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from PIL import Image
from functools import partial
import sys
import numpy as np
import cv2
from pylab import plot,show
from numpy import vstack,array
from numpy.random import rand
from scipy.cluster.vq import kmeans,vq
from pywinauto.application import Application
import win32api, win32con
import sys
import time
import os
#import pyscreenshot as ImageGrab
PY3 = sys.version_info[0] == 3
if PY3:
xrange = range
def mse(imageA, imageB):
err = np.sum((imageA.astype("float") - imageB.astype("float")) ** 2)
err /= float(imageA.shape[0] * imageA.shape[1])
return err
def click(x,y):
win32api.SetCursorPos((x,y))
win32api.mouse_event(win32con.MOUSEEVENTF_LEFTDOWN,x,y,0,0)
win32api.mouse_event(win32con.MOUSEEVENTF_LEFTUP,x,y,0,0)
im = cv2.imread(r'C:\Users\martlee2\Documents\roster2.png')
gray = cv2.cvtColor(im,cv2.COLOR_BGR2GRAY)
gray = np.float32(gray)
#dst = cv2.cornerHarris(gray,2,3,0.04)
dst = cv2.cornerHarris(gray,14,5,0.04)
dst = cv2.dilate(dst,None)
#im[dst>0.01*dst.max()]=[0,0,255]
dd = dst>0.01*dst.max()
#out = np.zeros(im.shape,np.uint8)
#gray = cv2.cvtColor(im,cv2.COLOR_BGR2GRAY)
#thresh = cv2.adaptiveThreshold(gray,255,1,1,11,2)
m5 = cv2.imread(r'C:\Users\martlee2\Documents\roster2.png')
im = cv2.imread(r'C:\Users\martlee2\Documents\roster2.png')
#im3 = im.copy()
ma = Image.open("roster2.png")
color1 = ma.load()
print ma.size
print color1[1,1]
color1 = ma.load()
print ma.size
print color1[1,1]
colortolocation = {}
def addtogroupkey(keyandmemory, key1, memorycontent):
k = key1
if k in keyandmemory:
keyandmemory[k].append(memorycontent)
else:
keyandmemory[k] = [memorycontent]
return keyandmemory
#for ii in range(0, ma.size[0]):
# for jj in range(0, ma.size[1]):
#if color1[ii,jj][0] <= 102 and color1[ii,jj][2] <= 57 and color1[ii,jj][2] > 0 and color1[ii,jj][0] > 0:
#colortolocation = addtogroupkey(colortolocation, (0,0,0), (ii,jj))
def isneighborlocation(lo1, lo2):
if abs(lo1[0] - lo2[0]) <= 70 and abs(lo1[1] - lo2[1]) <= 12:
return 1
elif abs(lo1[0] - lo2[0]) == 1 and lo1[1] == lo2[1]:
return 1
elif abs(lo1[1] - lo2[1]) == 1 and lo1[0] == lo2[0]:
return 1
else:
return 0
eachcolor = (0,0,0)
#max_key = sorted(colortolocation, key=lambda k: len(colortolocation[k]), reverse=True)[:12]
#del max_key[0]
#for eachcolor in max_key:
# print eachcolor
#for eachcolor in colortolocation:
#if 1 == 1:
#for eachcolor in max_key:
eachcolor = (0,0,0)
if 1 == 1:
#testing1 = list(colortolocation[eachcolor])
#testing1.sort(key=lambda x: (x[0], x[1]))
#locations = testing1
#testing1 = [list((float(elem[0]),float(elem[1]))) for elem in testing1]
testing1 = zip(*np.where(dd == 1))
locations = testing1
testing1 = [list((float(elem[0]),float(elem[1]))) for elem in testing1]
centroids,_ = kmeans(testing1,10)
row,col = vq(testing1,centroids)
locationsgroup = {}
keyone = len(locationsgroup)+1
for jj in range(0, len(row)):
for ii in range(0, len(np.nonzero(row == jj)[0])):
locationsgroup = addtogroupkey(locationsgroup, keyone, locations[np.nonzero(row == jj)[0][ii]])
keyone = len(locationsgroup)+1
#for ii in range(0, len(np.nonzero(row == jj)[0])):
#locationsgroup = addtogroupkey(locationsgroup, keyone, locations[np.nonzero(row == jj)[0][ii]])
#keyone = len(locationsgroup)+1
colortolocation[eachcolor] = locationsgroup
count = 0
#for eachcolor in max_key:
#app = Application().start("notepad.exe")
#dlg_spec = app.window(title='Untitled - Notepad')
#dlg_spec.maximize()
eachcolor = (0,0,0)
if 1 == 1:
for kk in colortolocation[eachcolor]:
if len(colortolocation[eachcolor][kk]) > 0:
x = min(colortolocation[eachcolor][kk])[0]-5
y = min(colortolocation[eachcolor][kk])[1]-5
xw = max(colortolocation[eachcolor][kk])[0]+10
yh = max(colortolocation[eachcolor][kk])[1]+7
cv2.rectangle(im,(x,y),(xw,yh),(0,0,255),2)
#if x < 300 and y < 100:
#click((x+xw)/2,(y+yh)/2)
#time.sleep(5)
cv2.imwrite("C:\\Users\\martlee2\\Documents\\words\\"+str(count)+".png",im[y:yh,x:xw])
count = count + 1
im[dst>0.01*dst.max()]=[0,0,255]
cv2.imshow('norm',im)
cv2.waitKey(0)
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