mirror of https://github.com/open-mmlab/mmocr.git
37 lines
1.1 KiB
Markdown
37 lines
1.1 KiB
Markdown
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# Key Information Extraction
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## Overview
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The structure of the key information extraction dataset directory is organized as follows.
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```text
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└── wildreceipt
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├── class_list.txt
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├── dict.txt
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├── image_files
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├── openset_train.txt
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├── openset_test.txt
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├── test.txt
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└── train.txt
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```
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## Preparation Steps
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### WildReceipt
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- Just download and extract [wildreceipt.tar](https://download.openmmlab.com/mmocr/data/wildreceipt.tar).
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### WildReceiptOpenset
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- Step0: have [WildReceipt](#WildReceipt) prepared.
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- Step1: Convert annotation files to OpenSet format:
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```bash
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# You may find more available arguments by running
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# python tools/data/kie/closeset_to_openset.py -h
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python tools/data/kie/closeset_to_openset.py data/wildreceipt/train.txt data/wildreceipt/openset_train.txt
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python tools/data/kie/closeset_to_openset.py data/wildreceipt/test.txt data/wildreceipt/openset_test.txt
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```
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:::{note}
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You can learn more about the key differences between CloseSet and OpenSet annotations in our [tutorial](../tutorials/kie_closeset_openset.md).
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:::
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