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Collections:
- Name: CRNN
Metadata:
Training Data: OCRDataset
Training Techniques:
- Adadelta
Epochs: 5
Batch Size: 64
Training Resources: 1x NVIDIA A100-SXM4-80GB
Architecture:
- MiniVGG
- CRNNDecoder
Paper:
URL: https://arxiv.org/pdf/1507.05717.pdf
Title: 'An End-to-End Trainable Neural Network for Image-based Sequence Recognition and Its Application to Scene Text Recognition'
README: configs/textrecog/crnn/README.md
Models:
- Name: crnn_mini-vgg_5e_mj
Alias: CRNN
In Collection: CRNN
Config: configs/textrecog/crnn/crnn_mini-vgg_5e_mj.py
Metadata:
Training Data: Syn90k
Results:
- Task: Text Recognition
Dataset: IIIT5K
Metrics:
word_acc: 0.8053
- Task: Text Recognition
Dataset: SVT
Metrics:
word_acc: 0.8053
- Task: Text Recognition
Dataset: ICDAR2013
Metrics:
word_acc: 0.8739
- Task: Text Recognition
Dataset: ICDAR2015
Metrics:
word_acc: 0.5556
- Task: Text Recognition
Dataset: SVTP
Metrics:
word_acc: 0.6093
- Task: Text Recognition
Dataset: CT80
Metrics:
word_acc: 0.5694
Weights: https://download.openmmlab.com/mmocr/textrecog/crnn/crnn_mini-vgg_5e_mj/crnn_mini-vgg_5e_mj_20220826_224120-8afbedbb.pth
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