delete work_dir in all configs (open-mmlab#2315)

* delete work_dir in all configs

* add comment on work_dir priority

Author: xvjiarui

configs/albu_example/mask_rcnn_r50_fpn_albu_1x_coco.py

@@ -71,4 +71,3 @@
                    'pad_shape', 'scale_factor'))
 ]
 data = dict(train=dict(pipeline=train_pipeline))
-work_dir = './work_dirs/mask_rcnn_r50_fpn_1x'

configs/atss/atss_r50_fpn_1x_coco.py

@@ -4,4 +4,3 @@
 ]
 # optimizer
 optimizer = dict(type='SGD', lr=0.01, momentum=0.9, weight_decay=0.0001)
-work_dir = './work_dirs/atss_r50_fpn_1x'

configs/carafe/faster_rcnn_r50_fpn_carafe_1x_coco.py

@@ -48,4 +48,3 @@
     train=dict(pipeline=train_pipeline),
     val=dict(pipeline=test_pipeline),
     test=dict(pipeline=test_pipeline))
-work_dir = './work_dirs/faster_rcnn_r50_fpn_carafe_1x'

configs/carafe/mask_rcnn_r50_fpn_carafe_1x_coco.py

@@ -57,4 +57,3 @@
     train=dict(pipeline=train_pipeline),
     val=dict(pipeline=test_pipeline),
     test=dict(pipeline=test_pipeline))
-work_dir = './work_dirs/mask_rcnn_r50_fpn_carafe_1x'

configs/cascade_rcnn/cascade_mask_rcnn_r101_fpn_1x_coco.py

@@ -1,3 +1,2 @@
 _base_ = './cascade_mask_rcnn_r50_fpn_1x_coco.py'
 model = dict(pretrained='torchvision://resnet101', backbone=dict(depth=101))
-work_dir = './work_dirs/cascade_mask_rcnn_r101_fpn_1x'

configs/cascade_rcnn/cascade_mask_rcnn_r50_fpn_1x_coco.py

@@ -3,4 +3,3 @@
     '../_base_/datasets/coco_instance.py',
     '../_base_/schedules/schedule_1x.py', '../_base_/default_runtime.py'
 ]
-work_dir = './work_dirs/cascade_mask_rcnn_r50_fpn_1x'

configs/cascade_rcnn/cascade_mask_rcnn_x101_32x4d_fpn_1x_coco.py

@@ -11,4 +11,3 @@
         frozen_stages=1,
         norm_cfg=dict(type='BN', requires_grad=True),
         style='pytorch'))
-work_dir = './work_dirs/cascade_mask_rcnn_x101_32x4d_fpn_1x'

configs/cascade_rcnn/cascade_mask_rcnn_x101_64x4d_fpn_1x_coco.py

@@ -11,4 +11,3 @@
         frozen_stages=1,
         norm_cfg=dict(type='BN', requires_grad=True),
         style='pytorch'))
-work_dir = './work_dirs/cascade_mask_rcnn_x101_64x4d_fpn_1x'

configs/cascade_rcnn/cascade_rcnn_r101_fpn_1x_coco.py

@@ -1,3 +1,2 @@
 _base_ = './cascade_rcnn_r50_fpn_1x_coco.py'
 model = dict(pretrained='torchvision://resnet101', backbone=dict(depth=101))
-work_dir = './work_dirs/cascade_rcnn_r101_fpn_1x'

configs/cascade_rcnn/cascade_rcnn_r50_fpn_1x_coco.py

@@ -3,4 +3,3 @@
     '../_base_/datasets/coco_detection.py',
     '../_base_/schedules/schedule_1x.py', '../_base_/default_runtime.py'
 ]
-work_dir = './work_dirs/cascade_rcnn_r50_fpn_1x'

configs/cascade_rcnn/cascade_rcnn_x101_32x4d_fpn_1x_coco.py

@@ -11,4 +11,3 @@
         frozen_stages=1,
         norm_cfg=dict(type='BN', requires_grad=True),
         style='pytorch'))
-work_dir = './work_dirs/cascade_rcnn_x101_32x4d_fpn_1x'

configs/cascade_rcnn/cascade_rcnn_x101_64x4d_fpn_1x_coco.py

@@ -13,4 +13,3 @@
         frozen_stages=1,
         norm_cfg=dict(type='BN', requires_grad=True),
         style='pytorch'))
-work_dir = './work_dirs/cascade_rcnn_x101_64x4d_fpn_1x'

