, then , snap pic
cv2.namedWindow("Image")
while (shoot):
ret, frame = cap.read() #拍照
cv2.waitKey(200) #延时200毫秒
# Python监听鼠标键盘事件 https://www.cnblogs.com/cmm2016/p/6775409.html
# ord 得到整数
#print(cv2.waitKey(100))
if cv2.waitKey(100)&0xFF==0x0D: # (Key.esc): # ==ord('s'): # 'F1': 0x70 ???? , #'left_arrow': 0x25 ???, # 'page_up': 0x21 ????, #'enter': 0x0D OKOKOK,# 'tab': 0x09 OKOKOK, #'home': 0x24???, 'spacebar': 0x20 OKOKOK,
sys.exit() #退出程序
if cv2.waitKey(100)&0xFF==ord('\x1b'): #(Key.esc): #('s'):
shoot = False
herecnt=herecnt-1
if herecnt==0:
shoot=False
if shoot==True:
font = cv2.FONT_HERSHEY_SIMPLEX
cv2.putText(frame, str(herecnt) + "press keyboard Esc to snap, ", (10, 60), font, 1, (0, 0, 127), 1)
cv2.putText(frame, "select file OK for BPHor", (10, 100), font, 1, (0, 0, 127), 1)
cv2.putText(frame, "select file cancel for snap again", (10, 160), font, 1, (0, 0, 127), 1)
cv2.imshow(" press Esc , snap, filename is camera_snap.jpg press Enter to exit", frame)
savedname = 'camera_snap' + '.jpg' #默认文件名
if cameraFound ==True:
cv2.imwrite(savedpath + savedname, frame) #存盘
cap.release()
cv2.destroyAllWindows()
############ end capture
#############################
#socket
##def socket_service():
#################### # end socket
BPHlast=1111
mylocation_str=""
while 1==1:
root = tkinter.Tk()
root.withdraw() # 隐藏 hide that little blank dialog
root.update() # 隐藏
# 对话框，可能 不太支持 汉字。
picfilename = tkinter.filedialog.askopenfilename(initialdir=os.getcwd()) #选文件名
if cameraFound==False and picfilename=="": #摄像头 未用， 对话选文件名 是 空， 就退出程序。
sys.exit() # 退出程序
while picfilename=="":
###################### capture
cap = cv2.VideoCapture(0, cv2.CAP_DSHOW) # if not 0 ,you can try 700
print("capture初始化成功！")
# savedpath = r'd:\\py\\'
savedpath = os.getcwd() + '\\'
print(savedpath)
isExists = os.path.exists(savedpath)
if not isExists:
os.makedirs(savedpath)
print('path of %s is build' % (savedpath))
else:
print('path of %s already exist and rebuild' % (savedpath))
ret, frame = cap.read()
cameraFound = True
shoot = True
if ret == False:
shoot = False
cameraFound =False
print("camera 0 or 700 not found")
herecnt = 100 # 30 # delay 10 seconds,to form video, then , snap pic
cv2.namedWindow("Image")
while (shoot):
ret, frame = cap.read()
cv2.waitKey(200)
if cv2.waitKey( 100) & 0xFF == 0x0D: # (Key.esc): # ==ord('s'): # 'F1': 0x70 ???? , #'left_arrow': 0x25 ???, # 'page_up': 0x21 ????, #'enter': 0x0D OKOKOK,# 'tab': 0x09 OKOKOK, #'home': 0x24???, 'spacebar': 0x20 OKOKOK,
sys.exit() #退出程序
if cv2.waitKey(100) & 0xFF == ord('\x1b'):#('s'):
shoot = False
herecnt = herecnt - 1
if herecnt == 0:
shoot = False
if shoot == True:
font = cv2.FONT_HERSHEY_SIMPLEX
cv2.putText(frame, str(herecnt) + " press keyboard Esc to snap ", (60, 60), font, 1, (0, 0, 127), 1)
cv2.putText(frame, "select file , OK for BPHor", (10, 100), font, 1, (0, 0, 127), 1)
cv2.putText(frame, "select file , cancel for snap again", (10, 160), font, 1, (0, 0, 127), 1)
# 编码转换不起作用啊 ？？？由于在OpenCV-Python包中，imshow函数的窗口标题是gbk编码，而Python3默认UTF-8编码。因而窗口标题包含中文时，会显示乱码。 要 转换 啊 ！！！.encode("gbk").decode(errors="ignore")
cv2.imshow("now ,press Esc , snap, filename is camera_snap.jpg press Enter to exit", frame) # 按 Esc键 拍照， 然后： 若 选文件 ok，识别之；若 不选文件Cancel,继续拍照
savedname = 'camera_snap' + '.jpg' #默认文件名 # 'example' + '.jpg'
if cameraFound == True:
cv2.imwrite(savedpath + savedname, frame)
cap.release()
cv2.destroyAllWindows()
############ end capture
root = tkinter.Tk()
root.withdraw() # 隐藏
root.update() # 隐藏
# 对话框，可能 不太支持 汉字。
picfilename = tkinter.filedialog.askopenfilename(initialdir=os.getcwd())
cv2.destroyAllWindows()
imageRGB = cv2.imread(picfilename) #读图片文件
BPHlast,size_w_h,mylocation_str ,x_return,y_return,str_return,markedImg= main("normal", imageRGB,"nodialog")
cv2.imshow('markedImg'+y_return+str_return, markedImg)
##cv2.waitKey(0)
print("")
print("size_W_H",size_w_h)
print("location_str",mylocation_str)
print("x_return",x_return)
print("y_return",y_return)
print("str_return",str_return)
if BPHlast<1:# <=1 BPH检测得 太少， 增一次 放大后检测。
imageRGB = cv2.imread(picfilename)
BPHlast,size_w_h,mylocation_str,x_return,y_return,str_return,markedImg=main("resize_again",imageRGB,"nodialog")
cv2.imshow('markedImg resize again '+y_return+str_return, markedImg)
##cv2.waitKey(0)
messagebox.showinfo("提示", "LF="+y_return+"\n"+"HEX:"+x_return+"\n"+str_return)
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