From f1d06cdc70a81fbeee219f7c99654c319131ab8a Mon Sep 17 00:00:00 2001
From: Kai Chen <chenkaidev@gmail.com>
Date: Wed, 13 Feb 2019 20:23:39 +0800
Subject: [PATCH] support gt_bboxes_ignore for anchor heads
---
mmdet/core/anchor/anchor_target.py | 11 ++++++++---
mmdet/models/anchor_heads/anchor_head.py | 11 +++++++++--
mmdet/models/anchor_heads/rpn_head.py | 18 +++++++++++++++---
mmdet/models/anchor_heads/ssd_head.py | 11 +++++++++--
mmdet/models/detectors/cascade_rcnn.py | 5 +++--
mmdet/models/detectors/rpn.py | 9 +++++++--
mmdet/models/detectors/single_stage.py | 10 ++++++++--
mmdet/models/detectors/two_stage.py | 7 +++++--
8 files changed, 64 insertions(+), 18 deletions(-)
diff --git a/mmdet/core/anchor/anchor_target.py b/mmdet/core/anchor/anchor_target.py
index 2dae831..7a5bf4e 100644
--- a/mmdet/core/anchor/anchor_target.py
+++ b/mmdet/core/anchor/anchor_target.py
@@ -11,6 +11,7 @@ def anchor_target(anchor_list,
target_means,
target_stds,
cfg,
+ gt_bboxes_ignore_list=None,
gt_labels_list=None,
label_channels=1,
sampling=True,
@@ -41,6 +42,8 @@ def anchor_target(anchor_list,
valid_flag_list[i] = torch.cat(valid_flag_list[i])
# compute targets for each image
+ if gt_bboxes_ignore_list is None:
+ gt_bboxes_ignore_list = [None for _ in range(num_imgs)]
if gt_labels_list is None:
gt_labels_list = [None for _ in range(num_imgs)]
(all_labels, all_label_weights, all_bbox_targets, all_bbox_weights,
@@ -49,6 +52,7 @@ def anchor_target(anchor_list,
anchor_list,
valid_flag_list,
gt_bboxes_list,
+ gt_bboxes_ignore_list,
gt_labels_list,
img_metas,
target_means=target_means,
@@ -90,6 +94,7 @@ def images_to_levels(target, num_level_anchors):
def anchor_target_single(flat_anchors,
valid_flags,
gt_bboxes,
+ gt_bboxes_ignore,
gt_labels,
img_meta,
target_means,
@@ -108,11 +113,11 @@ def anchor_target_single(flat_anchors,
if sampling:
assign_result, sampling_result = assign_and_sample(
- anchors, gt_bboxes, None, None, cfg)
+ anchors, gt_bboxes, gt_bboxes_ignore, None, cfg)
else:
bbox_assigner = build_assigner(cfg.assigner)
- assign_result = bbox_assigner.assign(anchors, gt_bboxes, None,
- gt_labels)
+ assign_result = bbox_assigner.assign(anchors, gt_bboxes,
+ gt_bboxes_ignore, gt_labels)
bbox_sampler = PseudoSampler()
sampling_result = bbox_sampler.sample(assign_result, anchors,
gt_bboxes)
diff --git a/mmdet/models/anchor_heads/anchor_head.py b/mmdet/models/anchor_heads/anchor_head.py
index 57a7d64..d3ab2d2 100644
--- a/mmdet/models/anchor_heads/anchor_head.py
+++ b/mmdet/models/anchor_heads/anchor_head.py
@@ -169,8 +169,14 @@ class AnchorHead(nn.Module):
avg_factor=num_total_samples)
return loss_cls, loss_reg
- def loss(self, cls_scores, bbox_preds, gt_bboxes, gt_labels, img_metas,
- cfg):
+ def loss(self,
+ cls_scores,
+ bbox_preds,
+ gt_bboxes,
+ gt_labels,
+ img_metas,
+ cfg,
+ gt_bboxes_ignore=None):
