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configs/table/SLANet_lcnetv2.yml
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139
configs/table/SLANet_lcnetv2.yml
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Global:
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use_gpu: true
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epoch_num: 50
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log_smooth_window: 20
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print_batch_step: 10
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save_model_dir: ./output/SLANet_lcnetv2
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save_epoch_step: 20
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# evaluation is run every 1000 iterations after the 0th iteration
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eval_batch_step: [0, 1000]
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cal_metric_during_train: True
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pretrained_model:
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checkpoints:
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save_inference_dir: ./SLANet_lcnetv2_infer
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use_visualdl: False
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infer_img: ppstructure/docs/table/table.jpg
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# for data or label process
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character_dict_path: ppocr/utils/dict/table_structure_dict.txt
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character_type: en
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max_text_length: &max_text_length 500
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box_format: &box_format 'xyxy' # 'xywh', 'xyxy', 'xyxyxyxy'
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infer_mode: False
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use_sync_bn: True
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save_res_path: 'output/infer'
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d2s_train_image_shape: [3, -1, -1]
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amp_custom_white_list: ['concat', 'elementwise_sub', 'set_value']
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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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clip_norm: 5.0
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lr:
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learning_rate: 0.001
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regularizer:
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name: 'L2'
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factor: 0.00000
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Architecture:
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model_type: table
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algorithm: SLANet
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Backbone:
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name: PPLCNetV2_base
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Neck:
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name: CSPPAN
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out_channels: 96
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Head:
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name: SLAHead
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hidden_size: 256
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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: SLALoss
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structure_weight: 1.0
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loc_weight: 2.0
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loc_loss: smooth_l1
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PostProcess:
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name: TableLabelDecode
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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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loc_reg_num: *loc_reg_num
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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: ../table_data/pubtabnet/train/
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label_file_list: [../table_data/pubtabnet/PubTabNet_2.0.0_train.jsonl]
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transforms:
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- DecodeImage: # load image
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img_mode: BGR
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channel_first: False
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- TableLabelEncode:
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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: False
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loc_reg_num: *loc_reg_num
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max_text_length: *max_text_length
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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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- ResizeTableImage:
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max_len: 488
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- NormalizeImage:
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scale: 1./255.
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mean: [0.485, 0.456, 0.406]
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std: [0.229, 0.224, 0.225]
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order: 'hwc'
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- PaddingTableImage:
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size: [488, 488]
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- ToCHWImage:
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- KeepKeys:
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keep_keys: [ 'image', 'structure', 'bboxes', 'bbox_masks', 'length', 'shape' ]
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loader:
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shuffle: True
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batch_size_per_card: 24
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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: ../table_data/pubtabnet/val/
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label_file_list: [../table_data/pubtabnet/PubTabNet_2.0.0_val.jsonl]
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transforms:
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- DecodeImage: # load image
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img_mode: BGR
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channel_first: False
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- TableLabelEncode:
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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: False
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loc_reg_num: *loc_reg_num
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max_text_length: *max_text_length
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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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- ResizeTableImage:
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max_len: 488
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- NormalizeImage:
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scale: 1./255.
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mean: [0.485, 0.456, 0.406]
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std: [0.229, 0.224, 0.225]
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order: 'hwc'
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- PaddingTableImage:
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size: [488, 488]
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- ToCHWImage:
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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: 48
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num_workers: 4
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