| 1234567891011121314151617181920212223242526272829303132333435363738394041424344454647484950515253545556575859606162636465666768697071727374757677787980818283848586878889909192939495969798 |
- Global:
- device: gpu
- epoch_num: 20
- log_smooth_window: 20
- print_batch_step: 10
- output_dir: ./output/rec/u14m_filter/resnet45_fpn_dan/
- 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: ./tools/utils/EN_symbol_dict.txt
- max_text_length: 25
- use_space_char: False
- save_res_path: ./output/rec/u14m_filter/predicts_resnet45_fpn_dan.txt
- use_amp: True
- grad_clip_val: 20
- Optimizer:
- name: Adam
- lr: 0.00065 # for 4gpus bs256/gpu
- weight_decay: 0.0
- 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: DAN
- Transform:
- Encoder:
- name: ResNet45
- in_channels: 3
- strides: [2, 1, 2, 1, 1]
- return_list: True
- Decoder:
- name: DANDecoder
- max_len: 25
- channels_list: [64, 128, 256, 512]
- strides_list: [[2, 2], [1, 1], [1, 1]]
- in_shape: [8, 32]
- depth: 4
- Loss:
- name: ARLoss
- PostProcess:
- name: ARLabelDecode
- 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:
- - ARLabelEncode:
- - RecTVResize:
- image_shape: [32, 128]
- 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: 4
- Eval:
- dataset:
- name: LMDBDataSet
- data_dir: ../evaluation
- transforms:
- - DecodeImagePIL: # load image
- img_mode: RGB
- - ARLabelEncode:
- - RecTVResize:
- image_shape: [32, 128]
- 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
|
