mirror of https://github.com/open-mmlab/mmocr.git
45 lines
1.4 KiB
Python
45 lines
1.4 KiB
Python
model = dict(
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type='FCENet',
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backbone=dict(
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type='mmdet.ResNet',
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depth=50,
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num_stages=4,
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out_indices=(1, 2, 3),
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frozen_stages=-1,
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norm_cfg=dict(type='BN', requires_grad=True),
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norm_eval=True,
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style='pytorch',
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dcn=dict(type='DCNv2', deform_groups=2, fallback_on_stride=False),
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init_cfg=dict(type='Pretrained', checkpoint='torchvision://resnet50'),
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stage_with_dcn=(False, True, True, True)),
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neck=dict(
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type='mmdet.FPN',
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in_channels=[512, 1024, 2048],
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out_channels=256,
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add_extra_convs='on_output',
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num_outs=3,
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relu_before_extra_convs=True,
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act_cfg=None),
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det_head=dict(
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type='FCEHead',
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in_channels=256,
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fourier_degree=5,
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module_loss=dict(
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type='FCEModuleLoss',
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num_sample=50,
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level_proportion_range=((0, 0.25), (0.2, 0.65), (0.55, 1.0))),
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postprocessor=dict(
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type='FCEPostprocessor',
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scales=(8, 16, 32),
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text_repr_type='poly',
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num_reconstr_points=50,
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alpha=1.0,
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beta=2.0,
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score_thr=0.3)),
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data_preprocessor=dict(
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type='TextDetDataPreprocessor',
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mean=[123.675, 116.28, 103.53],
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std=[58.395, 57.12, 57.375],
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bgr_to_rgb=True,
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pad_size_divisor=32))
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