Spaces:
Sleeping
Sleeping
File size: 2,622 Bytes
9bf4bd7 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 |
model = dict(
type='TextSnake',
backbone=dict(
type='mmdet.ResNet',
depth=50,
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://resnet50'),
norm_eval=True,
style='caffe'),
neck=dict(
type='FPN_UNet', in_channels=[256, 512, 1024, 2048], out_channels=32),
det_head=dict(
type='TextSnakeHead',
in_channels=32,
module_loss=dict(type='TextSnakeModuleLoss'),
postprocessor=dict(
type='TextSnakePostprocessor', 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_bbox=True,
with_polygon=True,
with_label=True),
dict(
type='TorchVisionWrapper',
op='ColorJitter',
brightness=32.0 / 255,
saturation=0.5),
dict(
type='RandomApply',
transforms=[dict(type='RandomCrop', min_side_ratio=0.3)],
prob=0.65),
dict(
type='RandomRotate',
max_angle=20,
pad_with_fixed_color=False,
use_canvas=True),
dict(
type='BoundedScaleAspectJitter',
long_size_bound=800,
short_size_bound=480,
ratio_range=(0.7, 1.3),
aspect_ratio_range=(0.9, 1.1)),
dict(
type='RandomChoice',
transforms=[[
dict(type='Resize', scale=800, keep_ratio=True),
dict(type='SourceImagePad', target_scale=800)
],
dict(type='Resize', scale=800, keep_ratio=False)],
prob=[0.4, 0.6]),
dict(type='RandomFlip', prob=0.5, direction='horizontal'),
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),
# add loading annotation after ``Resize`` because ground truth
# does not need to do resize data transform
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'))
]
|