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Updated Recognition Competition Model Link (#13259)
* Updated Recognition Competition Model Link * Updated Recognition Competition Model Link * Updated Recognition Competition Model Link
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‎configs/rec/SVTRv2/rec_repsvtr_ch.yml‎

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Global:
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debug: false
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use_gpu: true
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epoch_num: 200
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log_smooth_window: 20
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print_batch_step: 10
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save_model_dir: ./output/rec_repsvtr_ch
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save_epoch_step: 10
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eval_batch_step: [0, 1000]
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cal_metric_during_train: False
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pretrained_model:
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checkpoints:
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save_inference_dir:
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use_visualdl: false
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infer_img: doc/imgs_words/ch/word_1.jpg
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character_dict_path: ppocr/utils/ppocr_keys_v1.txt
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max_text_length: &max_text_length 25
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infer_mode: false
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use_space_char: true
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distributed: true
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save_res_path: ./output/rec/predicts_repsvtr.txt
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Optimizer:
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name: AdamW
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beta1: 0.9
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beta2: 0.999
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epsilon: 1.e-8
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weight_decay: 0.025
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no_weight_decay_name: norm
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one_dim_param_no_weight_decay: True
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lr:
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name: Cosine
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learning_rate: 0.001 # 8gpus 192bs
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warmup_epoch: 5
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Architecture:
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model_type: rec
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algorithm: SVTR_HGNet
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Transform:
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Backbone:
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name: RepSVTR
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Head:
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name: MultiHead
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head_list:
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- CTCHead:
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Neck:
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name: svtr
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dims: 256
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depth: 2
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hidden_dims: 256
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kernel_size: [1, 3]
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use_guide: True
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Head:
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fc_decay: 0.00001
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- NRTRHead:
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nrtr_dim: 384
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max_text_length: *max_text_length
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num_decoder_layers: 2
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Loss:
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name: MultiLoss
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loss_config_list:
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- CTCLoss:
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- NRTRLoss:
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PostProcess:
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name: CTCLabelDecode
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Metric:
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name: RecMetric
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main_indicator: acc
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Train:
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dataset:
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name: MultiScaleDataSet
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ds_width: false
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data_dir: ./train_data/
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ext_op_transform_idx: 1
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label_file_list:
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- ./train_data/train_list.txt
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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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- RecAug:
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- MultiLabelEncode:
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gtc_encode: NRTRLabelEncode
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- KeepKeys:
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keep_keys:
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- image
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- label_ctc
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- label_gtc
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- length
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- valid_ratio
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sampler:
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name: MultiScaleSampler
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scales: [[320, 32], [320, 48], [320, 64]]
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first_bs: &bs 192
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fix_bs: false
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divided_factor: [8, 16] # w, h
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is_training: True
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loader:
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shuffle: true
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batch_size_per_card: *bs
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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: SimpleDataSet
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data_dir: ./train_data
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label_file_list:
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- ./train_data/val_list.txt
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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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- MultiLabelEncode:
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gtc_encode: NRTRLabelEncode
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- RecResizeImg:
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image_shape: [3, 48, 320]
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- KeepKeys:
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keep_keys:
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- image
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- label_ctc
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- label_gtc
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- length
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- valid_ratio
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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: 128
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num_workers: 4

‎configs/rec/SVTRv2/rec_svtrv2_ch.yml‎

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Global:
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debug: false
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use_gpu: true
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epoch_num: 200
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log_smooth_window: 20
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print_batch_step: 10
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save_model_dir: ./output/rec_svtrv2_ch
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save_epoch_step: 10
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eval_batch_step: [0, 1000]
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cal_metric_during_train: False
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pretrained_model:
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checkpoints:
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save_inference_dir:
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use_visualdl: false
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infer_img: doc/imgs_words/ch/word_1.jpg
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character_dict_path: ppocr/utils/ppocr_keys_v1.txt
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max_text_length: &max_text_length 25
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infer_mode: false
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use_space_char: true
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distributed: true
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save_res_path: ./output/rec/predicts_svrtv2.txt
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Optimizer:
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name: AdamW
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beta1: 0.9
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beta2: 0.999
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epsilon: 1.e-8
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weight_decay: 0.05
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no_weight_decay_name: norm
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one_dim_param_no_weight_decay: True
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lr:
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name: Cosine
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learning_rate: 0.001 # 8gpus 192bs
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warmup_epoch: 5
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Architecture:
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model_type: rec
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algorithm: SVTR_HGNet
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Transform:
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Backbone:
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name: SVTRv2
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use_pos_embed: False
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dims: [128, 256, 384]
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depths: [6, 6, 6]
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num_heads: [4, 8, 12]
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mixer: [['Conv','Conv','Conv','Conv','Conv','Conv'],['Conv','Conv','Global','Global','Global','Global'],['Global','Global','Global','Global','Global','Global']]
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local_k: [[5, 5], [5, 5], [-1, -1]]
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sub_k: [[2, 1], [2, 1], [-1, -1]]
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last_stage: False
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use_pool: True
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Head:
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name: MultiHead
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head_list:
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- CTCHead:
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Neck:
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name: svtr
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dims: 256
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depth: 2
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hidden_dims: 256
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kernel_size: [1, 3]
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use_guide: True
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Head:
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fc_decay: 0.00001
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- NRTRHead:
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nrtr_dim: 384
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max_text_length: *max_text_length
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num_decoder_layers: 2
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Loss:
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name: MultiLoss
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loss_config_list:
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- CTCLoss:
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- NRTRLoss:
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PostProcess:
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name: CTCLabelDecode
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Metric:
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name: RecMetric
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main_indicator: acc
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Train:
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dataset:
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name: MultiScaleDataSet
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ds_width: false
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data_dir: ./train_data/
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ext_op_transform_idx: 1
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label_file_list:
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- ./train_data/train_list.txt
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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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- RecAug:
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- MultiLabelEncode:
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gtc_encode: NRTRLabelEncode
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- KeepKeys:
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keep_keys:
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- image
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- label_ctc
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- label_gtc
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- length
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- valid_ratio
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sampler:
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name: MultiScaleSampler
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scales: [[320, 32], [320, 48], [320, 64]]
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first_bs: &bs 192
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fix_bs: false
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divided_factor: [8, 16] # w, h
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is_training: True
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loader:
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shuffle: true
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batch_size_per_card: *bs
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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: SimpleDataSet
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data_dir: ./train_data
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label_file_list:
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- ./train_data/val_list.txt
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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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- MultiLabelEncode:
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gtc_encode: NRTRLabelEncode
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- RecResizeImg:
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image_shape: [3, 48, 320]
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- KeepKeys:
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keep_keys:
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- image
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- label_ctc
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- label_gtc
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- length
138+
- valid_ratio
139+
loader:
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shuffle: false
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drop_last: false
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batch_size_per_card: 128
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num_workers: 4

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