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.

What the numbers mean (8-bit)

Field	Reads like a scope	Healthy-ish
luma.blackPoint (1st pct)	where shadows bottom out	~0–16 (lifted if >16)
luma.whitePoint (99th pct)	where highlights top out	~240–255 (dim if <235)
luma.contrast (std)	overall punch	~45+ (flat if <45)
luma.dynamicRange	white−black	wide is good
saturation.meanSaturation (HSV S)	vectorscope spread	~0.25+ (dull if <0.22)
channels.{r,g,b}Mean + castHint	RGB parade / white balance	spread <~12 = neutral
luma.clippedHighPct/LowPct	blown / crushed pixels	keep low (<~2%)

Flags: washedOut, lowContrast, liftedBlacks, dimHighlights, lowSaturation, colorCast.

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The "washed out" signature

Washed out means compressed tonal range, and it has an exact fingerprint:

• whitePoint well below 255 (e.g. 191), so highlights never reach white
• blackPoint lifted off 0 (e.g. 45), giving milky shadows
• contrast low (std < 45)
• often normal saturation. Washout is usually not a saturation problem.

If you see that, the fix is a levels / contrast stretch, not a color match. In a real case, a WAN-Animate frame measured blackPoint 45 / whitePoint 191 / contrast 43, clearly a range problem; saturation 0.25 was fine.

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The load-bearing insight: a reference-match can't add contrast the source lacks

The instinct is to "match the render to the input photo" with a color-match node (ColorMatchV2 mkl/hm, ImageColorMatchAdobe+, easy imageColorMatch). Measure the reference first. If the reference is itself flat (e.g. a casual phone selfie with blackPoint 40, contrast 44), matching to it cannot produce punch; you'll match your way to the same flat numbers. In the real case, mkl and Adobe matches both left the frame flagged washedOut (whitePoint only crept from 191 to ~218).

So:

• Use a reference-match (ColorMatchV2, ImageColorMatchAdobe+) when you want to match a known-good graded frame or shot-match across clips, and the reference is actually good.
• Use a levels / contrast stretch when the defect is compressed range (the washout case). It targets full range regardless of the reference. This is usually the real fix.

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The fix: contrast / levels stretch (core nodes, no install)

AdjustContrast (core comfy_extras.nodes_dataset, category image/adjustments) has one factor (1.0 = none, >1 = more). It pivots around mid-gray, so it pushes the white point up and the black point down together. Tune it by measurement, not feel. A real measured sweep on the washout frame:

factor	blackPoint	whitePoint	contrast	sat	clippedHigh	verdict
1.3	29	239	56	0.33	0%	✅ not washed (slightly soft)
~1.4	~20	~247	~60	~0.38	~1–2%	✅ sweet spot
1.6	7	254	67	0.44	7.2% ⚠️	punchy but blows highlights

Pick the factor that lands whitePoint ~248 to 255 with clippedHighPct < ~2%. Going too far (1.6 here) blows highlights and over-warms, because per-channel contrast drops blue more than red and castHint worsens. The sweet spot was ~1.4.

Other levers when contrast alone isn't enough:

• CurveEditor (core, utilities) feeds a CURVE for precise black/white-point and gamma control (a true levels curve) when you need more than a single contrast pivot.
• AdjustContrast plus a small saturation/brightness adjust (same image/adjustments family) to fine-tune after the stretch.
• A mild reference-match after the stretch, only if you need to shot-match.

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The sandbox pattern (test corrections side by side, then measure)

Don't tune blind on the full pipeline. Build a tiny separate workflow (panel_new_workflow) and let one run produce several candidates you then measure:

LoadImage (the washed frame, staged into input/)
LoadImage (the reference, if shot-matching)
        │
        ├─► AdjustContrast factor 1.3 ─► SaveImage "contrast13"
        ├─► AdjustContrast factor 1.6 ─► SaveImage "contrast16"
        ├─► ColorMatchV2 (mkl, ref)   ─► SaveImage "balance_mkl"
        └─► ImageColorMatchAdobe+(LAB)─► SaveImage "balance_adobe"

Run once, then get_image (action:"analyze_color") every output, plus the reference and the untouched frame, and compare blackPoint / whitePoint / contrast / saturation / clippedHigh. Whichever lands the numbers in range wins; interpolate the factor (1.3 vs 1.6 gives 1.4) and confirm with one more pass. Stage the frame into the ComfyUI input dir first (cp the extracted PNG there) so LoadImage can see it. Input and output dirs may be custom, so don't guess paths.

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Porting the fix into a render graph

Place the chosen correction after decode, before the save. For a WAN/video graph that's right after WanVideoDecode (or the per-chunk color-match) and feeding the VHS_VideoCombine/save node. One AdjustContrast node is usually the whole fix. Keep it as a single inline node (or a small bypassable group) so it's easy to toggle and re-tune. Re-render a clip, extract a frame, get_image (action:"analyze_color") it, and nudge the factor to hit whitePoint ~250.

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Video-specific gotchas

• Per-window drift (WAN long video). WAN-Animate/long clips render in temporal windows and can desaturate or dim across them. Measure a frame from the first window and a late window. If they differ, that's drift, not a global grade issue; use the embeds' between-window colormatch, not a final stretch.
• Relight LoRA is not levels. A WanAnimate relight LoRA changes lighting, not black/white points. It won't fix a compressed-range washout. Measure before and after to prove it.
• Don't over-stretch. Watch clippedHighPct; blown highlights are unrecoverable. Prefer the lower factor that still clears dimHighlights.
• Cast is often inherited. If the reference has the same warm/cool cast (festival/sunset light), a matching cast on the render is correct. Don't "fix" it.

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Quick reference — the decision tree

get_image (action:"analyze_color") on the frame
  ├─ washedOut / lowContrast / dimHighlights ........ contrast/levels stretch (AdjustContrast ~1.4 → measure)
  ├─ lowSaturation only ............................. saturation boost (small)
  ├─ colorCast (and reference is neutral) ........... white-balance / neutralization, or reference-match
  ├─ want to MATCH a known-good graded frame ........ ColorMatchV2 / ImageColorMatchAdobe+ (ref must be good)
  └─ blackPoint/whitePoint already 0/255, sat ok .... color is healthy — stop touching it

Always re-measure after the fix. If get_image (action:"analyze_color") still flags it, the fix was wrong. Adjust and measure again. Numbers over vibes.

Sources

• Official: comfyui-mcp get_image action:"analyze_color" product behavior (this repo).
• Empirical: washed-out signature and levels-stretch recipes from observed renders.