From c01ab3b1cb850eb6757447678888b0a089e4f4ff Mon Sep 17 00:00:00 2001
From: Wenwei Zhang <40779233+ZwwWayne@users.noreply.github.com>
Date: Fri, 29 Nov 2019 11:22:12 +0800
Subject: [PATCH] fix scale factor bug (#1730)
* fix scale factor bug
* reformat
* clean code
---
mmdet/models/bbox_heads/bbox_head.py | 4 +++-
mmdet/models/detectors/test_mixins.py | 5 +++++
mmdet/models/mask_heads/fcn_mask_head.py | 2 ++
3 files changed, 10 insertions(+), 1 deletion(-)
diff --git a/mmdet/models/bbox_heads/bbox_head.py b/mmdet/models/bbox_heads/bbox_head.py
index 6188fb8..2e983ff 100644
--- a/mmdet/models/bbox_heads/bbox_head.py
+++ b/mmdet/models/bbox_heads/bbox_head.py
@@ -155,7 +155,9 @@ class BBoxHead(nn.Module):
if isinstance(scale_factor, float):
bboxes /= scale_factor
else:
- bboxes /= torch.from_numpy(scale_factor).to(bboxes.device)
+ scale_factor = torch.from_numpy(scale_factor).to(bboxes.device)
+ bboxes = (bboxes.view(bboxes.size(0), -1, 4) /
+ scale_factor).view(bboxes.size()[0], -1)
if cfg is None:
return bboxes, scores
diff --git a/mmdet/models/detectors/test_mixins.py b/mmdet/models/detectors/test_mixins.py
index 1abd609..05b2081 100644
--- a/mmdet/models/detectors/test_mixins.py
+++ b/mmdet/models/detectors/test_mixins.py
@@ -1,3 +1,5 @@
+import torch
+
from mmdet.core import (bbox2roi, bbox_mapping, merge_aug_bboxes,
merge_aug_masks, merge_aug_proposals, multiclass_nms)
@@ -114,6 +116,9 @@ class MaskTestMixin(object):
else:
# if det_bboxes is rescaled to the original image size, we need to
# rescale it back to the testing scale to obtain RoIs.
+ if rescale and not isinstance(scale_factor, float):
+ scale_factor = torch.from_numpy(scale_factor).to(
+ det_bboxes.device)
_bboxes = (
det_bboxes[:, :4] * scale_factor if rescale else det_bboxes)
mask_rois = bbox2roi([_bboxes])
diff --git a/mmdet/models/mask_heads/fcn_mask_head.py b/mmdet/models/mask_heads/fcn_mask_head.py
index f25aa17..f9dafcd 100644
--- a/mmdet/models/mask_heads/fcn_mask_head.py
+++ b/mmdet/models/mask_heads/fcn_mask_head.py
@@ -159,6 +159,8 @@ class FCNMaskHead(nn.Module):
scale_factor = 1.0
for i in range(bboxes.shape[0]):
+ if not isinstance(scale_factor, (float, np.ndarray)):
+ scale_factor = scale_factor.cpu().numpy()
bbox = (bboxes[i, :] / scale_factor).astype(np.int32)
label = labels[i]
w = max(bbox[2] - bbox[0] + 1, 1)
--
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