def show_paf(img,paf,stride = 5,thres=0.1):
"""
@param img: ndarry, HxWx3
@param paf: ndarry, HxWxN
"""
paf = transform.rescale(paf,img.shape[0]/paf.shape[0])
h,w,n = paf.shape
mask = (paf**2).reshape(h,w,n/2,2).sum(axis=3).sum(axis=2)<thres
paf[mask] = 0
# img_size = img.shape[:2]
X,Y = np.meshgrid(np.arange(0,w),np.arange(0,h))
plt.imshow(img, alpha=0.5)
res = plt.quiver( X[::stride,::stride],
Y[::stride,::stride],
-paf[::stride,::stride,::2].sum(axis=2),
paf[::stride,::stride,1::2].sum(axis=2),
scale=20,
units='width', headaxislength=0.01,
alpha=.8,
width=0.001,
color='r')
return res
plt.gca().invert_yaxis()
plt.subplot(4,1,2)
plt.plot(posT[:,0],posT[:,1],'.b',label='GPU')
plt.gca().invert_yaxis()
plt.legend()
plt.subplot(4,1,3)
plt.plot(my_dict['CPU_results'][0,:],my_dict['CPU_results'][1,:],'.r',label='CPU')
plt.plot(posT[:,0],posT[:,1],'.b',label='GPU')
plt.gca().invert_yaxis()
plt.legend()
plt.subplot(4,1,4)
for i in range(0,N,32):
plt.plot(posH[i::N,0],posH[i::N,1],'r')
# plt.plot(posH[i::N,0],posH[i::N,1],'r')
# plt.plot(posH[i,0],posH[i,1],'bo')
plt.gca().invert_yaxis()
plt.legend()
plt.figure()
# plt.plot(v[:,0],v[:,1],'.b',label='GPU velocities')
plt.quiver(my_dict['pts_at_0'][:,0][::10],
my_dict['pts_at_0'][:,1][::10],
v[:,0][::10],v[:,1][::10])
plt.gca().invert_yaxis()
plt.axis('scaled')
plt.legend()
pylab.show()
#raw_input()
def quiver(self,x,v,scale,ds=16,color='k',negate_vy=False,pivot='middle',
head=True,width=None):
"""
If width is None, its its value will be dictated by the value of
head
"""
if head:
headlength=5
headwidth=3
headaxislength=4.5
if width is None:
width=.005
else:
headlength=0
headwidth=0
headaxislength=0
if width is None:
width=.003
if x is None:
raise ValueError
# if x is None:
# x=self.xx
# y=self.yy
# if x.size != v[:,0].size:
# x=self.x_img
# y=self.y_img
#
# else:
# if x.ndim != 2:
# raise ValueError(x.shape)
# if x.shape[1]!=2:
# raise ValueError(x.shape)
#
# x,y=x[:,0].copy(),x[:,1].copy()
# if x.size != v[:,0].size:
# raise ValueError(x.shape,v.shape)
if x.size != v.size:
raise ValueError(x.shape,v.shape)
if v.ndim != 2:
raise ValueError(v.shape)
if v.shape[1]!=2:
raise ValueError(v.shape)
if x.shape != v.shape:
if x.ndim !=3 or x.shape[0]!=2:
raise ValueError(x.shape)
# x = np.asarray([x[0].flatten(),x[1].flatten()]).T
v = np.asarray([v.cpu[:,0].reshape(x.shape[1],x.shape[2]),
v.cpu[:,1].reshape(x.shape[1],x.shape[2])])
if x.shape != v.shape:
raise ValueError(x.shape,v.shape)
# if x.ndim != 2:
# raise ValueError(x.shape)
# if y.ndim != 2:
# raise ValueError(x.shape)
# try:
# vx = v[:,0].reshape(x.shape)
# vy = v[:,1].reshape(x.shape)
# except:
# raise ValueError(v.shape,x.shape)
# if x.shape[1]!=2:
# raise NotImplementedError(x.shape)
# if v.shape[1]!=2:
# raise NotImplementedError(x.shape)
if x.ndim !=3 and x.shape[1]!=2:
raise ValueError(x.shape)
if v.ndim !=3 and v.shape[1]!=2:
raise ValueError(v.shape)
# _x,_y = x.T
# vx,vy = v.T
if x.ndim == 2:
_x,_y = x.T
_u,_v = v.T
else:
_x,_y = x
_u,_v = v
if negate_vy:
_v = -_v
# print scale,ds
# 1/0
if _x.ndim==2:
plt.quiver(_x[::ds,::ds],_y[::ds,::ds],_u[::ds,::ds],_v[::ds,::ds],
angles='xy', scale_units='xy',scale=scale,
pivot=pivot,
color=color,
headlength=headlength,
headwidth=headwidth,
