def compute_dr_wrt(self, wrt):
if wrt not in (self.v, self.rt, self.t):
return
if wrt is self.t:
if not hasattr(self,
'_drt') or self._drt.shape[0] != self.v.r.size:
IS = np.arange(self.v.r.size)
JS = IS % 3
data = np.ones(len(IS))
self._drt = sp.csc_matrix((data, (IS, JS)))
return self._drt
if wrt is self.rt:
rot, rot_dr = cv2.Rodrigues(self.rt.r)
rot_dr = rot_dr.reshape((3, 3, 3))
dr = np.einsum('abc, zc -> zba', rot_dr, self.v.r).reshape((-1, 3))
return dr
if wrt is self.v:
rot = cv2.Rodrigues(self.rt.r)[0]
IS = np.repeat(np.arange(self.v.r.size), 3)
JS = np.repeat(np.arange(self.v.r.size).reshape((-1, 3)),
3,
axis=0)
data = np.vstack([rot for i in range(self.v.r.size / 3)])
result = sp.csc_matrix((data.ravel(), (IS.ravel(), JS.ravel())))
return result
def compute_dr_wrt(self, wrt):
if wrt not in [self.v, self.rt, self.t, self.f, self.c, self.k]:
return None
j = self.r_and_derivatives[1]
if wrt is self.rt:
return j[:, :3]
elif wrt is self.t:
return j[:, 3:6]
elif wrt is self.f:
return j[:, 6:8]
elif wrt is self.c:
return j[:, 8:10]
elif wrt is self.k:
return j[:, 10:10 + self.k.size]
elif wrt is self.v:
rot = cv2.Rodrigues(self.rt.r)[0]
data = np.asarray(j[:, 3:6].dot(rot), order='C').ravel()
IS = np.repeat(np.arange(self.v.r.size * 2 / 3), 3)
JS = np.asarray(np.repeat(np.arange(self.v.r.size).reshape(
(-1, 3)),
2,
axis=0),
order='C').ravel()
result = sp.csc_matrix((data, (IS, JS)))
return result
def draw_boundary_images(glf, glb, v, f, vpe, fpe, camera):
"""Assumes camera is set up correctly, and that glf has any texmapping on necessary."""
glf.Clear(GL_COLOR_BUFFER_BIT | GL_DEPTH_BUFFER_BIT)
glb.Clear(GL_COLOR_BUFFER_BIT | GL_DEPTH_BUFFER_BIT)
# Figure out which edges are on pairs of differently visible triangles
from opendr.geometry import TriNormals
tn = TriNormals(v, f).r.reshape((-1, 3))
campos = -cv2.Rodrigues(camera.rt.r)[0].T.dot(camera.t.r)
rays_to_verts = v.reshape((-1, 3)) - row(campos)
rays_to_faces = rays_to_verts[f[:, 0]] + rays_to_verts[
f[:, 1]] + rays_to_verts[f[:, 2]]
dps = np.sum(rays_to_faces * tn, axis=1)
dps = dps[fpe[:, 0]] * dps[fpe[:, 1]]
silhouette_edges = np.asarray(np.nonzero(dps <= 0)[0], np.uint32)
non_silhouette_edges = np.nonzero(dps > 0)[0]
lines_e = vpe[silhouette_edges]
lines_v = v
visibility = draw_edge_visibility(glb,
lines_v,
lines_e,
f,
hidden_wireframe=True)
shape = visibility.shape
visibility = visibility.ravel()
visible = np.nonzero(visibility.ravel() != 4294967295)[0]
visibility[visible] = silhouette_edges[visibility[visible]]
result = visibility.reshape(shape)
return result
def compute_vpe_boundary_idxs(v, f, camera, fpe):
# Figure out which edges are on pairs of differently visible triangles
from geometry import TriNormals
tn = TriNormals(v, f).r.reshape((-1, 3))
#ray = cv2.Rodrigues(camera.rt.r)[0].T[:,2]
campos = -cv2.Rodrigues(camera.rt.r)[0].T.dot(camera.t.r)
rays_to_verts = v.reshape((-1, 3)) - row(campos)
rays_to_faces = rays_to_verts[f[:, 0]] + rays_to_verts[
f[:, 1]] + rays_to_verts[f[:, 2]]
faces_invisible = np.sum(rays_to_faces * tn, axis=1)
dps = faces_invisible[fpe[:, 0]] * faces_invisible[fpe[:, 1]]
silhouette_edges = np.asarray(np.nonzero(dps <= 0)[0], np.uint32)
return silhouette_edges, faces_invisible < 0
def compute_r(self):
return (cv2.Rodrigues(self.rt.r)[0].dot(self.v.r.T) +
col(self.t.r)).T.copy()
def view_matrix(self):
R = cv2.Rodrigues(self.rt.r)[0]
return np.hstack((R, col(self.t.r)))
def compute_dr_wrt(self, wrt):
if wrt is self.rt:
return cv2.Rodrigues(self.rt.r)[1].T
def compute_r(self):
return cv2.Rodrigues(self.rt.r)[0]
