def myclick(self):
goods = self.lineEdit.text()
depth = 4
start_url = 'https://s.taobao.com/search?q=' + goods
for i in range(depth): # 循环3次
try:
url = start_url + '&s=' + str(44 * i) # 淘宝商品页面列表从0,44,88。
html = Test1.getHTMLText(url) # 两个函数
plt = re.findall(
r'\"view_price\"\:\"[\d\.]*\"', html
) # 以列表类型返回形如 "view_price":"186.2" ,反斜杠\" \"表示"view_price"
tlt = re.findall(r'\"raw_title\"\:\".*?\"', html)
for i in range(len(plt)):
price = eval(plt[i].split(':')[1]) # 详见淘宝商品信息爬虫（1）
title = eval(tlt[i].split(':')[1])
item = QtWidgets.QTreeWidgetItem()
item.setText(0, title)
item.setData(1, QtCore.Qt.DisplayRole, float(price))
self.treeWidget.addTopLevelItem(item)
except:
continue
print("222")
def getTest1C2AsC2(self, current):
return Test1.C2()
def getTest1C2AsObject(self, current):
return Test1.C2()
#-------------------------------Main body
#loading an image
#I=cv2.imread("colorProblem.jpg")
#R,G,B = I[:,:,0], I[:,:,1], I[:,:,2]
#for i in [R,G,B]:
# I_eq = cv2.equalizeHist(i)
# n,bins = histogram(array(I_eq),256,normed=True)
# displayHistogram(n,bins)
#Equalizing blue channel and merging
I = cv2.imread("colorProblem.jpg")
R, G, B = I[:, :, 0], I[:, :, 1], I[:, :, 2]
B_eq = cv2.equalizeHist(B)
I_mod = cv2.merge([R, G, B_eq])
Test1.show2_OpenCV(I, I_mod)
#------Example of histogram equalization
#loading an image
#I=cv2.imread("Eye3.jpg")
#I=cv2.cvtColor(I, cv2.COLOR_RGB2GRAY)
#I_eq = cv2.equalizeHist(I)
#Test1.show2_OpenCV(I,I_eq)
#n,bins = histogram(array(I),256,normed=True)
#n2,bins2= histogram(array(I_eq),256,normed=True)
#displayHistogram(n,bins)
#displayHistogram(n2,bins2)
'''
Created on 19-02-2013
@author: Wiktor
'''
import Test1
import cv2
from pylab import *
def greyLevelMapLambdaWay(II,b,a):
(M,N)=II.shape
cc=zeros((M,N),uint8)
for i in range(len[II]):
cc[i] = map(lambda x: max(min(x*a+b,255),0), II[i]) # MAP FUNCTION!!!!!!!
return cc
I1=cv2.imread("GreenTest.jpg")
I2 = cv2.cvtColor(I1, cv2.COLOR_RGB2GRAY)
I2 = greyLevelMapLambdaWay(I2, 2, 1)
Test1.show1_OpenCV(I2)
with open('result.txt', 'a') as f:
f.write('\n')
f.write(video_name)
# video_name='video.wmv'
im_dir = os.path.join(osp.dirname(__file__), 'frame')
head_dir = os.path.join(osp.dirname(__file__), 'head')
eye_dir = os.path.join(osp.dirname(__file__), 'eye')
cut_dir = os.path.join(osp.dirname(__file__), 'cut')
if not os.path.exists(im_dir):
os.mkdir(im_dir)
vc = cv2.VideoCapture(os.path.join(video_dir, video_name))
if vc.isOpened():
totalFrameNumber = vc.get(cv2.cv.CV_CAP_PROP_FRAME_COUNT)
totalFrameNumber = Test1.interception_video(
video_dir, video_name, im_dir, totalFrameNumber)
print totalFrameNumber
numpy = True
for root, dirs, files in os.walk(im_dir):
if len(files) == 0:
numpy = False
if numpy:
print 'demo1~~~~~~~~~~~~~~~~~~~~~'
board_datas = []
board_datas = demo1.main()
gc.collect()
print 'demo2~~~~~~~~~~~~~~~~~~~~~'
head_datas = demo2.main()
gc.collect()
video_name = 'video.wmv'
