您好： 我尝试复现你的这个项目，但是因为我的算力不足，我想用HRSC2016数据集，当我把

mmdet/models/backbones/swin.py mmdet/models/backbones/init.py configs/obb/oriented_rcnn/fasxxx.py 等等文件准备好，并且选择好HRSC2016数据集之后，出现了这个问题：

FoundError: [Errno 2] No such file or directory: '/tmp/tmp9tms1rcn/tmpidew67pt.py' (obbdetection) root@container-60cd118dac-91f4b7d2:~/OBBDetection# python tools/train.py configs/obb/oriented_rcnn/faster_rcnn_orpn_swin_fpn_3x_hrsc.py --work-dir work_dirs Traceback (most recent call last): File "/root/miniconda3/envs/obbdetection/lib/python3.7/site-packages/mmcv/utils/config.py", line 101, in _validate_py_syntax ast.parse(content) File "/root/miniconda3/envs/obbdetection/lib/python3.7/ast.py", line 35, in parse return compile(source, filename, mode, PyCF_ONLY_AST) File "", line 80 train_cfg = dict( ^ SyntaxError: invalid syntax

During handling of the above exception, another exception occurred:

Traceback (most recent call last): File "tools/train.py", line 153, in main() File "tools/train.py", line 64, in main cfg = Config.fromfile(args.config) File "/root/miniconda3/envs/obbdetection/lib/python3.7/site-packages/mmcv/utils/config.py", line 332, in fromfile use_predefined_variables) File "/root/miniconda3/envs/obbdetection/lib/python3.7/site-packages/mmcv/utils/config.py", line 205, in _file2dict Config._validate_py_syntax(filename) File "/root/miniconda3/envs/obbdetection/lib/python3.7/site-packages/mmcv/utils/config.py", line 103, in _validate_py_syntax raise SyntaxError('There are syntax errors in config ' SyntaxError: There are syntax errors in config file /root/OBBDetection/configs/obb/oriented_rcnn/faster_rcnn_orpn_swin_fpn_3x_hrsc.py: invalid syntax (, line 80) Exception ignored in: <function _TemporaryFileCloser.del at 0x7f7604d4aef0> Traceback (most recent call last): File "/root/miniconda3/envs/obbdetection/lib/python3.7/tempfile.py", line 448, in del self.close() File "/root/miniconda3/envs/obbdetection/lib/python3.7/tempfile.py", line 444, in close unlink(self.name) FileNotFoundError: [Errno 2] No such file or directory: '/tmp/tmp5luxzbce/tmp2lvn83mu.py' (obbdetection) root@container-60cd118dac-91f4b7d2:~/OBBDetection#

我把pretrain和optimal等注释掉了，也是不行：

base = [

'../base/datasets/dota.py',

'../base/schedules/schedule_1x.py',

'../../base/default_runtime.py'

]

base = [ '../base/datasets/hrsc.py', '../base/schedules/schedule_3x.py', '../../base/default_runtime.py' ] model = dict( type='OrientedRCNN', backbone=dict( type='SwinTransformer', embed_dims=96, depths=[2, 2, 6, 2], num_heads=[3, 6, 12, 24], window_size=7, mlp_ratio=4, qkv_bias=True, qk_scale=None, drop_rate=0., attn_drop_rate=0., drop_path_rate=0.2, patch_norm=True, out_indices=(0, 1, 2, 3), with_cp=False, convert_weights=True, # init_cfg=dict(type='Pretrained', checkpoint='swin_tiny_patch4_window7_224.pth')),

