Comments (2)
Hi :)
#16 would be helpful to you.
donut
does not require any bounding box annotation/supervision during the model training. But, as a result, there are no actual boxes in the model output. Instead, you can get an attention heatmap that could be used for your purpose.
Or, you may try your fuzzy matching logic with the attention heatmap.
I hope this comment is useful to you. Please let me know if you are still confused.
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I've found some updates at #45
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Related Issues (20)
- custom json schema - ASAP HOT 2
- Multi GPU support for fine tuning
- How to extract complete text from the document? HOT 3
- confidence 값의 공식적인 지원
- Classification inference
- Update donut-python Python Package to be compatible with latest versions of transformers
- donut inference시 sub task가 변경?
- Not getting prediction correctly using the model trained on the custom dataset (similar format as CORD-V2 dataset) HOT 6
- not work this app.py
- Can synthdog insert text for a specified bbox? HOT 1
- Where is the fine-tuned model?
- Why is the output of the intermediate verification empty after training?
- Donut generate ONLY <s><s>...<s></s> HOT 7
- Performance of the model HOT 1
- How to improve OCR accuracy for Japanese characters? HOT 2
- Early Stopping
- How many documents(invoices) are required for training model for document information extraction?
- What should be the configuration of the machine to train the model?
- Hindi Synthdog
- How to interpret the results of the Japanese document?
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