im_dir = os.path.join(osp.dirname(__file__), 'frame')
head_dir = os.path.join(osp.dirname(__file__), 'head')
eye_dir = os.path.join(osp.dirname(__file__), 'eye')
if not os.path.exists(im_dir):
os.mkdir(im_dir)
vc = cv2.VideoCapture(os.path.join(video_dir, video_name))
if vc.isOpened():
totalFrameNumber = vc.get(cv2.cv.CV_CAP_PROP_FRAME_COUNT)
shutil.rmtree(eye_dir)
os.mkdir(eye_dir)
shutil.rmtree(head_dir)
os.mkdir(head_dir)
shutil.rmtree(im_dir)
os.mkdir(im_dir)
Test1.interception_video(video_dir, video_name, im_dir)
numpy = True
for root, dirs, files in os.walk(im_dir):
if len(files) == 0:
numpy = False
if numpy:
print 'demo1~~~~~~~~~~~~~~~~~~~~~'
board_datas = []
board_datas = demo1.main()
print 'demo2~~~~~~~~~~~~~~~~~~~~~'
head_datas = demo2.main()
if not os.path.exists(head_dir):
os.mkdir(head_dir)
NAN.getHead(im_dir, head_dir, head_datas)
numpy = True
def throwTest1Def(self, current):
raise Test1._def()
ax.set_xlim(left[0], right[-1])
ax.set_ylim(bottom.min(), top.max())
plt.show()
#-------------------------------Main body
#loading an image
I=cv2.imread("colorProblem.jpg")
#Creating the image histogram
n,bins = histogram(array(I),256,normed=True)
#displaing the histogram
displayHistogram(n,bins)
#------Example of histogram equalization
#loading an image
I=cv2.imread("colorProblem.jpg")
I=cv2.cvtColor(I, cv2.COLOR_RGB2GRAY)
I_eq = cv2.equalizeHist(I)
Test1.show2_OpenCV(I,I_eq)
def ChangeGreenToWhite(I, Gthr):
R, G, B = cv2.split(I)
I2 = nonzero((G >= Gthr)) # Zwraca indexy wszystkich elementow dla ktorych condition is true
I[I2] = [255, 255, 255]
return I
def ChangeGreenScreenRGB(I, Ibcg, Gthr):
R, G, B = cv2.split(I)
I2 = nonzero((G >= Gthr))
I[I2] = Ibcg[I2]
return I
I = cv2.imread("GreenTest.jpg")
Ibcg = cv2.imread("GreenTest_Background.jpg")
t.show1_OpenCV(ChangeGreenScreenRGB(I, Ibcg, 180))
"""
#Replace all numbers >2 and <10 with 1
T = np.array(range(0,20))
T1 = nonzero((T>3) & (T<10))
T[T1] = 1
print T
"""
end = time()
temp = end - start
print("Sample's median chosen with selectDet time -->", temp)
# SMALL SAMPLE WITH SORTING
A = B
start = time()
Test5.QuickSort(A, m) # Sample ordered with selectionSort
end = time()
temp = end - start
print("Sample sorted with selectionSort time -->", temp)
A = B
start = time()
Test1.QuickSort(A, m) # Sample ordered with inserctionSort
end = time()
temp = end - start
print("Sample sorted with inserctionSort time -->", temp)
A = B
start = time()
test9.QuickSort(A, m) # Sample ordered with bubbleSort
end = time()
temp = end - start
print("Sample sorted with bubbleSort time -->", temp)
# OTHER SORTING ALGHORITMS
A = B
start = time()
'''
Created on 19-02-2013
@author: Wiktor
'''
import Test1
import cv2
from pylab import *
def greyLevelMapLambdaWay(II, b, a):
(M, N) = II.shape
cc = zeros((M, N), uint8)
for i in range(len[II]):
cc[i] = map(lambda x: max(min(x * a + b, 255), 0),
II[i]) # MAP FUNCTION!!!!!!!
