def test_06_unrecog_valid(self):
"""\
Test face against a database that it does not exist in, and the graveful return.
"""
recogniser_invalid = facerecognition.FaceRecognition(
self.pickle_file_invalid)
recognition_invalid = recogniser_invalid.recognise_face()
self.assertEqual(recognition_invalid, None)
def test_05_recog_valid(self):
"""
Test face against database it does exist in.
"""
print("LOOK AT CAMERA for 30 seconds!")
recogniser_valid = facerecognition.FaceRecognition(
self.pickle_file_valid)
recognition_valid = recogniser_valid.recognise_face()
self.assertEqual(recognition_valid, self.face_valid)
def main():
camid = 1
cap = cvs.VideoCapture(camid)
facerecog = facerecognition.FaceRecognition("./models", 0.63)
fcount = 0
start = time.time()
while True:
sleep(30)
img = cvs.read()
if img is None:
continue
fcount = fcount + 1
# global lbs
lbs = 'Average FPS: ' + str(fcount / (time.time() - start))
cvs.setLbs(lbs)
if camid == 1:
img = cv2.flip(img, 1)
#img=cv2.resize(img,(112,112))
image_char = img.astype(np.uint8).tostring()
rets = facerecog.getfacepose(img.shape[0], img.shape[1], image_char)
#print 'rets:',rets
for ret in rets:
#for ret in each:
print('draw bounding box for the face')
#cvs.infoshow('draw bounding box for the face')
rect = ret['rect']
#print rect
mtcnn = ret['mtcnn']
#print mtcnn
for i in range(5):
cvs.circle(img, (mtcnn[i], mtcnn[5 + i]), 2, (0, 0, 255), 2)
keypoint = ret['keypoints']
#print keypoint
p1 = (int(rect[0]), int(rect[1]))
p2 = (int(rect[0] + rect[2]), int(rect[1] + rect[3]))
#draw_name(img, rect, ret['name'])
cvs.rectangle(img, p1, p2, (0, 255, 0), 3, 1)
for p in range(0, 106):
#print p*2,' = ',keypoint[p*2]
#print p*2+1,' = ',keypoint[p*2+1]
k1 = int(rect[0] + keypoint[p * 2])
k2 = int(rect[1] + keypoint[p * 2 + 1])
cv2.circle(img, (k1, k2), 2, (253, 0, 0), 2)
cvs.imshow(img)
def main():
cap = cvs.VideoCapture(1)
facerecog = facerecognition.FaceRecognition("./models", 0.73)
max_none = 0
#facerecog = facerecognition.FaceRecognition("./models",0.6)
while True:
sleep(30)
img = cvs.read()
if img is None:
continue
#imshow(img)
#continue
#img=cv2.resize(img,(112,112))
image_char = img.astype(np.uint8).tostring()
msgType, msgName = cvs.getMsg()
if msgName != '' and msgType == 'add_person':
ret = facerecog.add_person(msgName, img.shape[0], img.shape[1],
image_char)
if ret == 0:
print 'you add_person is success!'
cvs.setMsg_status(1)
else:
print 'you add_person is failed!'
cvs.setMsg_status(-1)
#cv2.putText(img, ret['name'], (int(rect[0]), int(rect[1])-30),cv2.FONT_ITALIC, 2, (77, 255, 9), 2)
continue #
rets = facerecog.recognize(img.shape[0], img.shape[1], image_char)
print 'rets:', rets
for ret in rets:
#for ret in each:
print 'draw bounding box for the face'
rect = ret['rect']
p1 = (int(rect[0]), int(rect[1]))
p2 = (int(rect[0] + rect[2]), int(rect[1] + rect[2]))
#draw_name(img, rect, ret['name'])
cv2.rectangle(img, p1, p2, (0, 255, 0), 3, 1)
cv2.putText(img, ret['name'], (int(rect[0]), int(rect[1]) - 30),
cv2.FONT_ITALIC, 2, (77, 255, 9), 2)
cvs.infoshow('your name:' + ret['name'])
#final = cv2.copyMakeBorder(img,0,0,64,64, cv2.BORDER_CONSTANT,value=[255,255,255])
#final=cv2.flip(final,1)
cvs.imshow(img)
def process():
cap = cvs.VideoCapture(1)
facerecog = facerecognition.FaceRecognition("./models", 0.73)
while True:
sleep(30)
img = cap.read()
if img is None:
continue
image_char = img.astype(np.uint8).tostring()
userId = cvs.getLbs()
if userId != '':
ret = facerecog.add_person(userId, img.shape[0], img.shape[1],
image_char)
if ret == 0:
print('you add_person is success!')
