update ars_detr configs

configs/ars_detr/arcsl_detr_r50_1x_rsg.py

@@ -0,0 +1,10 @@
+# -*- coding: utf-8 -*-
+_base_ = 'csl_detr_r50_1x_rsg.py'
+model = dict(
+    bbox_head=dict(
+        angle_coder=dict(
+            window='aspect_ratio',
+            normalize=True,
+        )
+    )
+)

configs/ars_detr/csl_detr_r50_1x_rsg.py

@@ -0,0 +1,149 @@
+# -*- coding: utf-8 -*-
+
+angle_version = 'le90'
+_base_ = [
+    '../_base_/datasets/rsg.py', '../_base_/schedules/schedule_1x.py',
+    '../_base_/default_runtime.py'
+]
+model = dict(
+    type='ARSDETR',
+    backbone=dict(
+        type='ResNet',
+        depth=50,
+        num_stages=4,
+        out_indices=(1, 2, 3),
+        frozen_stages=1,
+        norm_cfg=dict(type='BN', requires_grad=False),
+        norm_eval=True,
+        style='pytorch',
+        init_cfg=dict(type='Pretrained', checkpoint='torchvision://resnet50')),
+    neck=dict(
+        type='ChannelMapper',
+        in_channels=[512, 1024, 2048],
+        kernel_size=1,
+        out_channels=256,
+        act_cfg=None,
+        norm_cfg=dict(type='GN', num_groups=32),
+        num_outs=4),
+    bbox_head=dict(
+        type='ARSDeformableDETRHead',
+        num_query=300,
+        num_classes=48,
+        in_channels=2048,
+        sync_cls_avg_factor=True,
+        with_box_refine=True,
+        as_two_stage=True,
+        angle_coder=dict(
+            type='CSLCoder',
+            angle_version=angle_version,
+            omega=1,
+            window='gaussian',
+            radius=6),
+        transformer=dict(
+            type='ARSRotatedDeformableDetrTransformer',
+            two_stage_num_proposals=300,
+            encoder=dict(
+                type='DetrTransformerEncoder',
+                num_layers=6,
+                transformerlayers=dict(
+                    type='BaseTransformerLayer',
+                    attn_cfgs=dict(
+                        type='MultiScaleDeformableAttention', embed_dims=256),
+                    feedforward_channels=1024,
+                    ffn_dropout=0.1,
+                    operation_order=('self_attn', 'norm', 'ffn', 'norm'))),
+            decoder=dict(
+                type='ARSRotatedDeformableDetrTransformerDecoder',
+                num_layers=6,
+                return_intermediate=True,
+                transformerlayers=dict(
+                    type='DetrTransformerDecoderLayer',
+                    attn_cfgs=[
+                        dict(
+                            type='MultiheadAttention',
+                            embed_dims=256,
+                            num_heads=8,
+                            dropout=0.1),
+                        dict(
+                            type='MultiScaleDeformableAttention',
+                            embed_dims=256)
+                    ],
+                    feedforward_channels=1024,
+                    ffn_dropout=0.1,
+                    operation_order=('self_attn', 'norm', 'cross_attn', 'norm',
+                                     'ffn', 'norm')))),
+        positional_encoding=dict(
+            type='SinePositionalEncoding',
+            num_feats=128,
+            normalize=True,
+            offset=-0.5),
+        bbox_coder=dict(
+            type='DeltaXYWHAOBBoxCoder',
+            angle_range=angle_version,
+            norm_factor=None,
+            edge_swap=True,
+            proj_xy=True,
+            target_means=(.0, .0, .0, .0, .0),
+            target_stds=(1, 1, 1, 1, 1)),
+        loss_cls=dict(
+            type='FocalLoss',
+            use_sigmoid=True,
+            gamma=2.0,
+            alpha=0.25,
+            loss_weight=2.0),
+        loss_bbox=dict(type='L1Loss', loss_weight=2.0),
+        loss_iou=dict(type='GIoULoss', loss_weight=5.0),
+        reg_decoded_bbox=True,
+        loss_angle=dict(
+            type='CrossEntropyLoss', use_sigmoid=True, loss_weight=2.0),
+    ),
+    # training and testing settings
+    train_cfg=dict(
+        assigner=dict(
+            type='ARS_HungarianAssigner',
+            cls_cost=dict(type='FocalLossCost', weight=2.0),
+            reg_cost=dict(type='BBoxL1Cost', weight=2.0, box_format='xywh'),
+            iou_cost=dict(type='IoUCost', iou_mode='giou', weight=5.0),
+            angle_cost=dict(type='CrossEntropyLossCost', weight=2.0)
+        )),
+    test_cfg=dict()
+)
+img_norm_cfg = dict(
+    mean=[123.675, 116.28, 103.53], std=[58.395, 57.12, 57.375], to_rgb=True)
+train_pipeline = [
+    dict(type='LoadImageFromFile'),
+    dict(type='LoadAnnotations', with_bbox=True),
+    dict(type='RResize', img_scale=(1024, 1024)),
+    dict(
+        type='RRandomFlip',
+        flip_ratio=[0.25, 0.25, 0.25],
+        direction=['horizontal', 'vertical', 'diagonal'],
+        version=angle_version),
+    dict(type='Normalize', **img_norm_cfg),
+    dict(type='Pad', size_divisor=32),
+    dict(type='DefaultFormatBundle'),
+    dict(type='Collect', keys=['img', 'gt_bboxes', 'gt_labels'])
+]
+
+data = dict(
+    samples_per_gpu=2,
+    workers_per_gpu=2,
+    train=dict(pipeline=train_pipeline, version=angle_version),
+    val=dict(version=angle_version),
+    test=dict(version=angle_version))
+
+optimizer = dict(
+    _delete_=True,
+    type='AdamW',
+    lr=1e-4,
+    weight_decay=0.00001,
+    betas=(0.9, 0.999),
+    paramwise_cfg=dict(
+        custom_keys={
+            'backbone': dict(lr_mult=0.1),
+            'sampling_offsets': dict(lr_mult=0.1),
+            'reference_points': dict(lr_mult=0.1)
+        }))
+
+checkpoint_config = dict(interval=1, max_keep_ckpts=1)
+evaluation = dict(interval=6, metric='mAP')

