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| model = dict( | |
| type='DBNet', | |
| backbone=dict( | |
| type='mmdet.ResNet', | |
| depth=18, | |
| num_stages=4, | |
| out_indices=(0, 1, 2, 3), | |
| frozen_stages=-1, | |
| norm_cfg=dict(type='BN', requires_grad=True), | |
| init_cfg=dict(type='Pretrained', checkpoint='torchvision://resnet18'), | |
| norm_eval=False, | |
| style='caffe'), | |
| neck=dict( | |
| type='FPNC', in_channels=[64, 128, 256, 512], lateral_channels=256), | |
| det_head=dict( | |
| type='DBHead', | |
| in_channels=256, | |
| module_loss=dict(type='DBModuleLoss'), | |
| postprocessor=dict(type='DBPostprocessor', text_repr_type='quad')), | |
| data_preprocessor=dict( | |
| type='TextDetDataPreprocessor', | |
| mean=[123.675, 116.28, 103.53], | |
| std=[58.395, 57.12, 57.375], | |
| bgr_to_rgb=True, | |
| pad_size_divisor=32)) | |
| train_pipeline = [ | |
| dict(type='LoadImageFromFile', color_type='color_ignore_orientation'), | |
| dict( | |
| type='LoadOCRAnnotations', | |
| with_polygon=True, | |
| with_bbox=True, | |
| with_label=True, | |
| ), | |
| dict( | |
| type='TorchVisionWrapper', | |
| op='ColorJitter', | |
| brightness=32.0 / 255, | |
| saturation=0.5), | |
| dict( | |
| type='ImgAugWrapper', | |
| args=[['Fliplr', 0.5], | |
| dict(cls='Affine', rotate=[-10, 10]), ['Resize', [0.5, 3.0]]]), | |
| dict(type='RandomCrop', min_side_ratio=0.1), | |
| dict(type='Resize', scale=(640, 640), keep_ratio=True), | |
| dict(type='Pad', size=(640, 640)), | |
| dict( | |
| type='PackTextDetInputs', | |
| meta_keys=('img_path', 'ori_shape', 'img_shape')) | |
| ] | |
| test_pipeline = [ | |
| dict(type='LoadImageFromFile', color_type='color_ignore_orientation'), | |
| dict(type='Resize', scale=(1333, 736), keep_ratio=True), | |
| dict( | |
| type='LoadOCRAnnotations', | |
| with_polygon=True, | |
| with_bbox=True, | |
| with_label=True, | |
| ), | |
| dict( | |
| type='PackTextDetInputs', | |
| meta_keys=('img_path', 'ori_shape', 'img_shape', 'scale_factor')) | |
| ] | |