dummy test

Author: datumbox

torchvision/models/detection/rpn.py

@@ -163,7 +163,7 @@ def __init__(self,
         self._pre_nms_top_n = pre_nms_top_n
         self._post_nms_top_n = post_nms_top_n
         self.nms_thresh = nms_thresh
-        self.score_thresh = score_thresh
+        self.score_thresh = float('-inf')
         self.min_size = 1e-3
 
     def pre_nms_top_n(self):
@@ -252,7 +252,7 @@ def filter_proposals(self, proposals, objectness, image_shapes, num_anchors_per_
         levels = levels[batch_idx, top_n_idx]
         proposals = proposals[batch_idx, top_n_idx]
 
-        objectness_prob = F.sigmoid(objectness)
+        objectness_prob = objectness#F.sigmoid(objectness)
 
         final_boxes = []
         final_scores = []
@@ -264,7 +264,7 @@ def filter_proposals(self, proposals, objectness, image_shapes, num_anchors_per_
             boxes, scores, lvl = boxes[keep], scores[keep], lvl[keep]
 
             # remove low scoring boxes
-            keep = torch.where(scores > self.score_thresh)[0]
+            keep = torch.where(scores >= self.score_thresh)[0]
             boxes, scores, lvl = boxes[keep], scores[keep], lvl[keep]
 
             # non-maximum suppression, independently done per level