def __init__(self, devid):
self.devid = devid
# modes :runtime detect face shetai
self.mode = "runtime"
self.faceFlag = False
self.faceList =[-100,1200,100,200,-100]
self.face = FaceDetect()
self.faceStableStandar = 0
self.faceCount =0
super(CameraThread, self).__init__()
def face_query(test_image):
cfg = importlib.import_module("RetinaFace.data.config")
fd = FaceDetect("./weights/Resnet50_Gender_Final.pth", cuda=True, cfg=cfg.cfg_re50)
fa = FaceAlign(target_size=112)
ff = FaceFeatures('ArcFace/weights/arcface_resnet50_epoch_30.pth', cuda=True)
fq = FaceRetrival()
img = cv.imread(test_image, cv.IMREAD_COLOR)
faces, landmarks, points = fd(img, target_size=None, top=-1)
aligned_faces = fa(img, faces, landmarks)
features = ff(aligned_faces)
results = fq(features)
for point in points:
cv.rectangle(img, (point[0], point[1]), (point[2], point[3]), color=(0, 0, 255), thickness=2)
f_size = 50
fontpath = "./simsun.ttc"
font = ImageFont.truetype(fontpath, f_size)
img_pil = Image.fromarray(cv.cvtColor(img, cv.COLOR_BGR2RGB))
for point, result in zip(points, results):
draw = ImageDraw.Draw(img_pil)
print(result[0]['star'])
draw.text((point[0], point[1] - f_size), result[0]['star'], font=font, fill=(255, 0, 0))
img_pil.save("result_" + test_image.split('/')[-1])
def extract_features(src_dir, save_dir):
cfg = importlib.import_module("RetinaFace.data.config")
fd = FaceDetect("./weights/Resnet50_Gender_Final.pth", cuda=True, cfg=cfg.cfg_re50)
fa = FaceAlign(target_size=112)
ff = FaceFeatures('./weights/arcface_resnet50_epoch_30.pth', cuda=True)
images = []
for root, dirs, files in os.walk(src_dir):
if not dirs:
for file in files:
images.append(os.path.join(root, file))
print("total images:", len(images))
with open(save_dir, "w") as f:
writer = csv.writer(f)
for i, image in enumerate(tqdm(images, desc="Features extracting")):
try:
star, fname = image.split('/')[-2:]
dst_path = os.path.join("/data/datasets/chs_stars_faces", star)
if not os.path.exists(dst_path):
os.mkdir(dst_path)
img = cv.imread(image, cv.IMREAD_COLOR)
faces, landmarks, points = fd(img, target_size=640, top=-1, max_size=1280)
if len(faces) != 1:
continue
aligned_faces = fa(img, faces, landmarks)
cv.imwrite(os.path.join(dst_path, fname), aligned_faces[0])
features = ff(aligned_faces)
writer.writerow([star, fname, features[0]])
except Exception as e:
print(image, e)
def face_beauty(test_image):
cfg = importlib.import_module("RetinaFace.data.config")
fd = FaceDetect("./weights/Resnet50_Gender_Final.pth", cuda=True, cfg=cfg.cfg_re50)
fa = FaceAlign(target_size=224)
fb = FaceBeauty('Beauty/weight_local/beauty_ft_epoch_50.pth', cuda=True)
img = cv.imread(test_image, cv.IMREAD_COLOR)
faces, landmarks = fd(img, target_size=512, top=5)
aligned_faces = fa(img, faces, landmarks)
score = fb(aligned_faces)
def run(camera_port, drone):
"""Process frames from camera
"""
cam = cv2.VideoCapture(camera_port)
face_detect = FaceDetect()
transform = Transform()
video_record = VideoRecord(cam)
try:
running = True
while running:
running, frame = cam.read()
if running:
center = face_detect(frame)
if center is not None:
result = transform(frame, center)
print result
zap, phi, theta, gaz, yaw = result
#gaz = theta = phi = 0
if drone is not None:
drone.at(libardrone.at_pcmd, True, phi, theta, gaz,
yaw)
if drone is not None:
navdata = drone.navdata.get(0, {})
# check battery status
battery = navdata.get('battery')
if battery is not None and battery < 15:
print 'Low battery:', battery
running = False
print navdata
else:
# error reading frame
print 'Error reading video feed'
if drone is not None:
print 'Is WiFi connected to drone?'