configs/cityscapes/faster_rcnn_r50_fpn_1x_cityscapes.py

@@ -31,6 +31,5 @@
     step=[7])
 total_epochs = 8  # actual epoch = 8 * 8 = 64
 log_config = dict(interval=100)
-work_dir = './work_dirs/cityscapes/faster_rcnn_r50_fpn_1x_cityscapes'
 # For better, more stable performance initialize from COCO
 load_from = 'https://s3.ap-northeast-2.amazonaws.com/open-mmlab/mmdetection/models/faster_rcnn_r50_fpn_2x_20181010-443129e1.pth'  # noqa

configs/cityscapes/mask_rcnn_r50_fpn_1x_cityscapes.py

@@ -38,6 +38,5 @@
     step=[7])
 total_epochs = 8  # actual epoch = 8 * 8 = 64
 log_config = dict(interval=100)
-work_dir = './work_dirs/cityscapes/mask_rcnn_r50_fpn_1x_cityscapes'
 # For better, more stable performance initialize from COCO
 load_from = 'https://s3.ap-northeast-2.amazonaws.com/open-mmlab/mmdetection/models/mask_rcnn_r50_fpn_2x_20181010-41d35c05.pth'  # noqa

configs/dcn/cascade_mask_rcnn_r50_fpn_dconv_c3-c5_1x_coco.py

@@ -3,4 +3,3 @@
     backbone=dict(
         dcn=dict(type='DCN', deformable_groups=1, fallback_on_stride=False),
         stage_with_dcn=(False, True, True, True)))
-work_dir = './work_dirs/cascade_mask_rcnn_dconv_c3-c5_r50_fpn_1x'

configs/dcn/cascade_rcnn_r50_fpn_dconv_c3-c5_1x_coco.py

@@ -3,4 +3,3 @@
     backbone=dict(
         dcn=dict(type='DCN', deformable_groups=1, fallback_on_stride=False),
         stage_with_dcn=(False, True, True, True)))
-work_dir = './work_dirs/cascade_rcnn_dconv_c3-c5_r50_fpn_1x'

configs/dcn/faster_rcnn_r50_fpn_dconv_c3-c5_1x_coco.py

@@ -3,4 +3,3 @@
     backbone=dict(
         dcn=dict(type='DCN', deformable_groups=1, fallback_on_stride=False),
         stage_with_dcn=(False, True, True, True)))
-work_dir = './work_dirs/faster_rcnn_dconv_c3-c5_r50_fpn_1x'

configs/dcn/faster_rcnn_r50_fpn_dpool_1x_coco.py

@@ -12,4 +12,3 @@
             trans_std=0.1),
         out_channels=256,
         featmap_strides=[4, 8, 16, 32]))
-work_dir = './work_dirs/faster_rcnn_dpool_r50_fpn_1x'

configs/dcn/faster_rcnn_r50_fpn_mdconv_c3-c5_1x_coco.py

@@ -3,4 +3,3 @@
     backbone=dict(
         dcn=dict(type='DCNv2', deformable_groups=1, fallback_on_stride=False),
         stage_with_dcn=(False, True, True, True)))
-work_dir = './work_dirs/faster_rcnn_mdconv_c3-c5_r50_fpn_1x'

configs/dcn/faster_rcnn_r50_fpn_mdconv_c3-c5_group4_1x_coco.py

@@ -3,4 +3,3 @@
     backbone=dict(
         dcn=dict(type='DCNv2', deformable_groups=4, fallback_on_stride=False),
         stage_with_dcn=(False, True, True, True)))
-work_dir = './work_dirs/faster_rcnn_mdconv_c3-c5_group4_r50_fpn_1x'

configs/dcn/faster_rcnn_r50_fpn_mdpool_1x_coco.py

@@ -12,4 +12,3 @@
             trans_std=0.1),
         out_channels=256,
         featmap_strides=[4, 8, 16, 32]))
-work_dir = './work_dirs/faster_rcnn_mdpool_r50_fpn_1x'

configs/dcn/faster_rcnn_x101_32x4d_fpn_dconv_c3-c5_1x_coco.py

@@ -13,4 +13,3 @@
         style='pytorch',
         dcn=dict(type='DCN', deformable_groups=1, fallback_on_stride=False),
         stage_with_dcn=(False, True, True, True)))
-work_dir = './work_dirs/faster_rcnn_dconv_c3-c5_x101_32x4d_fpn_1x'

