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rec_d28_can.yml
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rec_d28_can.yml
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Global:
use_gpu: True
epoch_num: 240
log_smooth_window: 20
print_batch_step: 10
save_model_dir: ./output/rec/can/
save_epoch_step: 1
# evaluation is run every 1105 iterations (1 epoch)(batch_size = 8)
eval_batch_step: [0, 1105]
cal_metric_during_train: True
pretrained_model:
checkpoints:
save_inference_dir:
use_visualdl: False
infer_img: doc/datasets/crohme_demo/hme_00.jpg
# for data or label process
character_dict_path: ppocr/utils/dict/latex_symbol_dict.txt
max_text_length: 36
infer_mode: False
use_space_char: False
save_res_path: ./output/rec/predicts_can.txt
Optimizer:
name: Momentum
momentum: 0.9
clip_norm_global: 100.0
lr:
name: TwoStepCosine
learning_rate: 0.01
warmup_epoch: 1
weight_decay: 0.0001
Architecture:
model_type: rec
algorithm: CAN
in_channels: 1
Transform:
Backbone:
name: DenseNet
growthRate: 24
reduction: 0.5
bottleneck: True
use_dropout: True
input_channel: 1
Head:
name: CANHead
in_channel: 684
out_channel: 111
max_text_length: 36
ratio: 16
attdecoder:
is_train: True
input_size: 256
hidden_size: 256
encoder_out_channel: 684
dropout: True
dropout_ratio: 0.5
word_num: 111
counting_decoder_out_channel: 111
attention:
attention_dim: 512
word_conv_kernel: 1
Loss:
name: CANLoss
PostProcess:
name: CANLabelDecode
Metric:
name: CANMetric
main_indicator: exp_rate
Train:
dataset:
name: SimpleDataSet
data_dir: ./train_data/CROHME/training/images/
label_file_list: ["./train_data/CROHME/training/labels.txt"]
transforms:
- DecodeImage:
channel_first: False
- NormalizeImage:
mean: [0,0,0]
std: [1,1,1]
order: 'hwc'
- GrayImageChannelFormat:
inverse: True
- CANLabelEncode:
lower: False
- KeepKeys:
keep_keys: ['image', 'label']
loader:
shuffle: True
batch_size_per_card: 8
drop_last: False
num_workers: 4
collate_fn: DyMaskCollator
Eval:
dataset:
name: SimpleDataSet
data_dir: ./train_data/CROHME/evaluation/images/
label_file_list: ["./train_data/CROHME/evaluation/labels.txt"]
transforms:
- DecodeImage:
channel_first: False
- NormalizeImage:
mean: [0,0,0]
std: [1,1,1]
order: 'hwc'
- GrayImageChannelFormat:
inverse: True
- CANLabelEncode:
lower: False
- KeepKeys:
keep_keys: ['image', 'label']
loader:
shuffle: False
drop_last: False
batch_size_per_card: 1
num_workers: 4
collate_fn: DyMaskCollator