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]