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
image
Input not captured
This run recorded no prompt or input file for the test, so we cannot show you what produced the result below. Capture gaps are tracked, not hidden.

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