video_record(frame)
if cv2.waitKey(1) & 0xFF == 27:
# escape key pressed so exit
running = False
except:
traceback.print_exc()
print 'Shutting down'
video_record.running = False
cam.release()
cv2.destroyAllWindows()
def __init__(self,
e_face=False,
e_helmet=False,
e_smoking=False,
TaskID='4396'):
threading.Thread.__init__(self)
self.e_face = e_face
self.e_helmet = e_helmet
self.e_smoking = e_smoking
if e_face:
self.e_face = FaceDetect()
if e_helmet:
self.e_helmet = MultiObjects_yolov3('yolo')
if e_smoking:
self.e_smoking = Smoking_yolo3('tiny')
self.period = 10
self.TaskID = '4396'
self.rq = redis.Redis(host='127.0.0.1', port=6379)
from pymongo import *
import gParam
from event import Event
from facedetect import FaceDetect
from inspection import Inspection
from mongo.mongodb import features_write, person_write
from newthread import NewThread
from periodins import MultiObjects_yolov3
from stoppableThread import StoppableThread
from utils.utils import setting
from videocap import VCAP
# 由于Event事件响应功能接口仍未确定，因此初始化过程无法确定，目前初始化仅在测试时使用
# 初始化各线程 Event功能时的初始化
f_dectect = FaceDetect()
v_cap = VCAP()
v_cap.video_path = gParam.Video_Path
v_cap.video = '1.mp4'
# v_cap.video_path = False
# v_cap.start()
f_dectect.start()
setdefaulttimeout(10)
with open(gParam.Client_Server_Cfg, 'r') as f:
configuration = json.loads(f.read())
print('客户端与服务端TCP连接配置如下', configuration)
# redis 连接池
pool = redis.ConnectionPool(host=configuration['REDIS_HOST'],
class CameraThread(QThread):
#定义信号,定义参数为str类型
_signal = pyqtSignal(str)
_signalError = pyqtSignal(dict)
_signalDetectFace = pyqtSignal(list)
_signalMessage = pyqtSignal(str)
lock = threading.Lock()
def __init__(self, devid):
self.devid = devid
# modes :runtime detect face shetai
self.mode = "runtime"
self.faceFlag = False
self.faceList =[-100,1200,100,200,-100]
self.face = FaceDetect()
self.faceStableStandar = 0
self.faceCount =0
super(CameraThread, self).__init__()
def run(self):
self.camera()
def camera(self):
cap = cv2.VideoCapture(self.devid)
if cap==None:
self._signalError.connect(PUBLIC.CAMERA_OPEN_ERROR)
return
# i = 0
_, frame = cap.read()
# 稳定因素
self.faceStableStandar = frame.shape[0]/8
beginTime =time.time()
while (True):
_, frame = cap.read()
# font = cv2.FONT_HERSHEY_SIMPLEX
# i = i + 1
# i = i % 100
# cv2.putText(frame,"read:"+str(result),(10,500), font, 4,(255,0,255),2,cv2.LINE_AA)
# cv2.imwrite("temp/temp"+str(i)+".jpg",frame)
# print("temp/temp_" + self.mode + ".jpg")
# 加锁
if self.lock.acquire():
# 每隔0.5s检查一下有无人脸
if time.time()-beginTime >= 0.5 and self.mode == "runtime" :
r=self.face.detect(frame,True)
if len(r)>0 and self.faceFlag==True:
# 如果人头接近静止
if self.isStable(r[0],self.faceStableStandar):
self._signalDetectFace.emit(list(r))
self.faceFlag =False
else:
# print("not stable")
self._signalMessage.emit("don't move")
cv2.imwrite("temp/temp_" + self.mode + ".jpg", frame)
if self.mode != "runtime":
print("mode:" + self.mode)
self.mode = "runtime"
self.lock.release()
else:
print("没有获取锁")
# cv2.imshow("video",frame)
self._signal.emit("temp/temp_runtime" + ".jpg")
cv2.waitKey(30)
def isStable(self,r,standar=100):
self.faceCount +=1
self.faceList[self.faceCount % 5] = r[0]+r[2]/2
temp = self.faceList[:]
temp.sort()
if temp[-1]-temp[0] < standar:
return True
else:
return False
def setMode(self, mode):
# modes :runtime detect face shetai
# 加锁
if (self.lock.acquire()):
self.mode = mode
self.lock.release()
def setFaceFlag(self, f):
# modes :runtime detect face shetai
# 加锁
if (self.lock.acquire()):
self.faceFlag = f
self.lock.release()