Delete grounding_dino_swin-t_finetune_8xb2_20e_concrete.py

grounding_dino_swin-t_finetune_8xb2_20e_concrete.py

@@ -1,59 +0,0 @@
-# _base_ = 'grounding_dino_swin-t_finetune_16xb2_1x_coco.py'
-_base_ = './grounding_dino_swin-t_finetune_16xb2_1x_coco.py'
-
-data_root = 'data/concrete_defect/'
-class_name = ('crack', 'corrosion', 'efflorescence', 'pothole', 'spalling')
-num_classes = len(class_name)
-metainfo = dict(classes=class_name,
-                palette=[(244, 108, 59), (99, 102, 129), (249, 193, 0), (160, 180, 0), (115, 82, 59)])
-
-model = dict(bbox_head=dict(num_classes=num_classes))
-
-train_dataloader = dict(
-    dataset=dict(
-        data_root=data_root,
-        metainfo=metainfo,
-        ann_file='annotations/trainval.json',
-        data_prefix=dict(img='images/')))
-
-val_dataloader = dict(
-    dataset=dict(
-        metainfo=metainfo,
-        data_root=data_root,
-        ann_file='annotations/test.json',
-        data_prefix=dict(img='images/')))
-
-test_dataloader = val_dataloader
-
-val_evaluator = dict(ann_file=data_root + 'annotations/test.json')
-test_evaluator = val_evaluator
-
-max_epoch = 20
-
-default_hooks = dict(
-    checkpoint=dict(interval=1, max_keep_ckpts=1, save_best='auto'),
-    logger=dict(type='LoggerHook', interval=5))
-train_cfg = dict(max_epochs=max_epoch, val_interval=1)
-
-param_scheduler = [
-    dict(type='LinearLR', start_factor=0.001, by_epoch=False, begin=0, end=30),
-    dict(
-        type='MultiStepLR',
-        begin=0,
-        end=max_epoch,
-        by_epoch=True,
-        milestones=[15],
-        gamma=0.1)
-]
-
-optim_wrapper = dict(
-    optimizer=dict(lr=0.00005),
-    paramwise_cfg=dict(
-        custom_keys={
-            'absolute_pos_embed': dict(decay_mult=0.),
-            'backbone': dict(lr_mult=0.1),
-            'language_model': dict(lr_mult=0),
-        }))
-
-auto_scale_lr = dict(base_batch_size=16)
-# auto_scale_lr = dict(base_batch_size=4)