configs/dcn/mask_rcnn_r50_fpn_dconv_c3-c5_1x_coco.py

@@ -3,4 +3,3 @@
     backbone=dict(
         dcn=dict(type='DCN', deformable_groups=1, fallback_on_stride=False),
         stage_with_dcn=(False, True, True, True)))
-work_dir = './work_dirs/mask_rcnn_dconv_c3-c5_r50_fpn_1x'

configs/dcn/mask_rcnn_r50_fpn_mdconv_c3-c5_1x_coco.py

@@ -3,4 +3,3 @@
     backbone=dict(
         dcn=dict(type='DCNv2', deformable_groups=1, fallback_on_stride=False),
         stage_with_dcn=(False, True, True, True)))
-work_dir = './work_dirs/mask_rcnn_dconv_c3-c5_r50_fpn_1x'

configs/double_heads/dh_faster_rcnn_r50_fpn_1x_coco.py

@@ -18,4 +18,3 @@
         loss_cls=dict(
             type='CrossEntropyLoss', use_sigmoid=False, loss_weight=2.0),
         loss_bbox=dict(type='SmoothL1Loss', beta=1.0, loss_weight=2.0)))
-work_dir = './work_dirs/dh_faster_rcnn_r50_fpn_1x'

configs/empirical_attention/faster_rcnn_r50_fpn_attention_0010_1x_coco.py

@@ -5,4 +5,3 @@
             spatial_range=-1, num_heads=8, attention_type='0010', kv_stride=2),
         stage_with_gen_attention=[[], [], [0, 1, 2, 3, 4, 5], [0, 1, 2]],
     ))
-work_dir = './work_dirs/faster_rcnn_r50_fpn_attention_0010_1x'

configs/empirical_attention/faster_rcnn_r50_fpn_attention_0010_dcn_1x_coco.py

@@ -7,4 +7,3 @@
         dcn=dict(type='DCN', deformable_groups=1, fallback_on_stride=False),
         stage_with_dcn=(False, True, True, True),
     ))
-work_dir = './work_dirs/faster_rcnn_r50_fpn_attention_0010_dcn_1x'

configs/empirical_attention/faster_rcnn_r50_fpn_attention_1111_1x_coco.py

@@ -5,4 +5,3 @@
             spatial_range=-1, num_heads=8, attention_type='1111', kv_stride=2),
         stage_with_gen_attention=[[], [], [0, 1, 2, 3, 4, 5], [0, 1, 2]],
     ))
-work_dir = './work_dirs/faster_rcnn_r50_fpn_attention_1111_1x'

configs/empirical_attention/faster_rcnn_r50_fpn_attention_1111_dcn_1x_coco.py

@@ -7,4 +7,3 @@
         dcn=dict(type='DCN', deformable_groups=1, fallback_on_stride=False),
         stage_with_dcn=(False, True, True, True),
     ))
-work_dir = './work_dirs/faster_rcnn_r50_fpn_attention_1111_dcn_1x'

configs/fast_rcnn/fast_rcnn_r50_fpn_1x_coco.py

@@ -50,4 +50,3 @@
     test=dict(
         proposal_file=data_root + 'proposals/rpn_r50_fpn_1x_val2017.pkl',
         pipeline=test_pipeline))
-work_dir = './work_dirs/fast_rcnn_r50_fpn_1x'

configs/faster_rcnn/faster_rcnn_r101_fpn_1x_coco.py

@@ -1,3 +1,2 @@
 _base_ = './faster_rcnn_r50_fpn_1x_coco.py'
 model = dict(pretrained='torchvision://resnet101', backbone=dict(depth=101))
-work_dir = './work_dirs/faster_rcnn_r101_fpn_1x'

configs/faster_rcnn/faster_rcnn_r50_caffe_c4_1x_coco.py

@@ -37,4 +37,3 @@
     test=dict(pipeline=test_pipeline))
 # optimizer
 optimizer = dict(type='SGD', lr=0.01, momentum=0.9, weight_decay=0.0001)
-work_dir = './work_dirs/faster_rcnn_r50_caffe_c4_1x'

