General OCR Struct

Offline OCR extracting and structuring Chinese/English screenshot text into raw or cleaned rows and fields for receipts, tables, and statements.

Use this skill to separate OCR recognition from downstream content整理.

Workflow

1. Run the local OCR script on the image first.
2. Return the raw OCR text before making business interpretations when accuracy matters.
3. If the image is a transaction-detail screenshot, run structuring mode to group rows into fields.
4. Mark uncertain fields explicitly as 待确认; do not guess missing content.
5. Only after the user confirms recognition quality, use the result for tables, summaries, or documents.

Commands

Raw OCR

bash

python3 scripts/general_ocr.py raw /path/to/image.jpg

Structured transaction extraction

bash

python3 scripts/general_ocr.py transactions /path/to/image.jpg

JSON output

bash

python3 scripts/general_ocr.py transactions /path/to/image.jpg --json

Output rules

• Prefer showing the recognition result first, then the cleaned structure.
• Preserve source wording where possible.
• For uncertain content, use 待确认 instead of inferring.
• Adapt the structure to the source image type. For statement-like screenshots, common fields are: card_last4, date, time, currency, merchant, amount.

Notes

• This skill uses RapidOCR locally.
• First install may need Python packages; after setup it runs offline.
• If OCR quality is weak, request a higher-resolution original screenshot before doing deeper整理.