featmap_sizes = [featmap.size()[-2:] for featmap in cls_scores]
assert len(featmap_sizes) == len(self.anchor_generators)
@@ -186,6 +192,7 @@ class AnchorHead(nn.Module):
self.target_means,
self.target_stds,
cfg,
+ gt_bboxes_ignore_list=gt_bboxes_ignore,
gt_labels_list=gt_labels,
label_channels=label_channels,
sampling=sampling)
diff --git a/mmdet/models/anchor_heads/rpn_head.py b/mmdet/models/anchor_heads/rpn_head.py
index b913fc7..fe9d5c3 100644
--- a/mmdet/models/anchor_heads/rpn_head.py
+++ b/mmdet/models/anchor_heads/rpn_head.py
@@ -34,9 +34,21 @@ class RPNHead(AnchorHead):
rpn_bbox_pred = self.rpn_reg(x)
return rpn_cls_score, rpn_bbox_pred
- def loss(self, cls_scores, bbox_preds, gt_bboxes, img_metas, cfg):
- losses = super(RPNHead, self).loss(cls_scores, bbox_preds, gt_bboxes,
- None, img_metas, cfg)
+ def loss(self,
+ cls_scores,
+ bbox_preds,
+ gt_bboxes,
+ img_metas,
+ cfg,
+ gt_bboxes_ignore=None):
+ losses = super(RPNHead, self).loss(
+ cls_scores,
+ bbox_preds,
+ gt_bboxes,
+ None,
+ img_metas,
+ cfg,
+ gt_bboxes_ignore=gt_bboxes_ignore)
return dict(
loss_rpn_cls=losses['loss_cls'], loss_rpn_reg=losses['loss_reg'])
diff --git a/mmdet/models/anchor_heads/ssd_head.py b/mmdet/models/anchor_heads/ssd_head.py
index ed1b27b..1f704f7 100644
--- a/mmdet/models/anchor_heads/ssd_head.py
+++ b/mmdet/models/anchor_heads/ssd_head.py
@@ -130,8 +130,14 @@ class SSDHead(AnchorHead):
avg_factor=num_total_samples)
return loss_cls[None], loss_reg
- def loss(self, cls_scores, bbox_preds, gt_bboxes, gt_labels, img_metas,
- cfg):
+ def loss(self,
+ cls_scores,
+ bbox_preds,
+ gt_bboxes,
+ gt_labels,
+ img_metas,
+ cfg,
+ gt_bboxes_ignore=None):
featmap_sizes = [featmap.size()[-2:] for featmap in cls_scores]
assert len(featmap_sizes) == len(self.anchor_generators)
@@ -145,6 +151,7 @@ class SSDHead(AnchorHead):
self.target_means,
self.target_stds,
cfg,
+ gt_bboxes_ignore_list=gt_bboxes_ignore,
gt_labels_list=gt_labels,
label_channels=1,
sampling=False,
diff --git a/mmdet/models/detectors/cascade_rcnn.py b/mmdet/models/detectors/cascade_rcnn.py
index 705a078..6df9e22 100644
--- a/mmdet/models/detectors/cascade_rcnn.py
+++ b/mmdet/models/detectors/cascade_rcnn.py
@@ -109,8 +109,8 @@ class CascadeRCNN(BaseDetector, RPNTestMixin):
img,
img_meta,
gt_bboxes,
- gt_bboxes_ignore,
gt_labels,
+ gt_bboxes_ignore=None,
gt_masks=None,
proposals=None):
x = self.extract_feat(img)
@@ -121,7 +121,8 @@ class CascadeRCNN(BaseDetector, RPNTestMixin):
rpn_outs = self.rpn_head(x)
rpn_loss_inputs = rpn_outs + (gt_bboxes, img_meta,
self.train_cfg.rpn)
- rpn_losses = self.rpn_head.loss(*rpn_loss_inputs)
+ rpn_losses = self.rpn_head.loss(
+ *rpn_loss_inputs, gt_bboxes_ignore=gt_bboxes_ignore)
losses.update(rpn_losses)
proposal_inputs = rpn_outs + (img_meta, self.test_cfg.rpn)
diff --git a/mmdet/models/detectors/rpn.py b/mmdet/models/detectors/rpn.py
