Fix variable naming error

zhiqwang · Oct 17, 2021 · 261590f · 261590f
1 parent fab48d7
commit 261590f
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Showing 2 changed files with 13 additions and 13 deletions.
diff --git a/yolort/models/_utils.py b/yolort/models/_utils.py
@@ -63,9 +63,9 @@ def decode_single(
         anchors_tupe (Tensor, Tensor, Tensor): reference boxes.
     """
 
-    pred_wh = (rel_codes[..., 0:2] * 2.0 + anchors_tuple[0]) * anchors_tuple[1]  # wh
-    pred_xy = (rel_codes[..., 2:4] * 2) ** 2 * anchors_tuple[2]  # xy
-    pred_boxes = torch.cat([pred_wh, pred_xy], dim=1)
+    pred_xy = (rel_codes[..., 0:2] * 2.0 + anchors_tuple[0]) * anchors_tuple[1]  # xy
+    pred_wh = (rel_codes[..., 2:4] * 2) ** 2 * anchors_tuple[2]  # wh
+    pred_boxes = torch.cat([pred_xy, pred_wh], dim=1)
     pred_boxes = box_convert(pred_boxes, in_fmt="cxcywh", out_fmt="xyxy")
 
     return pred_boxes

diff --git a/yolort/models/anchor_utils.py b/yolort/models/anchor_utils.py
@@ -17,43 +17,43 @@ def __init__(
         self.strides = strides
         self.anchor_grids = anchor_grids
 
-    def set_wh_weights(
+    def set_xy_weights(
         self,
         grid_sizes: List[List[int]],
         dtype: torch.dtype = torch.float32,
         device: torch.device = torch.device("cpu"),
     ) -> Tensor:
 
-        wh_weights = []
+        xy_weights = []
 
         for size, stride in zip(grid_sizes, self.strides):
             grid_height, grid_width = size
             stride = torch.as_tensor([stride], dtype=dtype, device=device)
             stride = stride.view(-1, 1)
             stride = stride.repeat(1, grid_height * grid_width * self.num_anchors)
             stride = stride.reshape(-1, 1)
-            wh_weights.append(stride)
+            xy_weights.append(stride)
 
-        return torch.cat(wh_weights)
+        return torch.cat(xy_weights)
 
-    def set_xy_weights(
+    def set_wh_weights(
         self,
         grid_sizes: List[List[int]],
         dtype: torch.dtype = torch.float32,
         device: torch.device = torch.device("cpu"),
     ) -> Tensor:
 
-        xy_weights = []
+        wh_weights = []
 
         for size, anchor_grid in zip(grid_sizes, self.anchor_grids):
             grid_height, grid_width = size
             anchor_grid = torch.as_tensor(anchor_grid, dtype=dtype, device=device)
             anchor_grid = anchor_grid.view(-1, 2)
             anchor_grid = anchor_grid.repeat(1, grid_height * grid_width)
             anchor_grid = anchor_grid.reshape(-1, 2)
-            xy_weights.append(anchor_grid)
+            wh_weights.append(anchor_grid)
 
-        return torch.cat(xy_weights)
+        return torch.cat(wh_weights)
 
     def grid_anchors(
         self,
@@ -91,8 +91,8 @@ def forward(self, feature_maps: List[Tensor]) -> Tuple[Tensor, Tensor, Tensor]:
         grid_sizes = list([feature_map.shape[-2:] for feature_map in feature_maps])
         dtype, device = feature_maps[0].dtype, feature_maps[0].device
 
-        wh_weights = self.set_wh_weights(grid_sizes, dtype, device)
         xy_weights = self.set_xy_weights(grid_sizes, dtype, device)
+        wh_weights = self.set_wh_weights(grid_sizes, dtype, device)
         anchors = self.grid_anchors(grid_sizes, dtype, device)
 
-        return anchors, wh_weights, xy_weights
+        return anchors, xy_weights, wh_weights