configs/faster_rcnn/faster_rcnn_r50_caffe_fpn_1x_coco.py

@@ -34,4 +34,3 @@
     train=dict(pipeline=train_pipeline),
     val=dict(pipeline=test_pipeline),
     test=dict(pipeline=test_pipeline))
-work_dir = './work_dirs/faster_rcnn_r50_caffe_fpn_1x'

configs/faster_rcnn/faster_rcnn_r50_fpn_1x_coco.py

@@ -3,4 +3,3 @@
     '../_base_/datasets/coco_detection.py',
     '../_base_/schedules/schedule_1x.py', '../_base_/default_runtime.py'
 ]
-work_dir = './work_dirs/faster_rcnn_r50_fpn_1x'

configs/faster_rcnn/faster_rcnn_r50_fpn_ohem_1x_coco.py

@@ -1,3 +1,2 @@
 _base_ = './faster_rcnn_r50_fpn_1x_coco.py'
 train_cfg = dict(rcnn=dict(sampler=dict(type='OHEMSampler')))
-work_dir = './work_dirs/faster_rcnn_r50_fpn_1x'

configs/faster_rcnn/faster_rcnn_x101_32x4d_fpn_1x_coco.py

@@ -11,4 +11,3 @@
         frozen_stages=1,
         norm_cfg=dict(type='BN', requires_grad=True),
         style='pytorch'))
-work_dir = './work_dirs/faster_rcnn_x101_32x4d_fpn_1x'

configs/faster_rcnn/faster_rcnn_x101_64x4d_fpn_1x_coco.py

@@ -11,4 +11,3 @@
         frozen_stages=1,
         norm_cfg=dict(type='BN', requires_grad=True),
         style='pytorch'))
-work_dir = './work_dirs/faster_rcnn_x101_64x4d_fpn_1x'

configs/fcos/fcos_center_r50_caffe_fpn_gn-head_4x4_1x_coco.py

@@ -1,3 +1,2 @@
 _base_ = './fcos_r50_caffe_fpn_gn-head_4x4_1x_coco.py'
 model = dict(bbox_head=dict(center_sampling=True, center_sample_radius=1.5))
-work_dir = './work_dirs/fcos_center_r50_caffe_fpn_gn_1x_4gpu'

configs/fcos/fcos_r101_caffe_fpn_gn-head_mstrain_640-800_4x4_2x_coco.py

@@ -41,4 +41,3 @@
 # learning policy
 lr_config = dict(step=[16, 22])
 total_epochs = 24
-work_dir = './work_dirs/fcos_mstrain_640_800_r101_caffe_fpn_gn_2x_4gpu'

configs/fcos/fcos_r50_caffe_fpn_gn-head_4x4_1x_coco.py

@@ -96,4 +96,3 @@
 # learning policy
 lr_config = dict(warmup='constant')
 total_epochs = 12
-work_dir = './work_dirs/fcos_r50_caffe_fpn_gn_1x_4gpu'

configs/fcos/fcos_x101_64x4d_fpn_gn-head_mstrain_640-800_4x2_2x_coco.py

@@ -55,4 +55,3 @@
 # learning policy
 lr_config = dict(warmup='constant', step=[16, 22])
 total_epochs = 24
-work_dir = './work_dirs/fcos_mstrain_640_800_x101_64x4d_fpn_gn_2x'

configs/foveabox/fovea_align_r101_fpn_gn-head_4x4_2x_coco.py

@@ -8,4 +8,3 @@
 # learning policy
 lr_config = dict(step=[16, 22])
 total_epochs = 24
-work_dir = './work_dirs/fovea_align_gn_r101_fpn_4gpu_2x'

configs/foveabox/fovea_align_r101_fpn_gn-head_mstrain_640-800_4x4_2x_coco.py

@@ -25,4 +25,3 @@
 # learning policy
 lr_config = dict(step=[16, 22])
 total_epochs = 24
-work_dir = './work_dirs/fovea_align_gn_ms_r101_fpn_4gpu_2x'

configs/foveabox/fovea_align_r50_fpn_gn-head_4x4_2x_coco.py

@@ -6,4 +6,3 @@
 # learning policy
 lr_config = dict(step=[16, 22])
 total_epochs = 24
-work_dir = './work_dirs/fovea_align_gn_r50_fpn_4gpu_2x'

