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Global:
device: gpu
epoch_num: 20
log_smooth_window: 20
print_batch_step: 10
output_dir: ./output/rec/syn/svtr_tiny/
eval_epoch_step: [0, 1]
eval_batch_step: [0, 500]
cal_metric_during_train: True
pretrained_model:
checkpoints:
use_tensorboard: false
infer_img:
# for data or label process
character_dict_path: &character_dict_path ./tools/utils/EN_symbol_dict.txt # 96en
# ./tools/utils/ppocr_keys_v1.txt # ch
max_text_length: &max_text_length 25
use_space_char: &use_space_char False
save_res_path: ./output/rec/syn/predicts_svtr_tiny.txt
use_amp: True
Optimizer:
name: AdamW
lr: 0.0005 # for 4gpus bs256/gpu
weight_decay: 0.05
filter_bias_and_bn: True
LRScheduler:
name: CosineAnnealingLR
warmup_epoch: 2
Architecture:
model_type: rec
algorithm: SVTR
Transform:
Encoder:
name: SVTRNet
img_size: [32, 100]
out_char_num: 25 # W//4 or W//8 or W/12
out_channels: 192
patch_merging: 'Conv'
embed_dim: [64, 128, 256]
depth: [3, 6, 3]
num_heads: [2, 4, 8]
mixer: ['Local','Local','Local','Local','Local','Local','Global','Global','Global','Global','Global','Global']
local_mixer: [[7, 11], [7, 11], [7, 11]]
last_stage: True
prenorm: False
Decoder:
name: CTCDecoder
Loss:
name: CTCLoss
zero_infinity: True
PostProcess:
name: CTCLabelDecode
character_dict_path: *character_dict_path
use_space_char: *use_space_char
Metric:
name: RecMetric
main_indicator: acc
Train:
dataset:
name: STRLMDBDataSet
data_dir: ./
transforms:
- DecodeImage: # load image
img_mode: BGR
channel_first: False
# - SVTRRecAug:
# aug_type: 0 # or 1
- CTCLabelEncode: # Class handling label
character_dict_path: *character_dict_path
use_space_char: *use_space_char
max_text_length: *max_text_length
- SVTRResize:
image_shape: [3, 32, 100]
padding: False
- KeepKeys:
keep_keys: ['image', 'label', 'length'] # dataloader will return list in this order
loader:
shuffle: True
batch_size_per_card: 256
drop_last: True
num_workers: 8
Eval:
dataset:
name: LMDBDataSet
data_dir: ../evaluation/
transforms:
- DecodeImage: # load image
img_mode: BGR
channel_first: False
- CTCLabelEncode: # Class handling label
character_dict_path: *character_dict_path
use_space_char: *use_space_char
max_text_length: *max_text_length
- SVTRResize:
image_shape: [3, 32, 100]
padding: False
- KeepKeys:
keep_keys: ['image', 'label', 'length'] # dataloader will return list in this order
loader:
shuffle: False
drop_last: False
batch_size_per_card: 256
num_workers: 2
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