def get_best_rect(self, rects_list, rects_xyz_list, rects_center):
"""
对于找到的一堆矩形选取最为正确的
:param rects_list: 矩形4个点的list
:param rects_xyz_list: 矩形xyz的4个点
:return:
"""
if len(rects_list) == 1:
return rects_list[0], rects_xyz_list[0], rects_center[0]
elif len(rects_list) == 0:
return None, None, None
else: #多于1个的情况
if DEBUG_FLAG:
print("出现了多个矩形的情况,他们的矩形情况为:")
print(rects_list)
print(rects_xyz_list)
correct = self.error
correct_i = 0
for i, middle_xyzs in enumerate(rects_xyz_list):
distance1 = tools.get_distance(middle_xyzs[0], middle_xyzs[3])
distance2 = tools.get_distance(middle_xyzs[1], middle_xyzs[2])
temp = abs((distance1 + distance2) / 2 -
self.target_legnth / 2) - self.error
if temp < correct:
correct_i = i
return rects_list[correct_i], rects_xyz_list[
correct_i], rects_center[correct_i]
def get_neighbors(nodes, node_id, node_type, d, auv_x, auv_y, auv_z, energy):
max_weight = 0
neighbor_id = -1
for i in range(len(nodes[0])):
if tools.get_distance(nodes[0][node_id], nodes[1][node_id],
nodes[2][node_id], nodes[0][i], nodes[1][i],
nodes[2][i]) <= d:
if node_type[i] != 0:
return i
weight = energy[i] / tools.get_distance(
nodes[0][i], nodes[1][i], nodes[2][i], auv_x, auv_y, auv_z)
max_weight, neighbor_id = (weight, i) if weight > max_weight else (
max_weight, neighbor_id)
return neighbor_id
def process_rect(self, station_rect, station_xyz):
"""
用于处理资源岛的矩形
最终得到x,y,z需要更改的值,速度先不管
:param station_rect:矩形的四个点(而非2个点四个值)
:param station_xyz:矩形的四个点对应的xyz
:return:
"""
leftdown, leftup, rightup, rightdown = station_rect #这里得到的是xy,而非wh
leftdown_xyz, leftup_xyz, rightup_xyz, rightdown_xyz = station_xyz
#获取中心点的xyz值
left_center = tools.get_middle(leftdown, leftup)
up_center = tools.get_middle(leftup, rightup)
# if DEBUG_FLAG:
# print("左边中心:",left_center,"右边中心为:",up_center)
center = (up_center[0], left_center[1])
center_xyz = self.detectStation.camera.get_xyz(center)
#获取左右的转角
x1, y1, z1 = leftup_xyz
x2, y2, z2 = rightup_xyz
distance = tools.get_distance(leftup_xyz, rightup_xyz)
temp_z = z1 - z2
xita_rad = math.asin(temp_z / distance)
xita = xita_rad * 180 / math.pi
return center, center_xyz, xita
def select_from_point(self):
for u in self.get_unit_list():
if tools.get_distance(self.init_xy, (u.x, u.y)) <= u.radius:
if not u.is_selected():
self.to_select.append(u)
elif self.keys[key.LSHIFT] and u.is_selected():
self.to_select.remove(u)
self.run_selection()
def check_conditions(self):
if tools.get_distance(self.unit.current_destination, self.unit.get_location()) < self.unit.radius*4:
return "idleing"
if self.idle_time >= self.waiting_period:
print "trying again"
return "movecommand"
return None
def select_from_point(self):
for u in self.get_unit_list():
if tools.get_distance(self.init_xy, (u.x, u.y)) <= u.radius:
if not u.is_selected():
self.to_select.append(u)
elif self.keys[key.LSHIFT] and u.is_selected():
self.to_select.remove(u)
self.run_selection()
def check_x_correct(self, middle_xyzs):
"""
送入中心矩形框的xyz值,查看是否为目标
:param middle_xyzs:中心矩形的xyzs
:return:
"""
distance1 = tools.get_distance(middle_xyzs[0], middle_xyzs[3])
