def init_target_boxes(self):
self.classifier_target_box = self.get_iounet_box(self.pos, self.target_sz, self.pos.round(), self.target_scale)
init_target_boxes = TensorList()
for T in self.transforms:
init_target_boxes.append(self.classifier_target_box + torch.Tensor([T.shift[1], T.shift[0], 0, 0]))
init_target_boxes = torch.cat(init_target_boxes.view(1, 4), 0).to(self.params.device)
self.target_boxes = init_target_boxes.new_zeros(self.params.sample_memory_size, 4)
self.target_boxes[:init_target_boxes.shape[0],:] = init_target_boxes
return init_target_boxes
def init_target_boxes(self):
"""Get the target bounding boxes for the initial augmented samples."""
self.classifier_target_box = self.get_training_box(self.pos, self.target_sz, self.init_sample_pos, self.init_sample_scale)
init_target_boxes = TensorList()
for T in self.transforms:
init_target_boxes.append(self.classifier_target_box + torch.Tensor([T.shift[1], T.shift[0], 0, 0]))
init_target_boxes = torch.cat(init_target_boxes.view(1, 4), 0).to(self.params.device)
self.target_boxes = init_target_boxes.new_zeros(self.params.sample_memory_size, 4)
self.target_boxes[:init_target_boxes.shape[0],:] = init_target_boxes
self.target_boxes_cls_72 = self.target_boxes.clone()
self.target_boxes_cls_18 = self.target_boxes.clone()
self.target_boxes_reg_72 = self.target_boxes.clone()
return init_target_boxes