Image To Excel

Extract table content from images, retrieve row/column data, correct recognition errors, and generate a well-formatted Excel file.

Extract tables from images and generate .xlsx files.

Use Cases

Use when users upload images containing tables and request "convert to table", "extract table", or "generate Excel".

Workflow

1. Analyze Image

Use the image tool to load the user-uploaded image, with a prompt requesting row-by-row, column-by-column table data extraction:

Extract all table data from the image row by row and column by column, returning it as a JSON array.
Format: [[row1col1, row1col2, ...], [row2col1, row2col2, ...], ...]
Notes:
- The first row may be a header; keep it as-is
- Split merged cells into individual cells and fill with the same value
- Preserve original formatting for amounts and numbers
- Use empty string "" for missing cells

2. Data Validation & Correction

After receiving the JSON data from the image model, check and correct:

• Row/column count consistency (fill in missing cells)
• Number format correctness (remove extra spaces, unify decimal points)
• Chinese character recognition accuracy (fix obvious typos)
• Header completeness (infer missing headers from content)

Store the corrected data in the variable rows.

3. Write to Excel

Call the generation script with the corrected data:

python3 scripts/gen_excel.py <output_path> '<json_data>'

• output_path: Output path, e.g., /root/.openclaw/workspace/table_extracted.xlsx
• json_data: Corrected 2D array as a JSON string

4. Output Results

Inform the user of the file save location and display a preview of the first 5 rows for confirmation.