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_base_ = ['../../_base_/default_runtime.py'] | |
model = dict( | |
type='SDMGR', | |
backbone=dict(type='UNet', base_channels=16), | |
bbox_head=dict( | |
type='SDMGRHead', visual_dim=16, num_chars=92, num_classes=4), | |
visual_modality=False, | |
train_cfg=None, | |
test_cfg=None, | |
class_list=None, | |
openset=True) | |
optimizer = dict(type='Adam', weight_decay=0.0001) | |
optimizer_config = dict(grad_clip=None) | |
lr_config = dict( | |
policy='step', | |
warmup='linear', | |
warmup_iters=1, | |
warmup_ratio=1, | |
step=[40, 50]) | |
total_epochs = 60 | |
train_pipeline = [ | |
dict(type='LoadAnnotations'), | |
dict(type='ResizeNoImg', img_scale=(1024, 512), keep_ratio=True), | |
dict(type='KIEFormatBundle'), | |
dict( | |
type='Collect', | |
keys=['img', 'relations', 'texts', 'gt_bboxes', 'gt_labels'], | |
meta_keys=('filename', 'ori_filename', 'ori_texts')) | |
] | |
test_pipeline = [ | |
dict(type='LoadAnnotations'), | |
dict(type='ResizeNoImg', img_scale=(1024, 512), keep_ratio=True), | |
dict(type='KIEFormatBundle'), | |
dict( | |
type='Collect', | |
keys=['img', 'relations', 'texts', 'gt_bboxes'], | |
meta_keys=('filename', 'ori_filename', 'ori_texts', 'ori_boxes', | |
'img_norm_cfg', 'ori_filename', 'img_shape')) | |
] | |
dataset_type = 'OpensetKIEDataset' | |
data_root = 'data/wildreceipt' | |
loader = dict( | |
type='HardDiskLoader', | |
repeat=1, | |
parser=dict( | |
type='LineJsonParser', | |
keys=['file_name', 'height', 'width', 'annotations'])) | |
train = dict( | |
type=dataset_type, | |
ann_file=f'{data_root}/openset_train.txt', | |
pipeline=train_pipeline, | |
img_prefix=data_root, | |
link_type='one-to-many', | |
loader=loader, | |
dict_file=f'{data_root}/dict.txt', | |
test_mode=False) | |
test = dict( | |
type=dataset_type, | |
ann_file=f'{data_root}/openset_test.txt', | |
pipeline=test_pipeline, | |
img_prefix=data_root, | |
link_type='one-to-many', | |
loader=loader, | |
dict_file=f'{data_root}/dict.txt', | |
test_mode=True) | |
data = dict( | |
samples_per_gpu=4, | |
workers_per_gpu=1, | |
val_dataloader=dict(samples_per_gpu=1), | |
test_dataloader=dict(samples_per_gpu=1), | |
train=train, | |
val=test, | |
test=test) | |
evaluation = dict(interval=1, metric='openset_f1', metric_options=None) | |
find_unused_parameters = True | |