configs/foveabox/fovea_align_r50_fpn_gn-head_mstrain_640-800_4x4_2x_coco.py

@@ -23,4 +23,3 @@
 # learning policy
 lr_config = dict(step=[16, 22])
 total_epochs = 24
-work_dir = './work_dirs/fovea_align_gn_ms_r50_fpn_4gpu_2x'

configs/foveabox/fovea_r50_fpn_4x4_1x_coco.py

@@ -49,4 +49,3 @@
 data = dict(imgs_per_gpu=4, workers_per_gpu=4)
 # optimizer
 optimizer = dict(type='SGD', lr=0.01, momentum=0.9, weight_decay=0.0001)
-work_dir = './work_dirs/fovea_r50_fpn_4gpu_1x'

configs/fp16/faster_rcnn_r50_fpn_fp16_1x_coco.py

@@ -1,4 +1,3 @@
 _base_ = '../faster_rcnn/faster_rcnn_r50_fpn_1x_coco.py'
 # fp16 settings
 fp16 = dict(loss_scale=512.)
-work_dir = './work_dirs/faster_rcnn_r50_fpn_fp16_1x'

configs/fp16/mask_rcnn_r50_fpn_fp16_1x_coco.py

@@ -1,4 +1,3 @@
 _base_ = '../mask_rcnn/mask_rcnn_r50_fpn_1x_coco.py'
 # fp16 settings
 fp16 = dict(loss_scale=512.)
-work_dir = './work_dirs/mask_rcnn_r50_fpn_fp16_1x'

configs/fp16/retinanet_r50_fpn_fp16_1x_coco.py

@@ -1,4 +1,3 @@
 _base_ = '../retinanet/retinanet_r50_fpn_1x_coco.py'
 # fp16 settings
 fp16 = dict(loss_scale=512.)
-work_dir = './work_dirs/retinanet_r50_fpn_fp16_1x'

configs/free_anchor/retinanet_free_anchor_r101_fpn_1x_coco.py

@@ -1,3 +1,2 @@
 _base_ = './retinanet_free_anchor_r50_fpn_1x_coco.py'
 model = dict(pretrained='torchvision://resnet101', backbone=dict(depth=101))
-work_dir = './work_dirs/retinanet_free_anchor_r101_fpn_1x'

configs/free_anchor/retinanet_free_anchor_r50_fpn_1x_coco.py

@@ -14,4 +14,3 @@
         target_means=[.0, .0, .0, .0],
         target_stds=[0.1, 0.1, 0.2, 0.2],
         loss_bbox=dict(type='SmoothL1Loss', beta=0.11, loss_weight=0.75)))
-work_dir = './work_dirs/retinanet_free_anchor_r50_fpn_1x'

configs/free_anchor/retinanet_free_anchor_x101-32x4d_fpn_1x_coco.py

@@ -10,4 +10,3 @@
         out_indices=(0, 1, 2, 3),
         frozen_stages=1,
         style='pytorch'))
-work_dir = './work_dirs/retinanet_free_anchor_x101-32x4d_fpn_1x'

configs/gcnet/mask_rcnn_r50_fpn_r16_gcb_c3-c5_1x_coco.py

@@ -2,4 +2,3 @@
 model = dict(
     backbone=dict(
         gcb=dict(ratio=1. / 16., ), stage_with_gcb=(False, True, True, True)))
-work_dir = './work_dirs/mask_rcnn_r16_gcb_c3-c5_r50_fpn_1x'

configs/gcnet/mask_rcnn_r50_fpn_r4_gcb_c3-c5_1x_coco.py

@@ -2,4 +2,3 @@
 model = dict(
     backbone=dict(
         gcb=dict(ratio=1. / 4., ), stage_with_gcb=(False, True, True, True)))
-work_dir = './work_dirs/mask_rcnn_r4_gcb_c3-c5_r50_fpn_1x'

configs/gcnet/mask_rcnn_r50_fpn_syncbn-backbone_1x_coco.py

@@ -2,4 +2,3 @@
 model = dict(
     backbone=dict(
         norm_cfg=dict(type='SyncBN', requires_grad=True), norm_eval=False))
-work_dir = './work_dirs/mask_rcnn_r50_fpn_sbn_1x'

configs/gcnet/mask_rcnn_r50_fpn_syncbn-backbone_r16_gcb_c3-c5_1x_coco.py

@@ -5,4 +5,3 @@
         norm_eval=False,
         stage_with_gcb=(False, True, True, True),
         gcb=dict(ratio=1. / 16., )))
-work_dir = './work_dirs/mask_rcnn_r16_gcb_c3-c5_r50_fpn_syncbn_1x'

