color-correction

Color Correction (measure, don't eyeball)

The core principle

You cannot reliably judge color from a storyboard or contact sheet. "Is it washed out?" flip-flops by eye, especially on AI-gen video. Make color measurable with the get_image (action:"analyze_color") MCP tool, read the numbers like a colorist reads scopes, pick the fix the data points to, then re-measure to confirm. The whole skill is this loop:

extract a frame ─► get_image (action:"analyze_color") ─► read black/white points + contrast + saturation
       ▲                                          │
       │                                          ▼
   re-measure  ◄──── apply fix (levels / contrast / match) ◄── diagnose from the numbers

Origin: on a WAN-Animate render we argued for many turns over whether the clip was "washed out." The instant we measured it, the answer was unambiguous and the correct fix (a contrast stretch, not the color-match nodes we'd been adding) fell straight out.

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The get_image (action:"analyze_color") tool

Read-only. Source = asset_id, a ComfyUI output ref (filename/subfolder/type), or an image path (absolute, or under the output dir). It returns per-image stats, heuristic flags, a one-line verdict, and optionally an overlaid R/G/B/luma histogram PNG.

get_image({ action: "analyze_color", filename: "render_00007_.png" })       # absolute numbers
get_image({ action: "analyze_color", path: "frame.png", reference_path: "src.jpg" })  # + shot-match deltas
get_image({ action: "analyze_color", filename: "x.png", histogram: true })  # + histogram image

For videos, get_image (action:"analyze_color") is image-only (no ffmpeg dep). Extract a frame first with the ComfyUI venv's cv2:

"<comfy-venv>/python" -c "import cv2; c=cv2.VideoCapture(r'IN.mp4'); n=int(c.get(7)); \
  c.set(1, n//2); _,f=c.read(); cv2.imwrite(r'frame.png', f)"

Grab the middle frame, or frame 0. For window-drift checks grab a frame from each window.