/vision-tools

name: vision-tools
description: >-
  Local vision CLIs: glance (describe/ask/OCR an image), ground (locate a
  target, pixel box), detect (element inventory), trace (image to SVG
  geometry), crop (cut a pixel box to a file), and scripts/html_shot.py (HTML
  file to image). Use for any task involving an image — questions, text,
  splitting and transcribing long screenshots or chat histories, locating elements,
  comparing, rebuilding as HTML/SVG, digitizing a sketch or diagram, reading
  values off a chart, operating a GUI from screenshots — and to re-check an
  image yourself when a description you were given lacks a detail.

vision-tools

Five local CLIs that give a text-only agent eyes. They read one shared vision config (`VISION_API_KEY` / `VISION_BASE_URL` / `VISION_MODEL` / `LANG`) — no extra credentials.

Pick the tool by the question you are answering:

| Question | Tool | |---|---| | "What does this image show / say?" | `glance` | | "Where is X?" — a thing you can name | `ground` | | "Where are all the Xs?" — every instance of a kind | `detect` | | "What is its exact shape, size, offset?" | `trace` | | "Cut this box out as its own image file" | `crop` | | "OCR this long screenshot / scrolling page / chat history" | `scripts/long_screenshot_ocr.py` | | "Extract the icon/logo foreground as transparent PNG — manual region or auto (cropped+scaled screenshots)" | `scripts/extract_fg.py` | | "Turn this HTML file into a screenshot" | `scripts/html_shot.py` | | "Which colours dominate a region, and which palette value fits it?" | `scripts/dominant_colors.py` | | A relation none of them return — a gap, a distance between two located things | code over the pixels (Pillow) |

`glance` answers what something is; `ground` and `detect` answer where. You give `ground` a description of a particular thing; you give `detect` a kind and it enumerates the instances.

Both give real coordinates, but they are not pixel-exact: the box arrives on a 0-1000 grid and is scaled to your image, so the last pixel or few are not reliable. That is accurate enough to crop with, to click, to compare positions against. When a number has to be exact, `trace` derives it from the actual pixels — offsets, sizes, shapes.

Use the provided tools before hand-rolled pixels

Everything this toolkit ships a tool for, call the tool — do not rewrite it with Pillow in the middle of a task. The CLIs exist so the same pixel work is not hand-coded differently every time:

• cut a box out of an image → `crop`, not `Image.open(...).crop(...)`
• sample a region's palette → `scripts/dominant_colors.py`
• compare two images → `scripts/pixel_diff.py`
• vectorize to SVG → `trace`
• locate / inventory elements → `ground` / `detect`
• describe / OCR an image → `glance`
• safely split, OCR, and merge a long screenshot → `scripts/long_screenshot_ocr.py`
• HTML file to a screenshot → `scripts/html_shot.py`

Hand-written Pillow is only for what none of them return: a relation between two things you already located (a gap, a distance), a resize or overlay, drawing. If you catch yourself writing `.crop()`, `.convert()`, or histogram code where one of the tools above fits, replace it with the tool call — same coordinates, same box format, and the output feeds the next tool directly.

glance — ask about an image

glance <image>                                 # detailed description
glance <image> -q "<question>"                 # targeted question (qualitative only)
glance <image> --ocr                           # verbatim OCR
glance <image> --region X1,Y1,X2,Y2 -q "..."   # zoom into a crop
glance <img1> <img2> -q "..."                  # compare in ONE call

When you do compare with `glance`, pass all paths to one call — separate calls cannot see both images, so two descriptions compared afterwards are two hallucination surfaces, not a comparison. `--region` uploads only the crop, so small text and icons become readable.

But "what changed between these two?" is not a glance question. A one-word badge or a small shift is a rounding error to a vision model and exact to `scripts/pixel_diff.py`. Diff first to get the box, then `glance --region` that box to read what the change actually is.

For a tall scrolling screenshot, do not send the whole image through one OCR call and accept the model's downscaling loss. Run the long-screenshot workflow, which finds low-content cut bands, invokes `glance` on each chunk, uses structured extraction for chat histories, merges only duplicated overlap, and writes a boundary audit:

python3 scripts/long_screenshot_ocr.py work/page.png -o work/page.ocr.md
python3 scripts/long_screenshot_ocr.py work/chat.png --mode chat --resume -o work/chat.ocr.md

Read `references/long-screenshot-ocr.md` before using it. It defines the verification pass for unsafe cuts and chat-message boundaries.

ground — locate a named target

ground <image> "<target description>"
ground <image> "<target>" --region X1,Y1,X2,Y2

Output: `x1: .., y1: .., x2: .., y2: ..` in original-image pixels — with `--region` too (crop hits are mapped back).

If several boxes come back numbered, your description matched more than one element rather than picking out a single thing. Narrow it with what distinguishes the one you mean — its text, its position, the block it sits in — and ask again.

The box is a handle, not just an answer — it feeds the next call:

$ ground screenshot.png "the send button"
x1: 1067, y1: 841, x2: 1108, y2: 881
$ glance screenshot.png --region 1067,841,1108,881 -q "is it enabled or greyed out?"

That two-step is how you inspect anything too small to survive a full-image pass.

detect — find every instance of a kind

detect <image>                        # every UI element
detect <image> "buttons"              # one kind only
detect <image> --region X1,Y1,X2,Y2   # inside one box

You name a particular thing for `ground`; you name a kind for `detect` an