distance2 = tools.get_distance(middle_xyzs[1], middle_xyzs[2])
X_temp = (distance1 + distance2) / 2
X_correct = abs(X_temp - self.target_legnth / 2) < self.error
if DEBUG_FLAG:
print("正确的X_temp为:", X_temp, "期望的距离为:", self.target_legnth / 2)
print("检测到的rect的X_temp为:", X_temp, "期望的距离为:",
self.target_legnth / 2)
return X_correct
def check_conditions(self):
if tools.get_distance(self.unit.current_destination,
self.unit.get_location()) < self.unit.radius * 4:
return "idleing"
if self.idle_time >= self.waiting_period:
print "trying again"
return "movecommand"
return None
def judge_node_type(nodes, node_type, phi, rho, omega, v_h, r, d, h, flag):
number = len(nodes[0])
for i in range(number):
# 如果节点与sink节点的距离小于等于通信半径，则为直接送达节点。这边本来应该是 <=r ,为了简单直接用安全距离。
if tools.get_distance(nodes[0][i], nodes[1][i], nodes[2][i], 0, 0,
0) <= d:
node_type[i] = 2
continue
# 解微分方程的方式求解太过麻烦，直接暴力破解。
t_max = h / v_h
min_distance = 65536
for t in range(int(t_max)):
auv_x, auv_y, auv_z = auv_position.get_auv_position_at_time_t(
t, phi, rho, omega, v_h, h, flag)
distance = tools.get_distance(nodes[0][i], nodes[1][i],
nodes[2][i], auv_x, auv_y, auv_z)
min_distance = distance if min_distance >= distance else min_distance
if min_distance <= d:
node_type[i] = 1
def collides(unit, other):
x1, y1 = unit.x + unit.dx, unit.y + unit.dy
x2, y2 = other.x + other.dx, other.y + other.dy
distance_old = tools.get_distance((unit.x, unit.y), (other.x, other.y))
distance = tools.get_distance((x1, y1), (x2, y2))
if unit.shape == "circle" and other.shape == "circle":
if distance <= unit.radius + other.radius:
return distance
else:
return False
if unit.shape == "rectangle" and other.shape == "circle":
if other.x + other.radius > unit.left and other.x - other.radius < unit.right:
if other.y + other.radius > unit.bottom and other.y - other.radius < unit.top:
return True
else:
return False
if unit.shape == "circle" and other.shape == "rectangle":
if unit.x > other.left and unit.x < other.right:
if unit.y > other.bottom and unit.y < other.top:
return True
else:
return False
def collides(unit, other):
x1, y1 = unit.x + unit.dx, unit.y + unit.dy
x2, y2 = other.x + other.dx, other.y + other.dy
distance_old = tools.get_distance((unit.x, unit.y), (other.x, other.y))
distance = tools.get_distance((x1, y1), (x2, y2))
if unit.shape == "circle" and other.shape == "circle":
if distance <= unit.radius + other.radius:
return distance
else:
return False
if unit.shape == "rectangle" and other.shape == "circle":
if other.x + other.radius > unit.left and other.x - other.radius < unit.right:
if other.y + other.radius > unit.bottom and other.y - other.radius < unit.top:
return True
else:
return False
if unit.shape == "circle" and other.shape == "rectangle":
if unit.x > other.left and unit.x < other.right:
if unit.y > other.bottom and unit.y < other.top:
return True
else:
return False
def check_conditions(self):
ranging_distance = tools.get_distance(self.unit.leash_point, self.unit.get_location())
if ranging_distance > self.unit.alert_range:
print "too far!"
