Skip to content

minor TypeError fix #73

New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Open
wants to merge 1 commit into
base: master
Choose a base branch
from
Open

minor TypeError fix #73

Changes from all commits
Commits
Show all changes
1 commit
Select commit
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
38 changes: 22 additions & 16 deletions lib/object_detector.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -305,27 +305,33 @@ def forward(self, x, im_sizes, image_offset,
od_box_priors = rois[:, 1:]

if (not self.training and not self.mode == 'gtbox') or self.mode in ('proposals', 'refinerels'):
nms_inds, nms_scores, nms_preds, nms_boxes_assign, nms_boxes, nms_imgs = self.nms_boxes(
nms_res = self.nms_boxes(
od_obj_dists,
rois,
od_box_deltas, im_sizes,
)
im_inds = nms_imgs + image_offset
obj_dists = od_obj_dists[nms_inds]
obj_fmap = obj_fmap[nms_inds]
box_deltas = od_box_deltas[nms_inds]
box_priors = nms_boxes[:, 0]

if self.training and not self.mode == 'gtbox':
# NOTE: If we're doing this during training, we need to assign labels here.
pred_to_gtbox = bbox_overlaps(box_priors, gt_boxes).data
pred_to_gtbox[im_inds.data[:, None] != gt_classes.data[None, :, 0]] = 0.0

max_overlaps, argmax_overlaps = pred_to_gtbox.max(1)
rm_obj_labels = gt_classes[:, 1][argmax_overlaps]
rm_obj_labels[max_overlaps < 0.5] = 0

if nms_res is None:
return None
else:
rm_obj_labels = None
nms_inds, nms_scores, nms_preds, nms_boxes_assign, nms_boxes, nms_imgs = nms_res

im_inds = nms_imgs + image_offset
obj_dists = od_obj_dists[nms_inds]
obj_fmap = obj_fmap[nms_inds]
box_deltas = od_box_deltas[nms_inds]
box_priors = nms_boxes[:, 0]

if self.training and not self.mode == 'gtbox':
# NOTE: If we're doing this during training, we need to assign labels here.
pred_to_gtbox = bbox_overlaps(box_priors, gt_boxes).data
pred_to_gtbox[im_inds.data[:, None] != gt_classes.data[None, :, 0]] = 0.0

max_overlaps, argmax_overlaps = pred_to_gtbox.max(1)
rm_obj_labels = gt_classes[:, 1][argmax_overlaps]
rm_obj_labels[max_overlaps < 0.5] = 0
else:
rm_obj_labels = None
else:
im_inds = rois[:, 0].long().contiguous() + image_offset
nms_scores = None
Expand Down