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