self.unit.current_destination = self.unit.leash_point
return "movecommand"
# hostile_unit = self.unit.controller.get_close_entity(self.unit.get_location())
# if not hostile_unit:
# self.unit.target = None
# print "target lost"
# return "idleing"
return None
def check_conditions(self):
ranging_distance = tools.get_distance(self.unit.leash_point,
self.unit.get_location())
if ranging_distance > self.unit.alert_range:
print "too far!"
self.unit.current_destination = self.unit.leash_point
return "movecommand"
# hostile_unit = self.unit.controller.get_close_entity(self.unit.get_location())
# if not hostile_unit:
# self.unit.target = None
# print "target lost"
# return "idleing"
return None
files=os.listdir('testVedios/test'+nb_video+'/')
print(direction[1:])
for i in files:
if (len(re.findall('joints_3DKinect_.'+direction[1:]+'[^2]', i))!=0):
filecm=i
print(filecm)
k=pd.DataFrame(pd.read_csv('testVedios/test'+nb_video+'/'+filecm))
kk=k
# find wrong points
badpoints=0
for i in range(len(k['frames'])):
akdis=k['z_lak'][i]-k['z_rak'][i]
kndis=k['z_lkn'][i]-k['z_rkn'][i]
l_kn_ak=tools.get_distance((k['x_lkn'][i], k['y_lkn'][i], k['z_lkn'][i]), (k['x_lak'][i], k['y_lak'][i], k['z_lak'][i]))
r_kn_ak=tools.get_distance((k['x_rkn'][i], k['y_rkn'][i], k['z_rkn'][i]), (k['x_rak'][i], k['y_rak'][i], k['z_rak'][i]))
if i==20:
print(i,akdis, kndis)
if k['kangle_r'][i]<0 or (akdis**2<=400 and kndis<100 and kndis>-20) or (akdis**2<=400 and kndis>220):
k.loc[i,['bad_frame']]=10
badpoints+=1
print(i, kndis)
elif k['kangle_l'][i]<0 or (akdis**2<=400 and kndis<-205) or (akdis**2<=400 and kndis>-100 and kndis<10):
k.loc[i,['bad_frame']]=11
badpoints+=1
print(i,kndis)
###!!!!!!! zuihao zuo you jiao fen kai left: 0 right: 1
elif (k['z_las'][i]-k['z_ras'][i])>80:
k.loc[i,['bad_frame']]=20
badpoints+=1
def get_close_entity(self, location, e_range=100):
for entity in self.get_unit_list():
distance = tools.get_distance(location, (entity.x, entity.y))
if distance < e_range:
return entity
return None
def get_distance_from_target(self):
return tools.get_distance((self.unit.x, self.unit.y),
(self.unit.current_destination[0], self.unit.current_destination[1])
)
def show_angle3d(nb_vedio, frames):
files = os.listdir('testVedios/test' + nb_vedio + '/')
for i in files:
if (len(re.findall('.*C\.json', i)) != 0):
filejson = i
if (len(re.findall('.*D.mp4', i)) != 0):
filedepth = i
number = filedepth[:-5]
#if (len(re.findall('_distance_data.csv', i))!=0):
# filedis=i
print(number)
#print(filedis)
print(filejson)
#disdata=pd.DataFrame(pd.read_csv('testVedios/test'+nb_vedio+'/'+filedis))
fig = plt.figure()
ax = fig.add_subplot(211)
ax2 = fig.add_subplot(212)
ax.set_title('3d kinect LCR-NET_Improved')
ax.set_xlabel('Frame')
ax.set_ylabel('Angle_left')
ax2.set_xlabel('Frame')
ax2.set_ylabel('Angle_right')
with open('testVedios/test' + nb_vedio + '/' + filejson) as json_data:
d = json.load(json_data)
v = cv2.VideoCapture('testVedios/test' + nb_vedio + '/' + filedepth)
anglesl = []
anglesr = []
points3dx = [[] for p in range(13)]
points3dy = [[] for p in range(13)]
points3dz = [[] for p in range(13)]
points2dx = [[] for p in range(13)]
points2dy = [[] for p in range(13)]
points2ddx = [[] for p in range(13)]
points2ddy = [[] for p in range(13)]
akdis = []
kndis = []
step = []
bad_frame = [0] * (frames[1] - frames[0])
l_kn_ak = []
r_kn_ak = []
for t in tqdm(range(frames[0], frames[1])):
#print(t)
v.set(cv2.CAP_PROP_POS_FRAMES, t)
ret, im = v.read()
img_m = cv2.medianBlur(im, 7)
font = cv2.FONT_HERSHEY_SIMPLEX
'''
for i in range(800,980,2):
for j in range(300,860,5):
a=RGBto3D((i,j),im)
x.append(a[0])
y.append(a[1])
z.append(a[2])
print(i)
#ax.scatter(x,z,y)
'''
if len(d['frames'][t]) != 0:
xjoints2d = d['frames'][t][0]['pose2d'][:13]
yjoints2d = d['frames'][t][0]['pose2d'][13:]
xjoints3d = []
yjoints3d = []
zjoints3d = []
xjoints2dd = []
yjoints2dd = []
###!!!!!!!!!11111!!!!
