excel图片汇总功能
Introduction
name: xlsx-image-rollup description: This skill should be used when the user wants to aggregate, summarize, or "roll up" a multi-sheet Excel workbook that contains embedded images (drawings) into a single summary table that also embeds the relevant images grouped by category/series/issue/responsibility. Trigger phrases include "把登记表按 XX 分类整理", "问题汇总 + 附图", "按维度聚合并附图片", "生成图片汇总相册", "embedded-image xlsx rollup", "把每张问题图片单独放在单元格中", "按问题点汇总图片", and any request where the source .xlsx contains a few hundred to a few thousand embedded product/issue images and the deliverable is a single grouped album/summary sheet. xlsx-image-rollup Overview Aggregate a multi-sheet .xlsx (each row may carry an embedded image) into a single grouped summary table that also embeds the relevant images. The source workbook is typically a quality-issue registration form, inspection log, or after-sales complaint table where every record has 1–N photos. The output is a single Excel file with one "rollup" sheet where rows are grouped by category → series → responsibility → issue point, with frequency, percentage, user-original-quote and grouped images side by side. Four output layouts are supported (selectable via --layout): thumbnail – 180px thumbnails, multiple images per row arranged horizontally original – original image data embedded (no resampling), 400px display detail – one image per row, text columns vertically merged, image centered in a fixed cell grid – one row per issue, all images packed into a single "图片" cell in a 4-per-line grid Workflow To produce a rollup from a source .xlsx, follow these steps: Inspect the source workbook to find the data sheets, header row, image-bearing column(s), and any image variants (.png/.jpeg/.mpo). Extract embedded images via scripts/extract_images.py (ZIP-level, NOT openpyxl). Save to a flat directory using a stable image{N}.{ext} naming scheme. Aggregate rows by (category, series, responsibility, issue) dimensions. For each unique key, count frequency, compute count / series_total percentage, collect user-original-quotes, and collect the list of image filenames. Choose a layout by asking the user which of the four layouts fits the use case (or default to grid for the most compact one-row-per-issue presentation). Build the output workbook via scripts/build_album.py with --layout and the summary JSON. Deliver the output .xlsx via present_files and offer to adjust layout/sizing. Key decisions to make with the user Layout – thumbnail (smallest file, fastest), original (largest, full resolution), detail (each image in its own cell), grid (one row per issue, images in a single cell, recommended default). Display edge – only relevant for thumbnail/original/detail. Default 320px gives a balance of clarity and row density. Grid width – only relevant for grid. Default 4 images per row; lower to 3 for larger images. Critical pitfalls to avoid See references/openpyxl_pitfalls.md for the full list. The non-obvious ones are: DO NOT use openpyxl.load_workbook to read drawings on a large file with hundreds of embedded images — it can crash on certain drawing-relationship XML. Use the ZIP-level extractor in scripts/extract_images.py instead. MPO images (3D/multi-frame, extension may be .jpeg) trigger KeyError: '.mpo' in openpyxl because openpyxl uses Pillow.Image.format as the embedded extension. The scripts auto-detect MPO and convert to JPEG via Pillow.Image.seek(0).convert('RGB').save('JPEG'). OneCellAnchor.ext must be XDRPositiveSize2D(cx, cy), NOT a (w, h) tuple. The error message says value is <class 'tuple'> but the real fix is to import from openpyxl.drawing.xdr and construct the proper class. Cell-center an image with AnchorMarker(col=..., colOff=pixels_to_EMU(x), row=..., rowOff=pixels_to_EMU(y)) and OneCellAnchor(_from=marker, ext=XDRPositiveSize2D(...)). The x/y offsets are the distance from the cell's top-left in pixels. Column width and row height units: column width is in "characters" (≈ 7px each for Calibri 11); row height is in pt (1pt = 1/72 inch, ≈ 1.33px). Convert with pixels_to_EMU(px) from openpyxl.utils.units (1px = 9525 EMU). Resources scripts/ extract_images.py – ZIP-level image extractor. Takes <input.xlsx> <output_dir> and writes every embedded image (across all sheets) to the output dir using image{N}.{ext} naming. Handles MPO and other exotic formats. build_album.py – Build a rollup workbook from a summary JSON + extracted image directory. Supports --layout {thumbnail,original,detail,grid}. Produces a styled xlsx with frozen header, blue header fill, bordered cells, and a "图片" column. references/ openpyxl_pitfalls.md – Detailed catalog of openpyxl embedding pitfalls with reproductions and fixes. layouts.md – Visual decision guide for choosing the right layout, with example row/column counts and file size impact.
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