index b882024..36b92d0 100644
--- a/mmdet/models/detectors/rpn.py
+++ b/mmdet/models/detectors/rpn.py
@@ -38,7 +38,11 @@ class RPN(BaseDetector, RPNTestMixin):
x = self.neck(x)
return x
- def forward_train(self, img, img_meta, gt_bboxes=None):
+ def forward_train(self,
+ img,
+ img_meta,
+ gt_bboxes=None,
+ gt_bboxes_ignore=None):
if self.train_cfg.rpn.get('debug', False):
self.rpn_head.debug_imgs = tensor2imgs(img)
@@ -46,7 +50,8 @@ class RPN(BaseDetector, RPNTestMixin):
rpn_outs = self.rpn_head(x)
rpn_loss_inputs = rpn_outs + (gt_bboxes, img_meta, self.train_cfg.rpn)
- losses = self.rpn_head.loss(*rpn_loss_inputs)
+ losses = self.rpn_head.loss(
+ *rpn_loss_inputs, gt_bboxes_ignore=gt_bboxes_ignore)
return losses
def simple_test(self, img, img_meta, rescale=False):
diff --git a/mmdet/models/detectors/single_stage.py b/mmdet/models/detectors/single_stage.py
index 17fe6fb..6f73b34 100644
--- a/mmdet/models/detectors/single_stage.py
+++ b/mmdet/models/detectors/single_stage.py
@@ -42,11 +42,17 @@ class SingleStageDetector(BaseDetector):
x = self.neck(x)
return x
- def forward_train(self, img, img_metas, gt_bboxes, gt_labels):
+ def forward_train(self,
+ img,
+ img_metas,
+ gt_bboxes,
+ gt_labels,
+ gt_bboxes_ignore=None):
x = self.extract_feat(img)
outs = self.bbox_head(x)
loss_inputs = outs + (gt_bboxes, gt_labels, img_metas, self.train_cfg)
- losses = self.bbox_head.loss(*loss_inputs)
+ losses = self.bbox_head.loss(
+ *loss_inputs, gt_bboxes_ignore=gt_bboxes_ignore)
return losses
def simple_test(self, img, img_meta, rescale=False):
diff --git a/mmdet/models/detectors/two_stage.py b/mmdet/models/detectors/two_stage.py
index 68f734f..3dca618 100644
--- a/mmdet/models/detectors/two_stage.py
+++ b/mmdet/models/detectors/two_stage.py
@@ -81,8 +81,8 @@ class TwoStageDetector(BaseDetector, RPNTestMixin, BBoxTestMixin,
img,
img_meta,
gt_bboxes,
- gt_bboxes_ignore,
gt_labels,
+ gt_bboxes_ignore=None,
gt_masks=None,
proposals=None):
x = self.extract_feat(img)
@@ -94,7 +94,8 @@ class TwoStageDetector(BaseDetector, RPNTestMixin, BBoxTestMixin,
rpn_outs = self.rpn_head(x)
rpn_loss_inputs = rpn_outs + (gt_bboxes, img_meta,
self.train_cfg.rpn)
- rpn_losses = self.rpn_head.loss(*rpn_loss_inputs)
+ rpn_losses = self.rpn_head.loss(
+ *rpn_loss_inputs, gt_bboxes_ignore=gt_bboxes_ignore)
losses.update(rpn_losses)
proposal_inputs = rpn_outs + (img_meta, self.test_cfg.rpn)
@@ -108,6 +109,8 @@ class TwoStageDetector(BaseDetector, RPNTestMixin, BBoxTestMixin,
bbox_sampler = build_sampler(
self.train_cfg.rcnn.sampler, context=self)
num_imgs = img.size(0)
+ if gt_bboxes_ignore is None:
+ gt_bboxes_ignore = [None for _ in range(num_imgs)]
sampling_results = []
for i in range(num_imgs):
assign_result = bbox_assigner.assign(
--
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