leg = ['z_rak', 'z_lak', 'z_rkn', 'z_lkn', 'z_ras', 'z_las']
for i in range(13):
if i <= -5:
z3d = float(disdata[leg[i]][disdata['frame'] == t])
print(z3d)
joints = tools.RGBto3D((xjoints2d[i], yjoints2d[i], z3d),
im, t)
xjoints3d.append(joints[0])
yjoints3d.append(joints[1])
zjoints3d.append(joints[2])
else:
joints = tools.RGBto3D((xjoints2d[i], yjoints2d[i]), im, t,
True, 7)
xjoints3d.append(joints[0])
yjoints3d.append(joints[1])
zjoints3d.append(joints[2])
joints2dd = tools.RGBtoD((xjoints2d[i], yjoints2d[i]), t)
xjoints2dd.append(joints2dd[0])
yjoints2dd.append(joints2dd[1])
for p in range(13):
points3dx[p].append(xjoints3d[p])
points3dy[p].append(yjoints3d[p])
points3dz[p].append(zjoints3d[p])
points2dx[p].append(xjoints2d[p])
points2dy[p].append(yjoints2d[p])
points2ddx[p].append(xjoints2dd[p])
points2ddy[p].append(yjoints2dd[p])
anglesl.append(180 -
tools.angle((xjoints3d[1], yjoints3d[1], zjoints3d[1]),
(xjoints3d[3], yjoints3d[3],
zjoints3d[3]), (xjoints3d[5], yjoints3d[5],
zjoints3d[5]), False))
anglesr.append(180 -
tools.angle((xjoints3d[0], yjoints3d[0], zjoints3d[0]),
(xjoints3d[2], yjoints3d[2],
zjoints3d[2]), (xjoints3d[4], yjoints3d[4],
zjoints3d[4]), False))
# static analysis
# save the important information:dis between ankles, as height, leg length
l_kn_ak.append(
tools.get_distance((xjoints3d[1], yjoints3d[1], zjoints3d[1]),
(xjoints3d[3], yjoints3d[3], zjoints3d[3])))
r_kn_ak.append(
tools.get_distance((xjoints3d[0], yjoints3d[0], zjoints3d[0]),
(xjoints3d[2], yjoints3d[2], zjoints3d[2])))
dak = (zjoints3d[0] - zjoints3d[1])
dkn = (zjoints3d[2] - zjoints3d[3])
akdis.append(dak)
kndis.append(dkn)
# dynamic analysis
# gen qian mian de zhen xiang bi jiao
# Model : step automatic by Vicon !!!!front back!!!!! condition 1 2 3
# dis>0 : left joint is in front, dis<0 : right joint is in front
if dkn <= 0 and dak > -100:
step.append(0)
elif dak <= -100 and dkn < 0:
step.append(1)
elif dkn >= 0 and dak < 100:
step.append(2)
elif dak >= 100 and dkn > 0:
step.append(3)
else:
step.append(-1)
# find the wrong frame
# +++++++++++
# correct the wrong ponts
# +++++++++++
# angle 2d
# anglesl.append(180-tools.angle((yjoints[1],zjoints[1]),(yjoints[3],zjoints[3]),(yjoints[5],zjoints[5])))
# anglesr.append(180-tools.angle((yjoints[0],zjoints[0]),(yjoints[2],zjoints[2]),(yjoints[4],zjoints[4])))
'''
print(xjoints)
print(yjoints)
print(zjoints)
ax2.scatter(xjoints, zjoints, yjoints, color='r')
'''
v.release()
#b, a = signal.butter(8, 0.3, 'lowpass')
#anglesl = signal.filtfilt(b, a, anglesl)
#anglesr = signal.filtfilt(b, a, anglesr)
frames = range(frames[0], frames[1])
ax.plot(frames, anglesl)
ax2.plot(frames, anglesr, color='r') #, marker='.')
