General OCR Struct#

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.