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table_master.yml
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table_master.yml
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Global:
use_gpu: true
epoch_num: 17
log_smooth_window: 20
print_batch_step: 100
save_model_dir: ./output/table_master/
save_epoch_step: 17
eval_batch_step: [0, 6259]
cal_metric_during_train: true
pretrained_model: null
checkpoints:
save_inference_dir: output/table_master/infer
use_visualdl: false
infer_img: ppstructure/docs/table/table.jpg
save_res_path: ./output/table_master
character_dict_path: ppocr/utils/dict/table_master_structure_dict.txt
infer_mode: false
max_text_length: &max_text_length 500
box_format: &box_format 'xywh' # 'xywh', 'xyxy', 'xyxyxyxy'
d2s_train_image_shape: [3, 480, 480]
Optimizer:
name: Adam
beta1: 0.9
beta2: 0.999
lr:
name: MultiStepDecay
learning_rate: 0.001
milestones: [12, 15]
gamma: 0.1
warmup_epoch: 0.02
regularizer:
name: L2
factor: 0.0
Architecture:
model_type: table
algorithm: TableMaster
Backbone:
name: TableResNetExtra
gcb_config:
ratio: 0.0625
headers: 1
att_scale: False
fusion_type: channel_add
layers: [False, True, True, True]
layers: [1,2,5,3]
Head:
name: TableMasterHead
hidden_size: 512
headers: 8
dropout: 0
d_ff: 2024
max_text_length: *max_text_length
loc_reg_num: &loc_reg_num 4
Loss:
name: TableMasterLoss
ignore_index: 42 # set to len of dict + 3
PostProcess:
name: TableMasterLabelDecode
box_shape: pad
merge_no_span_structure: &merge_no_span_structure True
Metric:
name: TableMetric
main_indicator: acc
compute_bbox_metric: False
box_format: *box_format
Train:
dataset:
name: PubTabDataSet
data_dir: train_data/table/pubtabnet/train/
label_file_list: [train_data/table/pubtabnet/PubTabNet_2.0.0_train.jsonl]
transforms:
- DecodeImage:
img_mode: BGR
channel_first: False
- TableMasterLabelEncode:
learn_empty_box: False
merge_no_span_structure: *merge_no_span_structure
replace_empty_cell_token: True
loc_reg_num: *loc_reg_num
max_text_length: *max_text_length
- ResizeTableImage:
max_len: 480
resize_bboxes: True
- PaddingTableImage:
size: [480, 480]
- TableBoxEncode:
in_box_format: *box_format
out_box_format: *box_format
- NormalizeImage:
scale: 1./255.
mean: [0.5, 0.5, 0.5]
std: [0.5, 0.5, 0.5]
order: hwc
- ToCHWImage: null
- KeepKeys:
keep_keys: [image, structure, bboxes, bbox_masks, shape]
loader:
shuffle: True
batch_size_per_card: 10
drop_last: True
num_workers: 8
Eval:
dataset:
name: PubTabDataSet
data_dir: train_data/table/pubtabnet/val/
label_file_list: [train_data/table/pubtabnet/PubTabNet_2.0.0_val.jsonl]
transforms:
- DecodeImage:
img_mode: BGR
channel_first: False
- TableMasterLabelEncode:
learn_empty_box: False
merge_no_span_structure: *merge_no_span_structure
replace_empty_cell_token: True
loc_reg_num: *loc_reg_num
max_text_length: *max_text_length
- ResizeTableImage:
max_len: 480
resize_bboxes: True
- PaddingTableImage:
size: [480, 480]
- TableBoxEncode:
in_box_format: *box_format
out_box_format: *box_format
- NormalizeImage:
scale: 1./255.
mean: [0.5, 0.5, 0.5]
std: [0.5, 0.5, 0.5]
order: hwc
- ToCHWImage: null
- KeepKeys:
keep_keys: [image, structure, bboxes, bbox_masks, shape]
loader:
shuffle: False
drop_last: False
batch_size_per_card: 10
num_workers: 8