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ch_PP-OCRv3_rec.yml
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ch_PP-OCRv3_rec.yml
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Global:
device: gpu
epoch_num: 500
log_smooth_window: 20
print_batch_step: 10
output_dir: ./output/rec/rec_ppocr_v3
eval_epoch_step: [0, 1]
cal_metric_during_train: true
pretrained_model:
checkpoints:
use_tensorboard: false
infer_mode: false
infer_img: doc/imgs_words/ch/word_1.jpg
character_dict_path: &character_dict_path ppocr/utils/ppocr_keys_v1.txt
max_text_length: &max_text_length 25
use_space_char: &use_space_char true
Export:
export_dir:
export_shape: [ 1, 3, 48, 320 ]
dynamic_axes: [ 0, 2, 3 ]
Optimizer:
name: Adam
lr: 0.001
weight_decay: 3.0e-05
LRScheduler:
name: CosineAnnealingLR
warmup_epoch: 5
Architecture:
model_type: rec
algorithm: SVTR_LCNet
Transform:
Backbone:
name: MobileNetV1Enhance
scale: 0.5
last_conv_stride: [1, 2]
last_pool_type: avg
last_pool_kernel_size: [2, 2]
Head:
name: MultiHead
head_list:
- CTCHead:
Neck:
name: svtr
dims: 64
depth: 2
hidden_dims: 120
use_guide: True
- SARHead:
enc_dim: 512
max_text_length: *max_text_length
Loss:
name: MultiLoss
loss_config_list:
- CTCLoss:
- SARLoss:
PostProcess:
name: CTCLabelDecode
character_dict_path: *character_dict_path
use_space_char: *use_space_char
Metric:
name: RecMetric
main_indicator: acc
ignore_space: False
Train:
dataset:
name: SimpleDataSet
data_dir: ./train_data
label_file_list:
- ./train_data/train_list.txt
ext_op_transform_idx: 1
transforms:
- DecodeImage:
img_mode: BGR
channel_first: false
- RecConAug:
prob: 0.5
ext_data_num: 2
image_shape: [48, 320, 3]
max_text_length: *max_text_length
- RecAug:
- MultiLabelEncode:
- RecResizeImg:
image_shape: [3, 48, 320]
- KeepKeys:
keep_keys: [image, label_ctc, label_sar, length, valid_ratio]
loader:
shuffle: true
batch_size_per_card: 128
drop_last: true
num_workers: 4
Eval:
dataset:
name: SimpleDataSet
data_dir: ./train_data/
ext_op_transform_idx: 1
label_file_list:
- ./train_data/val_list.txt
transforms:
- DecodeImage:
img_mode: BGR
channel_first: false
- MultiLabelEncode:
- RecResizeImg:
image_shape: [3, 48, 320]
- KeepKeys:
keep_keys: [ image, label_ctc, label_sar, length, valid_ratio ]
loader:
shuffle: false
drop_last: false
batch_size_per_card: 128
num_workers: 4