def get_scene_states(self, xabs):
"""
functions get scene_states (scene memories) for each current pedestrian
"""
nonlinear_grid_h0 = torch.zeros(
(self.num_layers, self.batch_size, self.rnn_size))
nonlinear_grid_c0 = torch.zeros(
(self.num_layers, self.batch_size, self.rnn_size))
if (self.use_cuda):
nonlinear_grid_h0, nonlinear_grid_c0 = nonlinear_grid_h0.cuda(
), nonlinear_grid_c0.cuda()
for pid in range(self.batch_size):
# For each ped in current frame
gid = get_grid_cell_index(xabs[pid].cpu().detach().numpy(),
self.num_grid_cells) # current grid-cell
sid = get_sub_grid_cell_index(
xabs[pid].cpu().detach().numpy(), self.num_grid_cells,
self.num_sub_grids) # current grid-cell
if (gid in self.scene_info["nonlinear_grid_list"][self.dataset_id]
and sid in self.scene_info["nonlinear_subgrid_maps"][
self.dataset_id][gid]):
# if current grid-cells is in nonlinear grid list then extract it to use
nonlinear_grid_h0[:, pid, :] = self.scene_states[
"nonlinear_h0_list"][self.dataset_id][gid]
nonlinear_grid_c0[:, pid, :] = self.scene_states[
"nonlinear_c0_list"][self.dataset_id][gid]
self.scene_grid_h0 = nonlinear_grid_h0.view(-1, self.batch_size,
self.rnn_size)
self.scene_grid_c0 = nonlinear_grid_c0.view(-1, self.batch_size,
self.rnn_size)
if (self.use_cuda):
self.scene_grid_h0, self.scene_grid_c0 = self.scene_grid_h0.cuda(
), self.scene_grid_c0.cuda()
def get_scene_states(self, xabs):
"""
functions get scene_states (scene memories) for each current pedestrian
"""
common_grid_h0 = torch.zeros(
(self.num_layers, self.batch_size, self.rnn_size))
common_grid_c0 = torch.zeros(
(self.num_layers, self.batch_size, self.rnn_size))
if (self.use_cuda):
common_grid_h0, common_grid_c0 = common_grid_h0.cuda(
), common_grid_c0.cuda()
for pid in range(self.batch_size):
# For each ped in current frame
gid = get_grid_cell_index(xabs[pid].detach().numpy(),
self.num_grid_cells) # current grid-cell
if (gid in self.scene_info["common_grid_list"][self.dataset_id]):
# if current grid-cells is in common grid list then extract it to use
common_grid_h0[:,
pid, :] = self.scene_states["common_h0_list"][
self.dataset_id][gid]
common_grid_c0[:,
pid, :] = self.scene_states["common_c0_list"][
self.dataset_id][gid]
self.scene_grid_h0 = common_grid_h0.view(-1, self.batch_size,
self.rnn_size)
self.scene_grid_c0 = common_grid_c0.view(-1, self.batch_size,
self.rnn_size)
if (self.use_cuda):
self.scene_grid_h0, self.scene_grid_c0 = self.scene_grid_h0.cuda(
), self.scene_grid_c0.cuda()
def get_scene_states(self, xabs):
"""
functions get scene_states (scene memories) for each current pedestrian
"""
scene_grid_h0 = torch.zeros(
(self.num_layers, self.batch_size, self.rnn_size))
scene_grid_c0 = torch.zeros(
(self.num_layers, self.batch_size, self.rnn_size))
if (self.use_cuda):
scene_grid_h0, scene_grid_c0 = scene_grid_h0.cuda(
), scene_grid_c0.cuda()
for pid in range(self.batch_size):
# For each ped in current frame
gid = get_grid_cell_index(xabs[pid].detach().numpy(),
self.num_grid_cells) # current grid-cell
scene_grid_h0[:, pid, :] = self.scene_states["scene_h0_list"][
self.dataset_id][gid]
scene_grid_c0[:, pid, :] = self.scene_states["scene_c0_list"][
self.dataset_id][gid]
self.scene_grid_h0 = scene_grid_h0.view(-1, self.batch_size,
self.rnn_size)
self.scene_grid_c0 = scene_grid_c0.view(-1, self.batch_size,
self.rnn_size)
if (self.use_cuda):
self.scene_grid_h0, self.scene_grid_c0 = self.scene_grid_h0.cuda(
), self.scene_grid_c0.cuda()
def update_scene_states(self, xabs):
"""
functions update scene_states (scene memories)
"""
for pid in range(self.batch_size):
# For each ped in current frame
gid = get_grid_cell_index(xabs[pid].detach().numpy(),
self.num_grid_cells) # current grid-cell
self.scene_states["scene_h0_list"][self.dataset_id][
gid] = self.scene_grid_h0[:, pid, :].data.clone()
self.scene_states["scene_c0_list"][self.dataset_id][
gid] = self.scene_grid_c0[:, pid, :].data.clone()
def update_scene_states(self, xabs):
"""
functions update scene_states (scene memories)
"""
for pid in range(self.batch_size):
# For each ped in current frame
gid = get_grid_cell_index(xabs[pid].detach().numpy(), self.num_grid_cells) # current grid-cell
sid = get_sub_grid_cell_index(xabs[pid].detach().numpy(), self.num_grid_cells, self.num_sub_grids)
if(gid in self.scene_info["common_grid_list"][self.dataset_id] \
and sid in self.scene_info["common_sub_grids_maps"][self.dataset_id][gid]):
# if grid-cell is in common_grid_list then update
self.scene_states["common_h0_list"][self.dataset_id][gid] = self.scene_grid_h0[:,pid,:].data.clone()
self.scene_states["common_c0_list"][self.dataset_id][gid] = self.scene_grid_c0[:,pid,:].data.clone()