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* openocr compti code * update config and repsvtr * svtrv2 doc
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Global: | ||
debug: false | ||
use_gpu: true | ||
epoch_num: &epoch_num 500 | ||
log_smooth_window: 20 | ||
print_batch_step: 100 | ||
save_model_dir: ./output/det_repsvtr_db | ||
save_epoch_step: 10 | ||
eval_batch_step: | ||
- 0 | ||
- 1000 | ||
cal_metric_during_train: false | ||
checkpoints: | ||
pretrained_model: | ||
save_inference_dir: null | ||
use_visualdl: false | ||
infer_img: doc/imgs_en/img_10.jpg | ||
save_res_path: ./checkpoints/det_db/predicts_db.txt | ||
distributed: true | ||
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Architecture: | ||
model_type: det | ||
algorithm: DB | ||
Transform: null | ||
Backbone: | ||
name: RepSVTR_det | ||
Neck: | ||
name: RSEFPN | ||
out_channels: 96 | ||
shortcut: True | ||
Head: | ||
name: DBHead | ||
k: 50 | ||
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Loss: | ||
name: DBLoss | ||
balance_loss: true | ||
main_loss_type: DiceLoss | ||
alpha: 5 | ||
beta: 10 | ||
ohem_ratio: 3 | ||
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Optimizer: | ||
name: Adam | ||
beta1: 0.9 | ||
beta2: 0.999 | ||
lr: | ||
name: Cosine | ||
learning_rate: 0.001 #(8*8c) | ||
warmup_epoch: 2 | ||
regularizer: | ||
name: L2 | ||
factor: 5.0e-05 | ||
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PostProcess: | ||
name: DBPostProcess | ||
thresh: 0.3 | ||
box_thresh: 0.6 | ||
max_candidates: 1000 | ||
unclip_ratio: 1.5 | ||
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Metric: | ||
name: DetMetric | ||
main_indicator: hmean | ||
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Train: | ||
dataset: | ||
name: SimpleDataSet | ||
data_dir: ./train_data/icdar2015/text_localization/ | ||
label_file_list: | ||
- ./train_data/icdar2015/text_localization/train_icdar2015_label.txt | ||
ratio_list: [1.0] | ||
transforms: | ||
- DecodeImage: | ||
img_mode: BGR | ||
channel_first: false | ||
- DetLabelEncode: null | ||
- CopyPaste: null | ||
- IaaAugment: | ||
augmenter_args: | ||
- type: Fliplr | ||
args: | ||
p: 0.5 | ||
- type: Affine | ||
args: | ||
rotate: | ||
- -10 | ||
- 10 | ||
- type: Resize | ||
args: | ||
size: | ||
- 0.5 | ||
- 3 | ||
- EastRandomCropData: | ||
size: | ||
- 640 | ||
- 640 | ||
max_tries: 50 | ||
keep_ratio: true | ||
- MakeBorderMap: | ||
shrink_ratio: 0.4 | ||
thresh_min: 0.3 | ||
thresh_max: 0.7 | ||
total_epoch: *epoch_num | ||
- MakeShrinkMap: | ||
shrink_ratio: 0.4 | ||
min_text_size: 8 | ||
total_epoch: *epoch_num | ||
- NormalizeImage: | ||
scale: 1./255. | ||
mean: | ||
- 0.485 | ||
- 0.456 | ||
- 0.406 | ||
std: | ||
- 0.229 | ||
- 0.224 | ||
- 0.225 | ||
order: hwc | ||
- ToCHWImage: null | ||
- KeepKeys: | ||
keep_keys: | ||
- image | ||
- threshold_map | ||
- threshold_mask | ||
- shrink_map | ||
- shrink_mask | ||
loader: | ||
shuffle: true | ||
drop_last: false | ||
batch_size_per_card: 8 | ||
num_workers: 8 | ||
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||
Eval: | ||
dataset: | ||
name: SimpleDataSet | ||
data_dir: ./train_data/icdar2015/text_localization/ | ||
label_file_list: | ||
- ./train_data/icdar2015/text_localization/test_icdar2015_label.txt | ||
transforms: | ||
- DecodeImage: | ||
img_mode: BGR | ||
channel_first: false | ||
- DetLabelEncode: null | ||
- DetResizeForTest: | ||
- NormalizeImage: | ||
scale: 1./255. | ||
mean: | ||
- 0.485 | ||
- 0.456 | ||
- 0.406 | ||
std: | ||
- 0.229 | ||
