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vit_large_mgpstr_only_char.yml
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Global:
device: gpu
epoch_num: 20
log_smooth_window: 20
print_batch_step: 10
output_dir: ./output/rec/u14m_filter/vit_base_mgpstr_only_char/
eval_epoch_step: [0, 1]
eval_batch_step: [0, 500]
cal_metric_during_train: False
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
max_text_length: &max_text_length 25
use_space_char: &use_space_char False
use_amp: True
save_res_path: ./output/rec/u14m_filter/predicts_vit_mgpstr_only_char.txt
grad_clip_val: 5
Optimizer:
name: Adam
lr: 0.000325 # 4gpus 128bs/gpu
weight_decay: 0.
filter_bias_and_bn: False
LRScheduler:
name: OneCycleLR
warmup_epoch: 1.5 # pct_start 0.075*20 = 1.5ep
cycle_momentum: False
Architecture:
model_type: rec
algorithm: MGPSTR
Transform:
Encoder:
name: ViT
img_size: [32,128]
patch_size: [4, 4]
embed_dim: 1024
depth: 24
num_heads: 16
mlp_ratio: 4
qkv_bias: True
Decoder:
name: MGPDecoder
only_char: &only_char True
Loss:
name: MGPLoss
only_char: *only_char
PostProcess:
name: MPGLabelDecode
character_dict_path: *character_dict_path
use_space_char: *use_space_char
only_char: *only_char
Metric:
name: RecMetric
main_indicator: acc
is_filter: True
Train:
dataset:
name: LMDBDataSet
data_dir: ../Union14M-L-LMDB-Filtered
transforms:
- DecodeImagePIL: # load image
img_mode: RGB
- PARSeqAugPIL:
- MGPLabelEncode: # Class handling label
character_dict_path: *character_dict_path
use_space_char: *use_space_char
max_text_length: *max_text_length
only_char: *only_char
- RecTVResize:
image_shape: [32, 128]
padding: False
- KeepKeys:
keep_keys: ['image', 'char_label', 'length'] # dataloader will return list in this order
loader:
shuffle: True
batch_size_per_card: 128
drop_last: True
num_workers: 4
Eval:
dataset:
name: LMDBDataSet
data_dir: ../evaluation/
transforms:
- DecodeImagePIL: # load image
img_mode: RGB
- MGPLabelEncode: # Class handling label
character_dict_path: *character_dict_path
use_space_char: *use_space_char
max_text_length: *max_text_length
only_char: *only_char
- RecTVResize:
image_shape: [32, 128]
padding: False
- KeepKeys:
keep_keys: ['image', 'char_label', 'length'] # dataloader will return list in this order
loader:
shuffle: False
drop_last: False
batch_size_per_card: 256
num_workers: 2