configs/ars_detr/dn_arw_arm_arcsl_rdetr_r50_1x_rsg.py

@@ -0,0 +1,30 @@
+# -*- coding: utf-8 -*-
+_base_ = 'arcsl_detr_r50_1x_rsg.py'
+model = dict(
+    bbox_head=dict(
+        type='DNARSDeformableDETRHead',
+        as_two_stage=True,
+        rotate_deform_attn=True,
+        aspect_ratio_weighting=True,
+        dn_cfg=dict(
+            type='DnQueryGenerator',
+            noise_scale=dict(label=0.5, box=0.4, angle=0.02),
+            group_cfg=dict(dynamic=True, num_groups=None, num_dn_queries=100)),
+        transformer=dict(
+            type='DNARSRotatedDeformableDetrTransformer',
+            decoder=dict(type='DNARSDeformableDetrTransformerDecoder',
+                    transformerlayers=dict(
+                    attn_cfgs=[
+                        dict(
+                            type='MultiheadAttention',
+                            embed_dims=256,
+                            num_heads=8,
+                            dropout=0.1),
+                        dict(
+                            type='RotatedMultiScaleDeformableAttention',
+                            embed_dims=256)
+                    ])
+            )
+        )
+    ),
+)

pjlab_train_yx.sh

@@ -4,14 +4,14 @@ partition='VC2'
 TYPE='reserved'
 # partition='INTERN3'
 # TYPE='spot'
-JOB_NAME='g_reppoints_r50_fpn_1x_rsg_le135'
+JOB_NAME='dn_arw_arm_arcsl_rdetr_r50_1x_rsg'
 GPUS=1
 GPUS_PER_NODE=1
 CPUS_PER_TASK=12
-export MASTER_PORT=29516
+export MASTER_PORT=29517
 
-SRUN_ARGS="--jobid=3211251 --nodes=1"
-CONFIG="./configs/g_reppoints/g_reppoints_r50_fpn_1x_rsg_le135.py"
+SRUN_ARGS="--jobid=3200806 --nodes=1"
+CONFIG="./configs/g_reppoints/dn_arw_arm_arcsl_rdetr_r50_1x_rsg.py"
 
 EXTRA_ARGS="--auto-resume"