Downscales the roughly 1080×1920 source to 360×640 and truncates a 20.02s clip to 5.005s.

⚠ Struggled🧾 artifact-verifiedinput + output shownTest date not recordedCutout.Pro →
What was measured
Output resolution

Does it maintain the input resolution or downscale?

context, not decisivetransformation

Keeping full resolution is important for delivery quality, but it is a downstream output constraint rather than the main background-removal task itself. (3 of 3 judges)

What was given, what came back

Test input: Busy Urban Street · video · group: remove-or-replace-video-backgrounds-using-ai
Input — what we sent

A video of a person walking through a busy city street with multiple people, moving vehicles, and a visually complex urban background. It was used to stress segmentation and tracking under heavy background distraction and continuous motion.

Why this input is hard
  • · Complex background segmentation
  • · Handling background distractions
  • · Subject tracking
  • · Temporal consistency across frames
  • · Edge accuracy during continuous movement
Provenance
Observation
38440c5b-4b6d-4704-8a36-74aba8d22968
Evidence run
10155228-7ce8-438a-a210-547331ef080b
Study
Remove or Replace Video Backgrounds Using AI
Research task
86ba42c2d
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: "cutout-pro",
  scenario: "remove-or-replace-video-backgrounds-using-ai"
})
MCP · mcp.aidemos.com/api/mcp
Free with attribution.
Same input, same check — 5 other tools
measured on Output resolution
Real inputs and real outputs, no retouching · every cell queryable via API & MCP · aidemos.com