PaddleOCR/configs/rec/rec_icdar15_train.yml

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YAML
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Global:
algorithm: CRNN
use_gpu: true
epoch_num: 1000
log_smooth_window: 20
print_batch_step: 10
save_model_dir: ./output/rec_CRNN
save_epoch_step: 300
eval_batch_step: 500
train_batch_size_per_card: 256
test_batch_size_per_card: 256
image_shape: [3, 32, 100]
max_text_length: 25
character_type: en
loss_type: ctc
distort: true
reader_yml: ./configs/rec/rec_icdar15_reader.yml
pretrain_weights: ./pretrain_models/rec_mv3_none_bilstm_ctc/best_accuracy
checkpoints:
save_inference_dir:
infer_img:
Architecture:
function: ppocr.modeling.architectures.rec_model,RecModel
Backbone:
function: ppocr.modeling.backbones.rec_mobilenet_v3,MobileNetV3
scale: 0.5
model_name: large
Head:
function: ppocr.modeling.heads.rec_ctc_head,CTCPredict
encoder_type: rnn
SeqRNN:
hidden_size: 96
Loss:
function: ppocr.modeling.losses.rec_ctc_loss,CTCLoss
Optimizer:
function: ppocr.optimizer,AdamDecay
base_lr: 0.0005
beta1: 0.9
beta2: 0.999
decay:
function: cosine_decay
step_each_epoch: 20
total_epoch: 1000