The desert-horse output shows clear identity drift, with the eye shape, nose structure, jawline, and face proportions all differing from the reference.

⚠ Struggled🧾 artifact-verifiedinput + output shownTest date not recordedImagineArt →
What was measured
Identity preservation

How closely the generated face matches the reference image across scenes.

decisive for this rankingtransformation

This is the core of the task: the tool must keep the same character looking like the reference image across scenes. (3 of 3 judges)

What was given, what came back

Test input: Full frontal portrait · image
Input — what we sent
Input file 1 — as supplied
Input file 1 — as supplied
Input file 2 — as supplied
Full frontal portrait
Full frontal portrait

Full frontal portrait reference image with fair skin, curly dark hair, bindi, gold jhumka earrings, and a green stone necklace. All features are clearly visible in good natural lighting, making it the easiest identity anchor for the tools.

Why this input is hard
  • · Baseline identity preservation
  • · Accessory retention
  • · Best-case frontal face matching
  • · Consistent character reuse across varied scenes
Output — unretouched
image
Provenance
Observation
a9483897-1a64-47e5-ac48-2e943f7a2286
Evidence run
1dfb8fa4-f7f0-47dc-911b-7db3af467e9a
Study
Generate Consistent AI Characters Across Different Scenes and Poses
Research task
86b96df11
Tested at
not recorded
Source
first-party
Evidence state
verified
Proof shown
input + output shown
Cost / latency
not captured
Repeat run
not captured
Tester
not captured

The last three rows are honest blanks, not placeholders — our capture has no field for them yet.

Query this
get_evidence({
  tool: "imagineart"
})
MCP · mcp.aidemos.com/api/mcp
Free with attribution.
Same input, same check — 4 other tools
measured on Identity preservation
Real inputs and real outputs, no retouching · every cell queryable via API & MCP · aidemos.com