in sam2/sam2_video_predictor.py [0:0]
def _get_empty_mask_ptr(self, inference_state, frame_idx):
"""Get a dummy object pointer based on an empty mask on the current frame."""
# A dummy (empty) mask with a single object
batch_size = 1
mask_inputs = torch.zeros(
(batch_size, 1, self.image_size, self.image_size),
dtype=torch.float32,
device=inference_state["device"],
)
# Retrieve correct image features
(
_,
_,
current_vision_feats,
current_vision_pos_embeds,
feat_sizes,
) = self._get_image_feature(inference_state, frame_idx, batch_size)
# Feed the empty mask and image feature above to get a dummy object pointer
current_out = self.track_step(
frame_idx=frame_idx,
is_init_cond_frame=True,
current_vision_feats=current_vision_feats,
current_vision_pos_embeds=current_vision_pos_embeds,
feat_sizes=feat_sizes,
point_inputs=None,
mask_inputs=mask_inputs,
output_dict={},
num_frames=inference_state["num_frames"],
track_in_reverse=False,
run_mem_encoder=False,
prev_sam_mask_logits=None,
)
return current_out["obj_ptr"]