headaxislength=headaxislength,
width=width
)
else:
plt.quiver(_x[::ds],_y[::ds],_u[::ds],_v[::ds],
angles='xy', scale_units='xy',scale=scale,
pivot=pivot,
color=color,
headlength=headlength,
headwidth=headwidth,
headaxislength=headaxislength,
width=width
)
plt.subplot(4, 1, 2)
plt.plot(posT[:, 0], posT[:, 1], '.b', label='GPU')
plt.gca().invert_yaxis()
plt.legend()
plt.subplot(4, 1, 3)
plt.plot(my_dict['CPU_results'][0, :],
my_dict['CPU_results'][1, :],
'.r',
label='CPU')
plt.plot(posT[:, 0], posT[:, 1], '.b', label='GPU')
plt.gca().invert_yaxis()
plt.legend()
plt.subplot(4, 1, 4)
for i in range(0, N, 32):
plt.plot(posH[i::N, 0], posH[i::N, 1], 'r')
# plt.plot(posH[i::N,0],posH[i::N,1],'r')
# plt.plot(posH[i,0],posH[i,1],'bo')
plt.gca().invert_yaxis()
plt.legend()
plt.figure()
# plt.plot(v[:,0],v[:,1],'.b',label='GPU velocities')
plt.quiver(my_dict['pts_at_0'][:, 0][::10],
my_dict['pts_at_0'][:, 1][::10], v[:, 0][::10], v[:, 1][::10])
plt.gca().invert_yaxis()
plt.axis('scaled')
plt.legend()
pylab.show()
#raw_input()
def quiver(self,
x,
v,
scale,
ds=16,
color='k',
negate_vy=False,
pivot='middle',
head=True,
width=None):
"""
If width is None, its its value will be dictated by the value of
head
"""
if head:
headlength = 5
headwidth = 3
headaxislength = 4.5
if width is None:
width = .005
else:
headlength = 0
headwidth = 0
headaxislength = 0
if width is None:
width = .003
if x is None:
raise ValueError
# if x is None:
# x=self.xx
# y=self.yy
# if x.size != v[:,0].size:
# x=self.x_img
# y=self.y_img
#
# else:
# if x.ndim != 2:
# raise ValueError(x.shape)
# if x.shape[1]!=2:
# raise ValueError(x.shape)
#
# x,y=x[:,0].copy(),x[:,1].copy()
# if x.size != v[:,0].size:
# raise ValueError(x.shape,v.shape)
if x.size != v.size:
raise ValueError(x.shape, v.shape)
if v.ndim != 2:
raise ValueError(v.shape)
if v.shape[1] != 2:
raise ValueError(v.shape)
if x.shape != v.shape:
if x.ndim != 3 or x.shape[0] != 2:
raise ValueError(x.shape)
# x = np.asarray([x[0].flatten(),x[1].flatten()]).T
v = np.asarray([
v.cpu[:, 0].reshape(x.shape[1], x.shape[2]),
v.cpu[:, 1].reshape(x.shape[1], x.shape[2])
])
if x.shape != v.shape:
raise ValueError(x.shape, v.shape)
# if x.ndim != 2:
# raise ValueError(x.shape)
# if y.ndim != 2:
# raise ValueError(x.shape)
# try:
# vx = v[:,0].reshape(x.shape)
# vy = v[:,1].reshape(x.shape)
# except:
# raise ValueError(v.shape,x.shape)
# if x.shape[1]!=2:
# raise NotImplementedError(x.shape)
# if v.shape[1]!=2:
# raise NotImplementedError(x.shape)
if x.ndim != 3 and x.shape[1] != 2:
raise ValueError(x.shape)
if v.ndim != 3 and v.shape[1] != 2:
raise ValueError(v.shape)
# _x,_y = x.T
# vx,vy = v.T
if x.ndim == 2:
_x, _y = x.T
_u, _v = v.T
else:
_x, _y = x
_u, _v = v
if negate_vy:
_v = -_v
# print scale,ds
# 1/0
if _x.ndim == 2:
plt.quiver(_x[::ds, ::ds],
_y[::ds, ::ds],
_u[::ds, ::ds],
_v[::ds, ::ds],
angles='xy',
scale_units='xy',
scale=scale,
pivot=pivot,
color=color,
headlength=headlength,
headwidth=headwidth,
headaxislength=headaxislength,
width=width)
else:
plt.quiver(_x[::ds],
_y[::ds],
_u[::ds],
_v[::ds],
angles='xy',
scale_units='xy',
scale=scale,
pivot=pivot,
color=color,
headlength=headlength,
headwidth=headwidth,
headaxislength=headaxislength,
width=width)