# cvs.setMsg_status(1)
else:
print('you add_person is failed!')
userId = ''
cvs.setLbs(userId)
continue
rets = facerecog.recognize(img.shape[0], img.shape[1], image_char)
#print 'rets:',rets
for ret in rets:
#for ret in each:
print('draw bounding box for the face')
rect = ret['rect']
p1 = (int(rect[0]), int(rect[1]))
p2 = (int(rect[0] + rect[2]), int(rect[1] + rect[2]))
#draw rect,names of faces
cv2.rectangle(img, p1, p2, (0, 255, 0), 3, 1)
cv2.putText(img, ret['name'], (int(rect[0]), int(rect[1]) - 30),
cv2.FONT_ITALIC, 2, (77, 255, 9), 2)
cvs.imshow(img)
def main():
cap=cvs.VideoCapture(1)
facerecog = facerecognition.FaceRecognition("./models", 0.63)
max_none=0
#facerecog = facerecognition.FaceRecognition("./models",0.6)
while True:
sleep(30)
img =cvs.read()
if img is None :
continue
#imshow(img)
#continue
img=cv2.flip(img,1)
#img=cv2.resize(img,(112,112))
image_char = img.astype(np.uint8).tostring()
rets = facerecog.getfacepose(img.shape[0], img.shape[1], image_char)
#print 'rets:',rets
for ret in rets:
#for ret in each:
print 'draw bounding box for the face'
rect = ret['rect']
print rect
mtcnn = ret['mtcnn']
print mtcnn
for i in range(5):
cv2.circle(img,(mtcnn[i],mtcnn[5+i]),2,(0,0,255),2)
keypoint=ret['keypoints']
#print keypoint
p1 = (int(rect[0]), int(rect[1]))
p2 = (int(rect[0]+rect[2]), int(rect[1]+rect[3]))
#draw_name(img, rect, ret['name'])
cv2.rectangle(img, p1,p2, (0, 255, 0) , 3, 1)
for p in range(0,106):
print p*2,' = ',keypoint[p*2]
print p*2+1,' = ',keypoint[p*2+1]
k1=int(rect[0]+keypoint[p*2])
k2=int(rect[1]+keypoint[p*2+1])
cv2.circle(img,(k1,k2),2,(253,0,0),2)
#cv2.putText(img, ret['name'], (20, 50),cv2.FONT_ITALIC, 2, (77, 255, 9), 2)
#final = cv2.copyMakeBorder(img,0,0,64,64, cv2.BORDER_CONSTANT,value=[255,255,255])
#final=cv2.flip(final,1)
cvs.imshow(img)
import numpy as np
import time, os
from multiprocessing import Process, Queue
import struct
import paho.mqtt.client as mqtt
import argparse
import SocketServer
import time
from PIL import Image
parser = argparse.ArgumentParser()
parser.add_argument('--svr',
type=str,
help='The ip for laptop training server')
facerecg = facerecognition.FaceRecognition("./models", 0.63)
HOST = ''
PORT = 21575
ADDR = (HOST, PORT)
bufSize = 4080
def recognize(rawData):
img = Image.frombytes('RGB', (480, 272), rawData, 'raw', 'RGB;16')
npimg = np.rot90(np.array(img), -1)
image_char = npimg.astype(np.uint8).tostring()
rets = facerecg.recognize(npimg.shape[0], npimg.shape[1], image_char)
if rets is None or len(rets) == 0:
import numpy as np
import facerecognition, cv2
class call_cpp(object):
def __init__(self, name):
self.itcom = mobilefacenet.communication(name)
def run(self, img) :
ret_list = self.itcom.test(img.shape[0], img.shape[1], image_char)
gray = np.zeros([img.shape[0], img.shape[1]], np.ubyte)
c = 0
for i in range(img.shape[0]):
for j in range(img.shape[1]):
gray[i][j] = ret_list[c]
c += 1
return gray
def run_class(self):
return self.itcom.ret_box_list()
if __name__ == '__main__':
facerecog = facerecognition.FaceRecognition("../models/")
img = cv2.imread('6.png')
image_char = img.astype(np.uint8).tostring()
#facerecog.recognize(img.shape[0], img.shape[1], image_char)
facerecog.add_person("gf", img.shape[0], img.shape[1], image_char)