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model = dict( | |
type='PSENet', | |
backbone=dict( | |
type='mmdet.ResNet', | |
depth=50, | |
num_stages=4, | |
out_indices=(0, 1, 2, 3), | |
frozen_stages=-1, | |
norm_cfg=dict(type='SyncBN', requires_grad=True), | |
init_cfg=dict(type='Pretrained', checkpoint='torchvision://resnet50'), | |
norm_eval=True, | |
style='caffe'), | |
neck=dict( | |
type='FPNF', | |
in_channels=[256, 512, 1024, 2048], | |
out_channels=256, | |
fusion_type='concat'), | |
det_head=dict( | |
type='PSEHead', | |
in_channels=[256], | |
hidden_dim=256, | |
out_channel=7, | |
module_loss=dict(type='PSEModuleLoss'), | |
postprocessor=dict(type='PSEPostprocessor', text_repr_type='poly')), | |
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='FixInvalidPolygon'), | |
dict(type='ShortScaleAspectJitter', short_size=736, scale_divisor=32), | |
dict(type='RandomFlip', prob=0.5, direction='horizontal'), | |
dict(type='RandomRotate', max_angle=10), | |
dict(type='TextDetRandomCrop', target_size=(736, 736)), | |
dict(type='Pad', size=(736, 736)), | |
dict( | |
type='PackTextDetInputs', | |
meta_keys=('img_path', 'ori_shape', 'img_shape', 'scale_factor')) | |
] | |
test_pipeline = [ | |
dict(type='LoadImageFromFile', color_type='color_ignore_orientation'), | |
dict(type='Resize', scale=(2240, 2240), 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')) | |
] | |