deblur_image

shallow

io.github.cnghockey/sats4ai · Verify this server

Recover detail from camera-shake and accidental motion blur. NAFNet (ECCV 2022, SOTA on GoPro/SIDD benchmarks). Best for: handheld shake, bumped camera, whole-frame uniform blur. NOT effective for: intentional panning blur, bokeh/depth-of-field, or artistic motion effects. Also supports denoising (grainy/noisy photos). 110 sats per image (~2 min processing), pay per request with Bitcoin Lightning — no API key or signup needed. Requires create_payment with toolName='deblur_image'.

100.0/100

1 trials · measured 2 days ago

deblur_image scores 100.0/100 on Vouch's measured behaviour index, from 1 real invocation trials against io.github.cnghockey/sats4ai, measured 31 Aug 2026 under methodology v0.2.0. Every measured component scored 100.

Component breakdown

ComponentWeightValue
Reliability35%not applicable
Schema integrity25%100.0
Failure behaviour15%not applicable
Latency15%not applicable
Concurrency10%not applicable

Tool details

Transport
remote + stdio
Credential class
self-provisionable
Category
Legal & government
Input schema
not declared
Output schema
not declared
Side-effect classification
unclassified

Score history

DayScoreTierMethodology
2026-08-31100.0shallowv0.2.0

Probe evidence

ProbeOutcomes
schema_integritypass: 1

Raw request/response logs are not archived yet — the outcome counts above are drawn directly from every recorded trial.

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Vouch score: deblur_image
[![Vouch score](https://vouch.tools/api/tools/f7206bee-fcc8-433a-9b0e-e1ad2276a17d/badge.svg)](https://vouch.tools/tools/f7206bee-fcc8-433a-9b0e-e1ad2276a17d)
deblur_image — Vouch