# CIVQA TesseractOCR Dataset

The Czech Invoice Visual Question Answering dataset was created with Tesseract OCR, and it is suitable for adding labels for the chosen model. 
The encoded dataset for LayoutLM model can be found on this link: https://huggingface.co/datasets/fimu-docproc-research/CIVQA-TesseractOCR-LayoutLM

All invoices used in this dataset were obtained from public sources. Over these invoices, we were focusing on 15 different entities, which are crucial for processing the invoices.
- Invoice number
- Variable symbol
- Specific symbol
- Constant symbol
- Bank code
- Account number
- ICO
- Total amount
- Invoice date
- Due date
- Name of supplier
- IBAN
- DIC
- QR code
- Supplier's address

The invoices included in this dataset were gathered from the internet. We understand that privacy is of utmost importance. Therefore, we sincerely apologise for any inconvenience caused by including your identifiable information in this dataset. If you have identified your data in this dataset and wish to have it removed from research purposes, we request you kindly to access the following URL: https://forms.gle/tUVJKoB22oeTncUD6

We profoundly appreciate your cooperation and understanding in this matter.
language:cs license:mit finance region:us
{"language": ["cs"], "license": "mit", "dataset_info": {"features": [{"name": "id", "dtype": "string"}, {"name": "words", "sequence": "string"}, {"name": "answers", "dtype": "string"}, {"name": "bboxes", "sequence": {"sequence": "float64"}}, {"name": "answers_bboxes", "sequence": {"sequence": "float64"}}, {"name": "questions", "dtype": "string"}, {"name": "image", "dtype": "string"}], "splits": [{"name": "train", "num_bytes": 1838637418, "num_examples": 160645}, {"name": "validation", "num_bytes": 177768370, "num_examples": 16220}], "download_size": 6274981, "dataset_size": 2016405788}, "tags": ["finance"]}
TAGS
#language-Czech #license-mit #finance #region-us 

# CIVQA TesseractOCR Dataset

The Czech Invoice Visual Question Answering dataset was created with Tesseract OCR, and it is suitable for adding labels for the chosen model. 
The encoded dataset for LayoutLM model can be found on this link: URL

All invoices used in this dataset were obtained from public sources. Over these invoices, we were focusing on 15 different entities, which are crucial for processing the invoices.
- Invoice number
- Variable symbol
- Specific symbol
- Constant symbol
- Bank code
- Account number
- ICO
- Total amount
- Invoice date
- Due date
- Name of supplier
- IBAN
- DIC
- QR code
- Supplier's address

The invoices included in this dataset were gathered from the internet. We understand that privacy is of utmost importance. Therefore, we sincerely apologise for any inconvenience caused by including your identifiable information in this dataset. If you have identified your data in this dataset and wish to have it removed from research purposes, we request you kindly to access the following URL: URL

We profoundly appreciate your cooperation and understanding in this matter.
# CIVQA TesseractOCR Dataset

The Czech Invoice Visual Question Answering dataset was created with Tesseract OCR, and it is suitable for adding labels for the chosen model. 
The encoded dataset for LayoutLM model can be found on this link: URL

All invoices used in this dataset were obtained from public sources. Over these invoices, we were focusing on 15 different entities, which are crucial for processing the invoices.
- Invoice number
- Variable symbol
- Specific symbol
- Constant symbol
- Bank code
- Account number
- ICO
- Total amount
- Invoice date
- Due date
- Name of supplier
- IBAN
- DIC
- QR code
- Supplier's address

The invoices included in this dataset were gathered from the internet. We understand that privacy is of utmost importance. Therefore, we sincerely apologise for any inconvenience caused by including your identifiable information in this dataset. If you have identified your data in this dataset and wish to have it removed from research purposes, we request you kindly to access the following URL: URL

We profoundly appreciate your cooperation and understanding in this matter.
TAGS
#language-Czech #license-mit #finance #region-us 
 # CIVQA TesseractOCR Dataset

The Czech Invoice Visual Question Answering dataset was created with Tesseract OCR, and it is suitable for adding labels for the chosen model. 
The encoded dataset for LayoutLM model can be found on this link: URL

All invoices used in this dataset were obtained from public sources. Over these invoices, we were focusing on 15 different entities, which are crucial for processing the invoices.
- Invoice number
- Variable symbol
- Specific symbol
- Constant symbol
- Bank code
- Account number
- ICO
- Total amount
- Invoice date
- Due date
- Name of supplier
- IBAN
- DIC
- QR code
- Supplier's address

The invoices included in this dataset were gathered from the internet. We understand that privacy is of utmost importance. Therefore, we sincerely apologise for any inconvenience caused by including your identifiable information in this dataset. If you have identified your data in this dataset and wish to have it removed from research purposes, we request you kindly to access the following URL: URL

We profoundly appreciate your cooperation and understanding in this matter.
passage: TAGS
#language-Czech #license-mit #finance #region-us 
# CIVQA TesseractOCR Dataset

The Czech Invoice Visual Question Answering dataset was created with Tesseract OCR, and it is suitable for adding labels for the chosen model. 
The encoded dataset for LayoutLM model can be found on this link: URL

All invoices used in this dataset were obtained from public sources. Over these invoices, we were focusing on 15 different entities, which are crucial for processing the invoices.
- Invoice number
- Variable symbol
- Specific symbol
- Constant symbol
- Bank code
- Account number
- ICO
- Total amount
- Invoice date
- Due date
- Name of supplier
- IBAN
- DIC
- QR code
- Supplier's address

The invoices included in this dataset were gathered from the internet. We understand that privacy is of utmost importance. Therefore, we sincerely apologise for any inconvenience caused by including your identifiable information in this dataset. If you have identified your data in this dataset and wish to have it removed from research purposes, we request you kindly to access the following URL: URL

We profoundly appreciate your cooperation and understanding in this matter.