- 0.224 | ||
- 0.225 | ||
order: hwc | ||
- ToCHWImage: null | ||
- KeepKeys: | ||
keep_keys: | ||
- image | ||
- shape | ||
- polys | ||
- ignore_tags | ||
loader: | ||
shuffle: false | ||
drop_last: false | ||
batch_size_per_card: 1 | ||
num_workers: 2 | ||
profiler_options: null |
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Global: | ||
debug: false | ||
use_gpu: true | ||
epoch_num: 200 | ||
log_smooth_window: 20 | ||
print_batch_step: 10 | ||
save_model_dir: ./output/rec_repsvtr_gtc | ||
save_epoch_step: 10 | ||
eval_batch_step: [0, 1000] | ||
cal_metric_during_train: False | ||
pretrained_model: | ||
checkpoints: | ||
save_inference_dir: | ||
use_visualdl: false | ||
infer_img: doc/imgs_words/ch/word_1.jpg | ||
character_dict_path: ppocr/utils/ppocr_keys_v1.txt | ||
max_text_length: &max_text_length 25 | ||
infer_mode: false | ||
use_space_char: true | ||
distributed: true | ||
save_res_path: ./output/rec/predicts_repsvtr.txt | ||
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Optimizer: | ||
name: AdamW | ||
beta1: 0.9 | ||
beta2: 0.999 | ||
epsilon: 1.e-8 | ||
weight_decay: 0.025 | ||
no_weight_decay_name: norm | ||
one_dim_param_no_weight_decay: True | ||
lr: | ||
name: Cosine | ||
learning_rate: 0.001 # 8gpus 192bs | ||
warmup_epoch: 5 | ||
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Architecture: | ||
model_type: rec | ||
algorithm: SVTR_HGNet | ||
Transform: | ||
Backbone: | ||
name: RepSVTR | ||
Head: | ||
name: MultiHead | ||
head_list: | ||
- CTCHead: | ||
Neck: | ||
name: svtr | ||
dims: 256 | ||
depth: 2 | ||
hidden_dims: 256 | ||
kernel_size: [1, 3] | ||
use_guide: True | ||
Head: | ||
fc_decay: 0.00001 | ||
- NRTRHead: | ||
nrtr_dim: 384 | ||
max_text_length: *max_text_length | ||
num_decoder_layers: 2 | ||
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Loss: | ||
name: MultiLoss | ||
loss_config_list: | ||
- CTCLoss: | ||
- NRTRLoss: | ||
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PostProcess: | ||
name: CTCLabelDecode | ||
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Metric: | ||
name: RecMetric | ||
main_indicator: acc | ||
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Train: | ||
dataset: | ||
name: MultiScaleDataSet | ||
ds_width: false | ||
data_dir: ./train_data/ | ||
ext_op_transform_idx: 1 | ||
label_file_list: | ||
- ./train_data/train_list.txt | ||
transforms: | ||
- DecodeImage: | ||
img_mode: BGR | ||
channel_first: false | ||
- RecAug: | ||
- MultiLabelEncode: | ||
gtc_encode: NRTRLabelEncode | ||
- KeepKeys: | ||
keep_keys: | ||
- image | ||
- label_ctc | ||
- label_gtc | ||
- length | ||
- valid_ratio | ||
sampler: | ||
name: MultiScaleSampler | ||
scales: [[320, 32], [320, 48], [320, 64]] | ||
first_bs: &bs 192 | ||
fix_bs: false | ||
divided_factor: [8, 16] # w, h | ||
is_training: True | ||
loader: | ||
shuffle: true | ||
batch_size_per_card: *bs | ||
drop_last: true | ||
num_workers: 8 | ||
Eval: | ||
dataset: | ||
name: SimpleDataSet | ||
data_dir: ./train_data | ||
label_file_list: | ||
- ./train_data/val_list.txt | ||
transforms: | ||
- DecodeImage: | ||
img_mode: BGR | ||
channel_first: false | ||
- MultiLabelEncode: | ||
gtc_encode: NRTRLabelEncode | ||
- RecResizeImg: | ||
image_shape: [3, 48, 320] | ||
- KeepKeys: | ||
keep_keys: | ||
- image | ||
- label_ctc | ||
- label_gtc | ||
- length | ||
- valid_ratio | ||
loader: | ||
shuffle: false | ||
drop_last: false | ||
batch_size_per_card: 128 | ||
num_workers: 4 |
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