configs/gcnet/mask_rcnn_r50_fpn_syncbn-backbone_r4_gcb_c3-c5_1x_coco.py

@@ -5,4 +5,3 @@
         norm_eval=False,
         gcb=dict(ratio=1. / 4., ),
         stage_with_gcb=(False, True, True, True)))
-work_dir = './work_dirs/mask_rcnn_r4_gcb_c3-c5_r50_fpn_syncbn_1x'

configs/ghm/retinanet_ghm_r50_fpn_1x_coco.py

@@ -15,4 +15,3 @@
             bins=10,
             momentum=0.7,
             loss_weight=10.0)))
-work_dir = './work_dirs/ghm'

configs/gn+ws/faster_rcnn_r50_fpn_gn_ws-all_1x_coco.py

@@ -10,4 +10,3 @@
         conv_out_channels=256,
         conv_cfg=conv_cfg,
         norm_cfg=norm_cfg))
-work_dir = './work_dirs/faster_rcnn_r50_fpn_gn_ws_1x'

configs/gn+ws/mask_rcnn_r50_fpn_gn_ws-all_20_23_24e_coco.py

@@ -2,4 +2,3 @@
 # learning policy
 lr_config = dict(step=[20, 23])
 total_epochs = 24
-work_dir = './work_dirs/mask_rcnn_r50_fpn_gn_ws_20_23_24e'

configs/gn+ws/mask_rcnn_r50_fpn_gn_ws-all_2x_coco.py

@@ -14,4 +14,3 @@
 # learning policy
 lr_config = dict(step=[16, 22])
 total_epochs = 24
-work_dir = './work_dirs/mask_rcnn_r50_fpn_gn_ws_2x'

configs/gn+ws/mask_rcnn_x101_32x4d_fpn_gn_ws-all_2x_coco.py

@@ -15,4 +15,3 @@
         style='pytorch',
         conv_cfg=conv_cfg,
         norm_cfg=norm_cfg))
-work_dir = './work_dirs/mask_rcnn_x101_32x4d_fpn_gn_ws_2x'

configs/gn/mask_rcnn_r101_fpn_gn-all_2x_coco.py

@@ -1,4 +1,3 @@
 _base_ = './mask_rcnn_r50_fpn_gn-all_2x_coco.py'
 model = dict(
     pretrained='open-mmlab://detectron/resnet101_gn', backbone=dict(depth=101))
-work_dir = './work_dirs/mask_rcnn_r101_fpn_gn_2x'

configs/gn/mask_rcnn_r50_fpn_gn-all_2x_coco.py

@@ -43,4 +43,3 @@
 # learning policy
 lr_config = dict(step=[16, 22])
 total_epochs = 24
-work_dir = './work_dirs/mask_rcnn_r50_fpn_gn_2x'

configs/gn/mask_rcnn_r50_fpn_gn-all_contrib_2x_coco.py

@@ -12,4 +12,3 @@
 # learning policy
 lr_config = dict(step=[16, 22])
 total_epochs = 24
-work_dir = './work_dirs/mask_rcnn_r50_fpn_gn_contrib_2x'

configs/grid_rcnn/grid_rcnn_r50_fpn_gn-head_2x_coco.py

@@ -122,4 +122,3 @@
     warmup_ratio=1.0 / 80,
     step=[17, 23])
 total_epochs = 25
-work_dir = './work_dirs/grid_rcnn_gn_head_r50_fpn_2x'

configs/grid_rcnn/grid_rcnn_x101_32x4d_fpn_gn-head_2x_coco.py

@@ -21,4 +21,3 @@
     warmup_ratio=1.0 / 80,
     step=[17, 23])
 total_epochs = 25
-work_dir = './work_dirs/grid_rcnn_gn_head_x101_32x4d_fpn_2x'

configs/guided_anchoring/ga_fast_r50_caffe_fpn_1x_coco.py

@@ -57,4 +57,3 @@
     test=dict(
         proposal_file=data_root + 'proposals/ga_rpn_r50_fpn_1x_val2017.pkl',
         pipeline=test_pipeline))
-work_dir = './work_dirs/ga_fast_rcnn_r50_caffe_fpn_1x'