#for i in range(50): y1.append(i) # 每迭代一次，将i放入y1中画出来 ax.cla() # 清除键 ax.bar(y1, label='test', height=y1, width=0.3) ax.legend() plt.pause(0.1)
data2d = {}
data = {}
data2dd = {}
data2dd['frames'] = frames
data2d['frames'] = frames
data['frames'] = frames
data['kangle_l'] = anglesl
data['kangle_r'] = anglesr
data['akdis'] = akdis
data['kndis'] = kndis
data['l_kn_ak'] = l_kn_ak
data['r_kn_ak'] = r_kn_ak
data['bad_frame'] = bad_frame
print(len(step))
data['step'] = step
j = [
'rak', 'lak', 'rkn', 'lkn', 'ras', 'las', 'rwr', 'lwr', 'rel', 'lel',
'rsh', 'lsh', 'head'
]
for p in range(13):
data['x_' + j[p]] = points3dx[p]
data['y_' + j[p]] = points3dy[p]
data['z_' + j[p]] = points3dz[p]
data2d['x_' + j[p]] = points2dx[p]
data2d['y_' + j[p]] = points2dy[p]
data2dd['x_' + j[p]] = points2ddx[p]
data2dd['y_' + j[p]] = points2ddy[p]
data = pd.DataFrame(data)
data2d = pd.DataFrame(data2d)
data2dd = pd.DataFrame(data2dd)
if frames[0] > 250:
data.to_csv('testVedios' + '/test' + nb_vedio + '/' + number +
'_LCR-NET_joints_3DKinect_back.csv',
encoding='gbk')
data2d.to_csv('testVedios' + '/test' + nb_vedio + '/' + number +
'_LCR-NET_joints_2DColor_back.csv',
encoding='gbk')
data2dd.to_csv('testVedios' + '/test' + nb_vedio + '/' + number +
'_LCR-NET_joints_2DDepth_back.csv',
encoding='gbk')
#data1=pd.DataFrame({'frame':frames, 'angle_left':anglesl, 'angle_right':anglesr})
#data1.to_csv('testVedios'+'/test'+nb_vedio+'/'+number+'_LCR-NET_angles_3DKinect_back.csv',encoding='gbk')
else:
data2dd.to_csv('testVedios' + '/test' + nb_vedio + '/' + number +
'_LCR-NET_joints_2DDepth_front.csv',
encoding='gbk')
data2d.to_csv('testVedios' + '/test' + nb_vedio + '/' + number +
'_LCR-NET_joints_2DColor_front.csv',
encoding='gbk')
data.to_csv('testVedios' + '/test' + nb_vedio + '/' + number +
'_LCR-NET_joints_3DKinect_front.csv',
encoding='gbk')
def show_angle3d(nb_video, frames):
files=os.listdir('testVideos/test'+nb_video+'/')
for i in files:
if (len(re.findall('.*C\.json', i))!=0):
filejson=i
if (len(re.findall('.*D.mp4', i))!=0):
filedepth=i
number=filedepth[:-5]
if (len(re.findall('_PifPaf_joints_3DKinect_front.csv', i))!=0):
filedis=i
print(number)
print(filejson)
print(filedis)
print('testVideos'+'/test'+nb_video+'/'+number+'_PifPaf_joints_3DKinect_back.csv')
disdata=pd.DataFrame(pd.read_csv('testVideos/test'+nb_video+'/'+filedis))
fig=plt.figure()
ax=fig.add_subplot(211)
ax2=fig.add_subplot(212)
ax.set_title('3d kinect PifPaf_Original')
