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[1_3] MMOCR 에서 제공되는 임의의 recognition 모델을 1% 금융데이터로 학습한다.

상태
Done
담당
마감일
요약
해당 데이터로 모델 학습, 평가, I/O확인이 가능하면 끝. 더불어, from the scratch / pretrained / transfered 모델 각각을 평가해서 비교한다.
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선행 태스크 상태
후행 태스크
관련 마일스톤
2 more properties
Aihub 금융 1% test score
from the scratch (Aihub 금융 train)
pretrained (no transfer learned)
transfer learned (Aihub 금융 train)
char precision
할필요없음
0.0000
0.9892
char recall
할필요없음
0.0000
0.9897
word accuracy
할필요없음
0.0000
0.9354
•
1% transfer learned
nohup tools/dist_train.sh \ configs/textrecog/sar/sar_resnet31_parallel-decoder_500e_aihubfinance1of100_pretrained.py \ 2 > nohup.out &
Bash
복사
train
ai-solution-lab
Weights & Biases, developer tools for machine learning
https://wandb.ai/ai-solution-lab/mmocr/runs/332i7nao?workspace=user-deer
cp work_dirs/sar_resnet31_parallel-decoder_500e_aihubfinance1of100_pretrained/epoch_500.pth \ pretrained/sar_resnet31_parallel-decoder_500e_aihubfinance1of100_pretrained_zesty-sun-97.pth nohup tools/dist_test.sh \ configs/textrecog/sar/sar_resnet31_parallel-decoder_500e_aihubfinance1of100_pretrained.py \ pretrained/sar_resnet31_parallel-decoder_500e_aihubfinance1of100_pretrained_zesty-sun-97.pth \ 2 > nohup.out &
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eval
11/28 11:44:16 - mmengine - INFO - Epoch(test) [66916/66916] AihubFinance1of100/recog/word_acc: 0.9354 AihubFinance1of100/recog/word_acc_ignore_case: 0.9354 AihubFinance1of100/recog/word_acc_ignore_case_symbol: 0.9699 AihubFinance10of100/recog/word_acc: 0.9474 AihubFinance10of100/recog/word_acc_ignore_case: 0.9474 AihubFinance10of100/recog/word_acc_ignore_case_symbol: 0.9755 AihubFinance100of100/recog/word_acc: 0.9369 AihubFinance100of100/recog/word_acc_ignore_case: 0.9373 AihubFinance100of100/recog/word_acc_ignore_case_symbol: 0.9706 IC15/recog/word_acc: 0.0303 IC15/recog/word_acc_ignore_case: 0.0327 IC15/recog/word_acc_ignore_case_symbol: 0.0342 AihubFinance1of100/recog/char_recall: 0.9897 AihubFinance1of100/recog/char_precision: 0.9892 AihubFinance10of100/recog/char_recall: 0.9912 AihubFinance10of100/recog/char_precision: 0.9921 AihubFinance100of100/recog/char_recall: 0.9900 AihubFinance100of100/recog/char_precision: 0.9909 IC15/recog/char_recall: 0.1938 IC15/recog/char_precision: 0.3663
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eval res
python3 -m mmocr.ocr \ --det-ckpt pretrained/dbnet_resnet18_fpnc_20e_aihubfinance10of100_sparkling-cloud-104.pth \ --det-config configs/textdet/dbnet/dbnet_resnet18_fpnc_20e_aihubfinance10of100.py \ --recog-ckpt pretrained/sar_resnet31_parallel-decoder_500e_aihubfinance1of100_pretrained_zesty-sun-97.pth \ --recog-config configs/textrecog/sar/sar_resnet31_parallel-decoder_500e_aihubfinance1of100_pretrained.py \ data/det/aihub_finance/part_10of100/imgs/IMG_OCR_6_F_00964.png \ --img-out-dir work_dirs/sar_resnet31_parallel-decoder_500e_aihubfinance1of100_pretrained \ --pred-out-file work_dirs/sar_resnet31_parallel-decoder_500e_aihubfinance1of100_pretrained/output.pkl \ --device cpu
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infer
◦
detection model 은 다음을 사용한다.
(할필요없음) 1%, from the scratch