mirror of https://github.com/open-mmlab/mmocr.git
65 lines
2.0 KiB
Python
65 lines
2.0 KiB
Python
model = dict(
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type='DBNet',
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backbone=dict(
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type='mmdet.ResNet',
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depth=18,
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num_stages=4,
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out_indices=(0, 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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init_cfg=dict(type='Pretrained', checkpoint='torchvision://resnet18'),
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norm_eval=False,
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style='caffe'),
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neck=dict(
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type='FPNC', in_channels=[64, 128, 256, 512], lateral_channels=256),
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det_head=dict(
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type='DBHead',
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in_channels=256,
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module_loss=dict(type='DBModuleLoss'),
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postprocessor=dict(type='DBPostprocessor', text_repr_type='quad')),
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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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train_pipeline = [
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dict(type='LoadImageFromFile', color_type='color_ignore_orientation'),
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dict(
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type='LoadOCRAnnotations',
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with_polygon=True,
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with_bbox=True,
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with_label=True,
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),
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dict(
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type='TorchVisionWrapper',
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op='ColorJitter',
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brightness=32.0 / 255,
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saturation=0.5),
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dict(
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type='ImgAugWrapper',
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args=[['Fliplr', 0.5],
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dict(cls='Affine', rotate=[-10, 10]), ['Resize', [0.5, 3.0]]]),
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dict(type='RandomCrop', min_side_ratio=0.1),
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dict(type='Resize', scale=(640, 640), keep_ratio=True),
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dict(type='Pad', size=(640, 640)),
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dict(
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type='PackTextDetInputs',
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meta_keys=('img_path', 'ori_shape', 'img_shape'))
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]
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test_pipeline = [
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dict(type='LoadImageFromFile', color_type='color_ignore_orientation'),
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dict(type='Resize', scale=(1333, 736), keep_ratio=True),
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dict(
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type='LoadOCRAnnotations',
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with_polygon=True,
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with_bbox=True,
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with_label=True,
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),
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dict(
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type='PackTextDetInputs',
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meta_keys=('img_path', 'ori_shape', 'img_shape', 'scale_factor'))
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]
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