ax.set_xlabel('Frame')
ax.set_ylabel('Angle_left')
ax2.set_xlabel('Frame')
ax2.set_ylabel('Angle_right')
with open('testVideos/test'+nb_video+'/'+filejson) as json_data:
d = json.load(json_data)
v=cv2.VideoCapture('testVideos/test'+nb_video+'/'+filedepth)
anglesl=[]
anglesr=[]
points3dx=[[] for p in range(17)]
points3dy=[[] for p in range(17)]
points3dz=[[] for p in range(17)]
points2dx=[[] for p in range(17)]
points2dy=[[] for p in range(17)]
points2ddx=[[] for p in range(17)]
points2ddy=[[] for p in range(17)]
akdis=[]
kndis=[]
step=[]
bad_frame=[0]*(frames[1]-frames[0])
l_kn_ak=[]
r_kn_ak=[]
for t in tqdm(range(frames[0],frames[1])):
#print(t)
v.set(cv2.CAP_PROP_POS_FRAMES, t)
ret, im=v.read()
img_m=cv2.medianBlur(im,5)
font=cv2.FONT_HERSHEY_SIMPLEX
'''
for i in range(800,980,2):
for j in range(300,860,5):
a=RGBto3D((i,j),im)
x.append(a[0])
y.append(a[1])
z.append(a[2])
print(i)
#ax.scatter(x,z,y)
'''
if len(d['frames'][t])!=0:
xjoints2d=d['frames'][t][0]['pose2d'][:17]
yjoints2d=d['frames'][t][0]['pose2d'][17:]
zjoints3d=[]
xjoints3d=[]
yjoints3d=[]
xjoints2dd=[]
yjoints2dd=[]
leg=['z_las','z_ras','z_lkn','z_rkn','z_lak','z_rak']
for i in range(17):
if i in [11,13,15,12,14,16]:
z3d=float(disdata[leg[i-11]][disdata['frames']==t])
print(z3d)
joints=tools.RGBto3D((xjoints2d[i], yjoints2d[i], z3d), im, t)
xjoints3d.append(joints[0])
yjoints3d.append(joints[1])
zjoints3d.append(joints[2])
else:
joints=tools.RGBto3D((xjoints2d[i], yjoints2d[i]), im, t, True, 7)
xjoints3d.append(joints[0])
yjoints3d.append(joints[1])
zjoints3d.append(joints[2])
joints2dd=tools.RGBtoD((xjoints2d[i], yjoints2d[i]), t)
xjoints2dd.append(joints2dd[0])
yjoints2dd.append(joints2dd[1])
anglesl.append(180-tools.angle((xjoints3d[11],yjoints3d[11],zjoints3d[11]),(xjoints3d[13],yjoints3d[13],zjoints3d[13]),(xjoints3d[15],yjoints3d[15],zjoints3d[15]),False))
anglesr.append(180-tools.angle((xjoints3d[12],yjoints3d[12],zjoints3d[12]),(xjoints3d[14],yjoints3d[14],zjoints3d[14]),(xjoints3d[16],yjoints3d[16],zjoints3d[16]),False))
# static analysis
# save the important information:dis between ankles, as height, leg length
l_kn_ak.append(tools.get_distance((xjoints3d[12],yjoints3d[12],zjoints3d[12]),(xjoints3d[13],yjoints3d[13],zjoints3d[13])))
r_kn_ak.append(tools.get_distance((xjoints3d[9],yjoints3d[9],zjoints3d[9]),(xjoints3d[10],yjoints3d[10],zjoints3d[10])))
dak=(zjoints3d[10]-zjoints3d[13])
dkn=(zjoints3d[9]-zjoints3d[12])
