def main():
FaceAPI.facesetdelete(check_empty=0)
create_table()
get_ID_name('./data/import')
cur.execute("delete from `face_data` where ID=0;")
conn.commit()
creat_faceset()
cur.close()
conn.close()
def creat_faceset():
cur.execute("select face_token from face_data")
result = FaceAPI.facesetcreate()
column = cur.fetchall()
a = zip(*column)
a = list(a[0])
for i in a:
print("******************************************")
with open('./data/log/import.log', 'r') as f:
f = f.read()
if i in f:
print "{}:------Has Been Exist!".format(i)
if i not in f:
with open("./data/log/import.log", 'a') as f:
f.write(i)
print i
result = FaceAPI.facesetaddface(face_tokens=i)
print result
def detect(filename):
global face_token
count = 0
faces = []
face_cascade1 = cv2.CascadeClassifier(
'./data/cascades/haarcascade_frontalface_alt.xml')
face_cascade2 = cv2.CascadeClassifier(
'./data/cascades/haarcascade_frontalface_default.xml')
img = cv2.imread(filename)
gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
faces1 = face_cascade1.detectMultiScale(gray, 1.3, 5)
faces2 = face_cascade2.detectMultiScale(gray, 1.3, 5)
try:
faces = faces1 if faces1.size <= faces2.size else faces2
except AttributeError:
print "HEllO"
ft = cv2.freetype.createFreeType2()
ft.loadFontData(fontFileName='./data/font/simhei.ttf', id=0)
for (x, y, w, h) in faces:
img = cv2.rectangle(img, (x, y), (x + w, y + h), (0, 255, 255), 3)
f = cv2.resize(gray[y:y + h, x:x + w], (200, 200))
cv2.imwrite(
'./data/search_img/{}/{}.pgm'.format(
filesdir, time.strftime('%Y%m%d%H%M%S')), f)
result = FaceAPI.searchItoI(
image_file='./data/search_img/{}/{}.pgm'.format(
filesdir, time.strftime('%Y%m%d%H%M%S')))
if len(result) == 4:
break
if result["results"][0]["confidence"] >= 80.00:
print result["results"][0]["confidence"]
face_token = result["results"][0]["face_token"]
print "face_token：{}".format(face_token)
detail = get_detail()
# if not os.path.exists('./data/at/{}/{}.pgm'.format(detail[0],filesdir)):
# shutil.copyfile("./data/search_img/{}/{}.pgm".format(filesdir,time.strftime('%Y%m%d%H%M%S')),"./data/at/%s/%s.pgm"%(detail[0],filesdir))
ft.putText(img=img,
text=detail[1],
org=(x, y - 10),
fontHeight=30,
line_type=cv2.LINE_AA,
color=(0, 255, 165),
thickness=1,
bottomLeftOrigin=True)
else:
print "Unknow face"
cv2.putText(img, "Unknow", (x, y - 10),
cv2.FONT_HERSHEY_COMPLEX_SMALL, 1, (0, 0, 225), 2)
count += 1
cv2.imwrite(i, img)
def video():
global face_token
ft = cv2.freetype.createFreeType2()
ft.loadFontData(fontFileName='./data/font/simhei.ttf', id=0)
face_cascade = cv2.CascadeClassifier(
'./data/cascades/haarcascade_frontalface_alt.xml')
camera = cv2.VideoCapture(0)
count = 0
while (True):
ret, frame = camera.read()
gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
faces = face_cascade.detectMultiScale(gray, 1.3, 5)
for (x, y, w, h) in faces:
img = cv2.rectangle(frame, (x, y), (x + w, y + h), (0, 255, 255),
2)
if count % 10 == 1:
f = cv2.resize(gray[y:y + h, x:x + w], (200, 200))
cv2.imwrite('./data/temp/temp.pgm', f)
result = FaceAPI.searchItoI('./data/temp/temp.pgm')
if len(result) == 4:
break
if result["results"][0]["confidence"] >= 80.00:
print result["results"][0]["confidence"]
face_token = result["results"][0]["face_token"]
detail = get_detail()
# shutil.copyfile("./data/temp/temp.pgm","./data/at/%s/%s.pgm"%(detail,time.strftime('%Y%m%d%H%M%S')))
print detail
ft.putText(img=img,
text=detail[1],
org=(x, y - 10),
fontHeight=60,
line_type=cv2.LINE_AA,
color=(0, 255, 165),
thickness=2,
bottomLeftOrigin=True)
# count+=1
insert_data()
else:
print "Unknow face"
cv2.putText(img, "Unknow", (x, y - 10),
cv2.FONT_HERSHEY_COMPLEX_SMALL, 1, (0, 0, 225),
2)
count += 1
print count
cv2.namedWindow("image", cv2.WINDOW_NORMAL)
cv2.imshow("image", frame)
if cv2.waitKey(1000 / 12) & 0xff == ord("q"):
break
camera.release()
cv2.destroyAllWindows()
def check_stuID(ID):
global face_token, gender, facequality
cur.execute("select ID from face_data")
column = cur.fetchall()
a = zip(*column)
if ID in a[0]:
