Fix bounding box sorting from dict to list

micro_sam/training/util.py

@@ -2,7 +2,6 @@
 from typing import List, Optional, Union
 
 import numpy as np
-import torch
 
 from ..prompt_generators import PointAndBoxPromptGenerator
 from ..util import get_centers_and_bounding_boxes, get_sam_model, segmentation_to_one_hot, _get_device
@@ -86,8 +85,8 @@ def _get_prompt_lists(self, gt, n_samples, prompt_generator):
             sampled_cell_ids = np.random.choice(cell_ids, size=min(n_samples, len(cell_ids)), replace=False)
             sampled_cell_ids = np.sort(sampled_cell_ids)
 
-            # only keep the bounding boxes for sampled cell ids
-            bbox_coordinates = [bbox_coordinates[sampled_id] for sampled_id in sampled_cell_ids]
+        # only keep the bounding boxes for sampled cell ids
+        bbox_coordinates = [bbox_coordinates[sampled_id] for sampled_id in sampled_cell_ids]
 
         # convert the gt to the one-hot-encoded masks for the sampled cell ids
         object_masks = segmentation_to_one_hot(gt, None if n_samples is None else sampled_cell_ids)