akdis.append(dak)
kndis.append(dkn)
for p in range(17):
points3dx[p].append(xjoints3d[p])
points3dy[p].append(yjoints3d[p])
points3dz[p].append(zjoints3d[p])
points2dx[p].append(xjoints2d[p])
points2dy[p].append(yjoints2d[p])
points2ddx[p].append(xjoints2dd[p])
points2ddy[p].append(yjoints2dd[p])
v.release()
#b, a = signal.butter(8, 0.3, 'lowpass')
#anglesl = signal.filtfilt(b, a, anglesl)
#anglesr = signal.filtfilt(b, a, anglesr)
frames=range(frames[0],frames[1])
ax.plot(frames, anglesl)
ax2.plot(frames, anglesr, color='r')
data2d={}
data={}
data2dd={}
data2dd['frames']=frames
data2d['frames']=frames
data['frames']=frames
data['kangle_l']=anglesl
data['kangle_r']=anglesr
data['akdis']=akdis
data['kndis']=kndis
data['l_kn_ak']=l_kn_ak
data['r_kn_ak']=r_kn_ak
data['bad_frame']=bad_frame
j=['head','leye','reye','lear','rear','lsh','rsh','lel','rel','lwr','rwr','las','ras','lkn','rkn','lak','rak']
for p in range(17):
data['x_'+j[p]]=points3dx[p]
data['y_'+j[p]]=points3dy[p]
data['z_'+j[p]]=points3dz[p]
data2d['x_'+j[p]]=points2dx[p]
data2d['y_'+j[p]]=points2dy[p]
data2dd['x_'+j[p]]=points2ddx[p]
data2dd['y_'+j[p]]=points2ddy[p]
data=pd.DataFrame(data)
data2d=pd.DataFrame(data2d)
data2dd=pd.DataFrame(data2dd)
if frames[0]>250:
data.to_csv('testVideos'+'/test'+nb_video+'/'+number+'_PifPaf_joints_3DKinect_back.csv',encoding='gbk')
data2d.to_csv('testVideos'+'/test'+nb_video+'/'+number+'_PifPaf_joints_2DColor_back.csv',encoding='gbk')
data2dd.to_csv('testVideos'+'/test'+nb_video+'/'+number+'_PifPaf_joints_2DDepth_back.csv',encoding='gbk')
#data1=pd.DataFrame({'frame':frames, 'angle_left':anglesl, 'angle_right':anglesr})
#data1.to_csv('testVedios'+'/test'+nb_vedio+'/'+number+'_LCR-NET_angles_3DKinect_back.csv',encoding='gbk')
else:
data2dd.to_csv('testVideos'+'/test'+nb_video+'/'+number+'_PifPaf_joints_2DDepth_front.csv',encoding='gbk')
data2d.to_csv('testVideos'+'/test'+nb_video+'/'+number+'_PifPaf_joints_2DColor_front.csv',encoding='gbk')
data.to_csv('testVideos'+'/test'+nb_video+'/'+number+'_PifPaf_joints_3DKinect_front.csv',encoding='gbk')
def get_distance_from_target(self):
return tools.get_distance((self.unit.x, self.unit.y),
(self.unit.current_destination[0],
self.unit.current_destination[1]))
def get_close_entity(self, location, e_range=100):
for entity in self.get_unit_list():
distance = tools.get_distance(location, (entity.x, entity.y))
if distance < e_range:
return entity
return None