print "{}:------Has been Exist!".format(ID)
if ID not in a[0]:
result = FaceAPI.detect(image_file=imagedir)
face_token = result["faces"][0]["face_token"]
gender = result["faces"][0]["attributes"]["gender"]["value"]
facequality = result["faces"][0]["attributes"]["facequality"]["value"]
print "ID：{}".format(ID)
print "Name：{}".format(name)
print "face_token：{}".format(face_token)
print "gender：{}".format(gender)
print "facequality：{}".format(facequality)
insert_data()
def detect(filename):
global face_token
count = 0
faces = []
face_cascade = cv2.CascadeClassifier(
'./data/cascades/haarcascade_frontalface_alt.xml')
img = cv2.imread(filename)
gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
faces = face_cascade.detectMultiScale(gray, 1.3, 5)
ft = cv2.freetype.createFreeType2()
ft.loadFontData(fontFileName='./data/font/simhei.ttf', id=0)
for (x, y, w, h) in faces:
img = cv2.rectangle(img, (x, y), (x + w, y + h), (0, 255, 255), 3)
f = cv2.resize(gray[y:y + h, x:x + w], (200, 200))
cv2.imwrite('./data/search/{}/{}.pgm'.format(filesdir, count), f)
result = FaceAPI.searchItoI(
image_file='./data/search/{}/{}.pgm'.format(filesdir, count))
if len(result) == 4:
break
if result["results"][0]["confidence"] >= 80.00:
print result["results"][0]["confidence"]
face_token = result["results"][0]["face_token"]
print "face_token：{}".format(face_token)
detail = get_detail()
ft.putText(img=img,
text=detail[1],
org=(x, y - 10),
fontHeight=30,
line_type=cv2.LINE_AA,
color=(0, 255, 165),
thickness=1,
bottomLeftOrigin=True)
else:
print "Unknow face"
cv2.putText(img, "Unknow", (x, y - 10),
cv2.FONT_HERSHEY_COMPLEX_SMALL, 1, (0, 0, 225), 2)
count += 1
cv2.imwrite(i, img)
def video():
global db_face_token
count = 0
names = ['100000000001', '100000000002', '100000000003', '100000000004']
[X, y] = read_images()
y = np.asarray(y, dtype=np.int32)
model = cv2.face.createLBPHFaceRecognizer()
ft = cv2.freetype.createFreeType2()
ft.loadFontData(fontFileName='./data/font/simhei.ttf', id=0)
# model = cv2.face.createEigenFaceRecognizer()
model.train(np.asarray(X), np.asarray(y))
camera = cv2.VideoCapture(0)
face_cascade = cv2.CascadeClassifier(
'./data/cascades/haarcascade_frontalface_default.xml')
while (True):
read, img = camera.read()
faces = face_cascade.detectMultiScale(img, 1.3, 5)
if (count % 20) < 1:
for (x, y, w, h) in faces:
img = cv2.rectangle(img, (x, y), (x + w, y + h), (255, 245, 0),
2)
gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
f = cv2.resize(gray[y:y + h, x:x + w], (200, 200))
cv2.imwrite('./data/temp/temp.pgm', f)
result = FaceAPI.searchItoI(image_file='./data/temp/temp.pgm')
if len(result) == 4:
break
if result["results"][0]["confidence"] >= 80.00:
print result["results"][0]["confidence"]
face_token = result["results"][0]["face_token"]
detail = get_detail()
# shutil.copyfile("./data/temp/temp.pgm","./data/at/%s/%s.pgm"%(detail,time.strftime('%Y%m%d%H%M%S')))
print detail
ft.putText(img=img,
text=detail[1],
org=(x, y - 10),
fontHeight=60,
line_type=cv2.LINE_AA,
color=(0, 255, 165),
thickness=2,
bottomLeftOrigin=True)
count += 1
else:
print "Unknow face"
cv2.putText(img, "Unknow", (x, y - 10),
cv2.FONT_HERSHEY_COMPLEX_SMALL, 1, (0, 0, 225),
2)
else:
for (x, y, w, h) in faces:
img = cv2.rectangle(img, (x, y), (x + w, y + h), (0, 255, 255),
2)
gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
roi = gray[x:x + w, y:y + h]
try:
roi = cv2.resize(roi, (200, 200),
interpolation=cv2.INTER_LINEAR)
# print roi.shape
params = model.predict(roi)
print "Label: %s, Confidence: %.2f" % (params[0],
params[1])
# ft.putText(img=img, text=names[params[0]-1], org=(x, y - 20), line_type=cv2.LINE_AA, color=(0,255,255), thickness=2,bottomLeftOrigin=True)
cv2.putText(img, names[params[0] - 1], (x, y - 20),
cv2.FONT_HERSHEY_SIMPLEX, 1, 255, 2)
if (params[0] == 0):
cv2.imwrite('face_rec.jpg', img)
except:
continue
count += 1
print count
cv2.namedWindow("camera", cv2.WINDOW_NORMAL)
cv2.imshow("camera", img)
if cv2.waitKey(1000 / 12) & 0xff == ord("q"):
break
camera.release()
cv2.destroyAllWindows()