From 1ec92ef4094c239ae138ace52787a2496e4cb8df Mon Sep 17 00:00:00 2001
From: myownskyW7 <1155098160@link.cuhk.edu.hk>
Date: Mon, 13 May 2019 17:21:29 +0800
Subject: [PATCH] rename use_focal_loss -> cls_focal_loss (#639)
* use_sigmoid_cls -> cls_sigmoid_loss; use_focal_loss -> cls_focal_loss
* fix flake8 error
* cls_sigmoid_loss - > use_sigmoid_cls
---
mmdet/models/anchor_heads/anchor_head.py | 20 ++++++++++----------
mmdet/models/anchor_heads/retina_head.py | 2 +-
mmdet/models/anchor_heads/ssd_head.py | 2 +-
3 files changed, 12 insertions(+), 12 deletions(-)
diff --git a/mmdet/models/anchor_heads/anchor_head.py b/mmdet/models/anchor_heads/anchor_head.py
index d059c65..54096a4 100644
--- a/mmdet/models/anchor_heads/anchor_head.py
+++ b/mmdet/models/anchor_heads/anchor_head.py
@@ -25,9 +25,9 @@ class AnchorHead(nn.Module):
anchor_base_sizes (Iterable): Anchor base sizes.
target_means (Iterable): Mean values of regression targets.
target_stds (Iterable): Std values of regression targets.
- use_sigmoid_cls (bool): Whether to use sigmoid loss for classification.
- (softmax by default)
- use_focal_loss (bool): Whether to use focal loss for classification.
+ use_sigmoid_cls (bool): Whether to use sigmoid loss for
+ classification. (softmax by default)
+ cls_focal_loss (bool): Whether to use focal loss for classification.
""" # noqa: W605
def __init__(self,
@@ -41,7 +41,7 @@ class AnchorHead(nn.Module):
target_means=(.0, .0, .0, .0),
target_stds=(1.0, 1.0, 1.0, 1.0),
use_sigmoid_cls=False,
- use_focal_loss=False):
+ cls_focal_loss=False):
super(AnchorHead, self).__init__()
self.in_channels = in_channels
self.num_classes = num_classes
@@ -54,7 +54,7 @@ class AnchorHead(nn.Module):
self.target_means = target_means
self.target_stds = target_stds
self.use_sigmoid_cls = use_sigmoid_cls
- self.use_focal_loss = use_focal_loss
+ self.cls_focal_loss = cls_focal_loss
self.anchor_generators = []
for anchor_base in self.anchor_base_sizes:
@@ -133,16 +133,16 @@ class AnchorHead(nn.Module):
cls_score = cls_score.permute(0, 2, 3, 1).reshape(
-1, self.cls_out_channels)
if self.use_sigmoid_cls:
- if self.use_focal_loss:
+ if self.cls_focal_loss:
cls_criterion = weighted_sigmoid_focal_loss
else:
cls_criterion = weighted_binary_cross_entropy
else:
- if self.use_focal_loss:
+ if self.cls_focal_loss:
raise NotImplementedError
else:
cls_criterion = weighted_cross_entropy
- if self.use_focal_loss:
+ if self.cls_focal_loss:
loss_cls = cls_criterion(
cls_score,
labels,
@@ -178,7 +178,7 @@ class AnchorHead(nn.Module):
anchor_list, valid_flag_list = self.get_anchors(
featmap_sizes, img_metas)
- sampling = False if self.use_focal_loss else True
+ sampling = False if self.cls_focal_loss else True
label_channels = self.cls_out_channels if self.use_sigmoid_cls else 1
cls_reg_targets = anchor_target(
anchor_list,
@@ -196,7 +196,7 @@ class AnchorHead(nn.Module):
return None
(labels_list, label_weights_list, bbox_targets_list, bbox_weights_list,
num_total_pos, num_total_neg) = cls_reg_targets
- num_total_samples = (num_total_pos if self.use_focal_loss else
+ num_total_samples = (num_total_pos if self.cls_focal_loss else
num_total_pos + num_total_neg)
losses_cls, losses_reg = multi_apply(
self.loss_single,
diff --git a/mmdet/models/anchor_heads/retina_head.py b/mmdet/models/anchor_heads/retina_head.py
index 815e8f0..3eefca4 100644
--- a/mmdet/models/anchor_heads/retina_head.py
+++ b/mmdet/models/anchor_heads/retina_head.py
@@ -32,7 +32,7 @@ class RetinaHead(AnchorHead):
in_channels,
anchor_scales=anchor_scales,
use_sigmoid_cls=True,
- use_focal_loss=True,
+ cls_focal_loss=True,
**kwargs)
def _init_layers(self):
diff --git a/mmdet/models/anchor_heads/ssd_head.py b/mmdet/models/anchor_heads/ssd_head.py
index 1f704f7..9c8b2a1 100644
--- a/mmdet/models/anchor_heads/ssd_head.py
+++ b/mmdet/models/anchor_heads/ssd_head.py
@@ -90,7 +90,7 @@ class SSDHead(AnchorHead):
self.target_means = target_means
self.target_stds = target_stds
self.use_sigmoid_cls = False
- self.use_focal_loss = False
+ self.cls_focal_loss = False
def init_weights(self):
for m in self.modules():
--
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