return cc
I1 = cv2.imread("GreenTest.jpg")
I2 = cv2.cvtColor(I1, cv2.COLOR_RGB2GRAY)
I2 = greyLevelMapLambdaWay(I2, 2, 1)
Test1.show1_OpenCV(I2)
I2 = nonzero((G>=Gthr)) #Zwraca indexy wszystkich elementow dla ktorych condition is true
I[I2] = [255, 255, 255]
return I
def ChangeGreenScreenRGB(I, Ibcg, Gthr):
R,G,B = cv2.split(I)
I2 = nonzero((G>=Gthr))
I[I2] = Ibcg[I2]
return I
I = cv2.imread("GreenTest.jpg")
Ibcg = cv2.imread("GreenTest_Background.jpg")
t.show1_OpenCV(ChangeGreenScreenRGB(I, Ibcg, 180))
"""
#Replace all numbers >2 and <10 with 1
T = np.array(range(0,20))
T1 = nonzero((T>3) & (T<10))
T[T1] = 1
print T
"""
#-------------------------------Main body
#loading an image
#I=cv2.imread("colorProblem.jpg")
#R,G,B = I[:,:,0], I[:,:,1], I[:,:,2]
#for i in [R,G,B]:
# I_eq = cv2.equalizeHist(i)
# n,bins = histogram(array(I_eq),256,normed=True)
# displayHistogram(n,bins)
#Equalizing blue channel and merging
I=cv2.imread("colorProblem.jpg")
R,G,B = I[:,:,0], I[:,:,1], I[:,:,2]
B_eq = cv2.equalizeHist(B)
I_mod = cv2.merge([R,G, B_eq])
Test1.show2_OpenCV(I, I_mod)
#------Example of histogram equalization
#loading an image
#I=cv2.imread("Eye3.jpg")
#I=cv2.cvtColor(I, cv2.COLOR_RGB2GRAY)
#I_eq = cv2.equalizeHist(I)
#Test1.show2_OpenCV(I,I_eq)
#n,bins = histogram(array(I),256,normed=True)
#n2,bins2= histogram(array(I_eq),256,normed=True)
#displayHistogram(n,bins)
#displayHistogram(n2,bins2)
def throwTest1E2AsE2(self, current):
raise Test1.E2()
def startIdentify():
recognizer = cv2.face.LBPHFaceRecognizer_create()
recognizer.read('trainer/trainer.yml')
#cascadePath = "haarcascade_frontalface_default.xml"
#faceCascade = cv2.CascadeClassifier(cascadePath);
faceCascade = cv2.CascadeClassifier(
'C:/Users/e3003895/AppData/Local/Continuum/anaconda3/Lib/site-packages/cv2/data/haarcascade_frontalface_default.xml'
)
font = cv2.FONT_HERSHEY_SIMPLEX
#iniciate id counter
id = 0
# names related to ids: example ==> Prasanna: id=1, etc
names = ['None', 'Prasanna', '', '', '', 'W']
# Initialize and start realtime video capture
cam = cv2.VideoCapture(0)
cam.set(3, 640) # set video widht
cam.set(4, 480) # set video height
# Define min window size to be recognized as a face
minW = 0.1 * cam.get(3)
minH = 0.1 * cam.get(4)
while True:
ret, img = cam.read()
#img = cv2.flip(img, -1) # Flip vertically
gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
faces = faceCascade.detectMultiScale(
gray,
scaleFactor=1.2,
minNeighbors=5,
minSize=(int(minW), int(minH)),
)
print('Number of faces detected: ' + str(len(faces)))
for (x, y, w, h) in faces:
cv2.rectangle(img, (x, y), (x + w, y + h), (0, 255, 0), 2)
id, confidence = recognizer.predict(gray[y:y + h, x:x + w])
# Check if confidence is less them 100 ==> "0" is perfect match
#pm#if (confidence < 100):
if (confidence < 80):
id = names[id]
#pm#confidence = " {0}%".format(round(100 - confidence))
confidence = " {0}%".format(round(confidence))
else:
id = "unknown"
#pm#confidence = " {0}%".format(round(100 - confidence))
confidence = " {0}%".format(round(confidence))
cv2.putText(img, str(id), (x + 5, y - 5), font, 1, (255, 255, 255),
2)
cv2.putText(img, str(confidence), (x + 5, y + h - 5), font, 1,
(255, 255, 0), 1)
cv2.imshow('camera', img)
k = cv2.waitKey(10) & 0xff # Press 'ESC' for exiting video
if k == 27:
break
# Do a bit of cleanup
print("\n [INFO] Exiting Program and cleanup stuff")
cam.release()
cv2.destroyAllWindows()
print('detected id is ' + id)
#ID_INT = int(id)
return Test1.render_static(id)
def throwTest1Def(self, current):
raise Test1._def()
import Test1 Test1.test()