neck=dict(
    type='FPN',
    in_channels=[96, 192, 384, 768],
    out_channels=256,
    num_outs=5),
rpn_head=dict(
    type='OrientedRPNHead',
    in_channels=256,
    feat_channels=256,
    anchor_generator=dict(
        type='AnchorGenerator',
        scales=[6],
        ratios=[0.5, 1.0, 2.0],
        strides=[4, 8, 16, 32, 64]),
    bbox_coder=dict(
        type='MidpointOffsetCoder',
        target_means=[.0, .0, .0, .0, .0, .0],
        target_stds=[1.0, 1.0, 1.0, 1.0, 0.5, 0.5]),
    loss_cls=dict(
        type='CrossEntropyLoss', use_sigmoid=True, loss_weight=1.0),
    loss_bbox=dict(type='SmoothL1Loss', beta=1.0 / 9.0, loss_weight=1.0)),
roi_head=dict(
    type='OBBStandardRoIHead',
    bbox_roi_extractor=dict(
        type='OBBSingleRoIExtractor',
        roi_layer=dict(type='RoIAlignRotated', out_size=7, sample_num=2),
        out_channels=256,
        extend_factor=(1.4, 1.2),
        featmap_strides=[4, 8, 16, 32]),
    bbox_head=dict(
        type='OBBShared2FCBBoxHead',
        start_bbox_type='obb',
        end_bbox_type='obb',
        in_channels=256,
        fc_out_channels=1024,
        roi_feat_size=7,
        num_classes=33,
        bbox_coder=dict(
            type='OBB2OBBDeltaXYWHTCoder',
            target_means=[0., 0., 0., 0., 0.],
            target_stds=[0.1, 0.1, 0.2, 0.2, 0.1]),
        reg_class_agnostic=True,
        loss_cls=dict(
            type='CrossEntropyLoss',
            use_sigmoid=False,
            loss_weight=1.0),
        loss_bbox=dict(type='SmoothL1Loss', beta=1.0,
                       loss_weight=1.0))))

model training and testing settings

train_cfg = dict( rpn=dict( assigner=dict( type='MaxIoUAssigner', pos_iou_thr=0.7, neg_iou_thr=0.3, min_pos_iou=0.3, match_low_quality=True, gpu_assign_thr=200, ignore_iof_thr=-1), sampler=dict( type='RandomSampler', num=256, pos_fraction=0.5, neg_pos_ub=-1, add_gt_as_proposals=False), allowed_border=0, pos_weight=-1, debug=False), rpn_proposal=dict( nms_across_levels=False, nms_pre=2000, nms_post=2000, max_num=2000, nms_thr=0.8, min_bbox_size=0), rcnn=dict( assigner=dict( type='MaxIoUAssigner', pos_iou_thr=0.5, neg_iou_thr=0.5, min_pos_iou=0.5, match_low_quality=False, ignore_iof_thr=-1, iou_calculator=dict(type='OBBOverlaps')), sampler=dict( type='OBBRandomSampler', num=512, pos_fraction=0.25, neg_pos_ub=-1, add_gt_as_proposals=True), pos_weight=-1, debug=False)) test_cfg = dict( rpn=dict( nms_across_levels=False, nms_pre=2000, nms_post=2000, max_num=2000, nms_thr=0.8, min_bbox_size=0), rcnn=dict( score_thr=0.005, nms=dict(type='obb_nms', iou_thr=0.1), max_per_img=2000))

optimizer = dict(

delete=True,

type='AdamW',

lr=0.0001,

betas=(0.9, 0.999),

weight_decay=0.05,

paramwise_cfg=dict(

custom_keys={

'absolute_pos_embed': dict(decay_mult=0.),

'relative_position_bias_table': dict(decay_mult=0.),

'norm': dict(decay_mult=0.)

}))

lr_config = dict(warmup_iters=1000, step=[9, 11])

runner = dict(max_epochs=12)

请问这个文件是干什么的？

您好，我想请问您在对FAIR1M数据集做数据增强的时候使用的是toolbox里面的smart_augment.py吗？如果直接用原图进行增强的话，我使用时每一张图片的增强产生的数量实在是太多了，感觉不太对，请问您当时比赛的时候具体是使用了toolbox中的哪一个文件如何进行的增强呢，十分想完成一下复现，感谢了！（同时我看您博文中提到了随机缩放的方法，请问它对应的增强函数是哪一个呀？）

如果方便，希望能跟您加个微信学习一下！！