style(formatting): box_utils/ssd_target_transform

Author: zjZSTU

py/ssd/data/transforms/ssd_target_transform.py

@@ -25,8 +25,9 @@ def __call__(self, gt_boxes, gt_labels):
             gt_boxes = torch.from_numpy(gt_boxes)
         if type(gt_labels) is np.ndarray:
             gt_labels = torch.from_numpy(gt_labels)
-        boxes, labels = box_utils.assign_priors(gt_boxes, gt_labels,
-                                                self.corner_form_priors, self.iou_threshold)
+        # boxes: [num_priors, 4] 每个先验框对应的标注框坐标
+        # labels: [num_priors] 每个先验框对应标签
+        boxes, labels = box_utils.assign_priors(gt_boxes, gt_labels, self.corner_form_priors, self.iou_threshold)
         boxes = box_utils.corner_form_to_center_form(boxes)
         locations = box_utils.convert_boxes_to_locations(boxes, self.center_form_priors, self.center_variance,
                                                          self.size_variance)

py/ssd/utils/box_utils.py

@@ -11,8 +11,7 @@
 import math
 
 
-def convert_locations_to_boxes(locations, priors, center_variance,
-                               size_variance):
+def convert_locations_to_boxes(locations, priors, center_variance, size_variance):
     """Convert regressional location results of SSD into boxes in the form of (center_x, center_y, h, w).
 
     The conversion: