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CameraDemo.py
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# coding:utf-8
from FaceAlignment import FaceAlignment
import numpy as np
import cv2
import utils
import globalvariable as gvar
import socket # 导入 socket 模块
# Change this to True if you want to use the DAN-Menpo-tracking.npz model,
# which is able to detect when face tracking is lost.
useTrackingModel = False
port = 12344
if useTrackingModel:
model = FaceAlignment(112, 112, 1, 1, True)
model.loadNetwork("model/DAN-Menpo-tracking.npz")
else:
model = FaceAlignment(112, 112, 1, 2)
model.loadNetwork("model/DAN-Menpo.npz")
vidIn = cv2.VideoCapture(0)
cascade = cv2.CascadeClassifier("data/haarcascade_frontalface_alt.xml")
neutral_face_flag = True
neutral_landmarks_std = []
reset = True
landmarks = None
print ("Press space to detect the face, press escape to exit")
while True:
vis = vidIn.read()[1]
if len(vis.shape) > 2:
img = np.mean(vis, axis=2).astype(np.uint8)
else:
img = vis.astype(np.uint8)
if reset:
rects = cascade.detectMultiScale(img, scaleFactor=1.2, minNeighbors=3, minSize=(50, 50))
if len(rects) > 0:
minX = rects[0][0]
maxX = rects[0][0] + rects[0][2]
minY = rects[0][1]
maxY = rects[0][1] + rects[0][3]
cv2.rectangle(vis, (minX, minY), (maxX, maxY), (255, 0, 0))
initLandmarks = utils.bestFitRect(None, model.initLandmarks, [minX, minY, maxX, maxY])
reset = False
if model.confidenceLayer:
landmarks, confidence = model.processImg(img[np.newaxis], initLandmarks)
if confidence < 0.1:
reset = True
else:
landmarks = model.processImg(img[np.newaxis], initLandmarks)
landmarks = landmarks.astype(np.int32)
for i in range(landmarks.shape[0]):
cv2.circle(vis, (landmarks[i, 0], landmarks[i, 1]), 2, (0, 255, 0))
# 以鼻子为原点，计算其余所有点的坐标
landmarks = landmarks.astype(np.float)
landmarks_std = landmarks - landmarks[30] # 所有坐标以鼻尖点为中心
if neutral_face_flag:
neutral_landmarks_std = landmarks_std
neutral_face_flag = False
else:
landmarks_std = landmarks_std - neutral_landmarks_std
# pos_nosetip = landmarks[30]
# pos_lefteye = (landmarks[36] + landmarks[39]) / 2
# pos_righteye = (landmarks[42] + landmarks[45]) / 2
bottom = max(landmarks_std[:, 1])
top = min(landmarks_std[:, 1])
left = min(landmarks_std[:, 0])
right = max(landmarks_std[:, 0])
landmarks_std[:, 0] = landmarks_std[:, 0] / (right - left)
landmarks_std[:, 1] = landmarks_std[:, 1] / (bottom - top)
g_fAU4 = 0.3 * (landmarks_std[17, 1] + 0.35) + \
0.3 * (landmarks_std[18, 1] + 0.4) + \
0.3 * (landmarks_std[19, 1] + 0.4) + \
0.3 * (landmarks_std[20, 1] + 0.4) + \
0.3 * (landmarks_std[21, 1] + 0.38)
if g_fAU4 < 0:
g_fAU4 = 0
if g_fAU4 > 1:
g_fAU4 = 1
gvar.set_g_fAU4(g_fAU4)
print(g_fAU4)
# create the string
info = "g_fAU4:" + str(g_fAU4)
# send the flag to client
s = socket.socket() # 创建 socket 对象
host = socket.gethostname() # 获取本地主机名
s.connect((host, port))
s.send(info)
s.close()
else:
initLandmarks = utils.bestFitRect(landmarks, model.initLandmarks)
if model.confidenceLayer:
landmarks, confidence = model.processImg(img[np.newaxis], initLandmarks)
if confidence < 0.1:
reset = True
else:
landmarks = model.processImg(img[np.newaxis], initLandmarks)
landmarks = np.round(landmarks).astype(np.int32)
for i in range(landmarks.shape[0]):
cv2.circle(vis, (landmarks[i, 0], landmarks[i, 1]), 2, (0, 255, 0))
# # # # # # #
pos_nosetip = landmarks[30]
pos_lefteye = (landmarks[36] + landmarks[39]) / 2
pos_righteye = (landmarks[42] + landmarks[45]) / 2
# 以鼻子为原点，计算其余所有点的坐标
landmarks = landmarks.astype(np.float)
landmarks_std = landmarks - landmarks[30] # 所有坐标以鼻尖点为中心
# landmarks_std[:, 1] = -landmarks_std[:, 1] # 转换为常用的标准四象限坐标
if neutral_face_flag:
neutral_landmarks_std = landmarks_std
neutral_face_flag = False
else:
# pos_nosetip = landmarks[30]
# pos_lefteye = (landmarks[36] + landmarks[39]) / 2
# pos_righteye = (landmarks[42] + landmarks[45]) / 2
bottom = max(landmarks_std[:, 1])
top = min(landmarks_std[:, 1])
left = min(landmarks_std[:, 0])
right = max(landmarks_std[:, 0])
landmarks_std[:, 0] = landmarks_std[:, 0] / (right - left)
landmarks_std[:, 1] = landmarks_std[:, 1] / (bottom - top)
# # 检验眉毛
# landmarks_std[[i for i in range(17, 22)]] # left
# landmarks_std[[i for i in range(22, 27)]] # right
#
g_fAU4 = 0.3 * (landmarks_std[17, 1] + 0.35) + \
0.3 * (landmarks_std[18, 1] + 0.4) + \
0.3 * (landmarks_std[19, 1] + 0.4) + \
0.3 * (landmarks_std[20, 1] + 0.4) + \
0.3 * (landmarks_std[21, 1] + 0.38)
if g_fAU4 < 0:
g_fAU4 = 0
if g_fAU4 > 1:
g_fAU4 = 1
gvar.set_g_fAU4(g_fAU4)
print(g_fAU4)
# create the string
info = "g_fAU4:" + str(g_fAU4)
# send the flag to client
s = socket.socket() # 创建 socket 对象
host = socket.gethostname() # 获取本地主机名
s.connect((host, port))
s.send(info)
s.close()
cv2.imshow("image", vis)
key = cv2.waitKey(1)
if key == 27:
break
if key == 32:
reset = True
s.close()