configs/guided_anchoring/ga_faster_r50_caffe_fpn_1x_coco.py

@@ -49,4 +49,3 @@
         assigner=dict(pos_iou_thr=0.6, neg_iou_thr=0.6, min_pos_iou=0.6),
         sampler=dict(type='RandomSampler', num=256)))
 test_cfg = dict(rpn=dict(max_num=300), rcnn=dict(score_thr=1e-3))
-work_dir = './work_dirs/ga_faster_rcnn_r50_caffe_fpn_1x'

configs/guided_anchoring/ga_faster_r50_fpn_1x_coco.py

@@ -49,4 +49,3 @@
         assigner=dict(pos_iou_thr=0.6, neg_iou_thr=0.6, min_pos_iou=0.6),
         sampler=dict(type='RandomSampler', num=256)))
 test_cfg = dict(rpn=dict(max_num=300), rcnn=dict(score_thr=1e-3))
-work_dir = './work_dirs/ga_faster_rcnn_r50_fpn_1x'

configs/guided_anchoring/ga_faster_x101_32x4d_fpn_1x_coco.py

@@ -11,4 +11,3 @@
         frozen_stages=1,
         norm_cfg=dict(type='BN', requires_grad=True),
         style='pytorch'))
-work_dir = './work_dirs/ga_faster_rcnn_x101_32x4d_fpn_1x'

configs/guided_anchoring/ga_retinanet_r50_caffe_fpn_1x_coco.py

@@ -48,4 +48,3 @@
     assigner=dict(neg_iou_thr=0.5, min_pos_iou=0.0),
     center_ratio=0.2,
     ignore_ratio=0.5)
-work_dir = './work_dirs/ga_retinanet_r50_caffe_fpn_1x'

configs/guided_anchoring/ga_retinanet_r50_fpn_1x_coco.py

@@ -48,4 +48,3 @@
     assigner=dict(neg_iou_thr=0.5, min_pos_iou=0.0),
     center_ratio=0.2,
     ignore_ratio=0.5)
-work_dir = './work_dirs/ga_retinanet_r50_fpn_1x'

configs/guided_anchoring/ga_retinanet_x101_32x4d_fpn_1x_coco.py

@@ -11,4 +11,3 @@
         frozen_stages=1,
         norm_cfg=dict(type='BN', requires_grad=True),
         style='pytorch'))
-work_dir = './work_dirs/ga_retinanet_x101_32x4d_fpn_1x'

configs/guided_anchoring/ga_rpn_r101_caffe_rpn_1x_coco.py

@@ -2,4 +2,3 @@
 # model settings
 model = dict(
     pretrained='open-mmlab://resnet101_caffe', backbone=dict(depth=101))
-work_dir = './work_dirs/ga_rpn_r101_caffe_fpn_1x'

configs/guided_anchoring/ga_rpn_r50_caffe_fpn_1x_coco.py

@@ -43,4 +43,3 @@
         allowed_border=-1,
         center_ratio=0.2,
         ignore_ratio=0.5))
-work_dir = './work_dirs/ga_rpn_r50_caffe_fpn_1x'

configs/guided_anchoring/ga_rpn_r50_fpn_1x_coco.py

@@ -43,4 +43,3 @@
         allowed_border=-1,
         center_ratio=0.2,
         ignore_ratio=0.5))
-work_dir = './work_dirs/ga_rpn_r50_fpn_1x'

configs/guided_anchoring/ga_rpn_x101_32x4d_fpn_1x_coco.py

@@ -11,4 +11,3 @@
         frozen_stages=1,
         norm_cfg=dict(type='BN', requires_grad=True),
         style='pytorch'))
-work_dir = './work_dirs/ga_rpn_x101_32x4d_fpn_1x'

configs/hrnet/cascade_mask_rcnn_hrnetv2p_w32_20e_coco.py

@@ -37,4 +37,3 @@
 # learning policy
 lr_config = dict(step=[16, 19])
 total_epochs = 20
-work_dir = './work_dirs/cascade_mask_rcnn_hrnetv2p_w32_20e'

configs/hrnet/cascade_rcnn_hrnetv2p_w32_20e_coco.py

@@ -37,4 +37,3 @@
 # learning policy
 lr_config = dict(step=[16, 19])
 total_epochs = 20
-work_dir = './work_dirs/cascade_rcnn_hrnetv2p_w32'