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uzh-rpg/rpg_svo

Semi-direct Visual Odometry

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  • C++
  • ★ 2,236
  • commit d6161063b47f
  • scored 2026-11-13
  • scoring prov-4+qual-2+sec-2

AI provenance

0%

none-detected

Confidence
65%
Coverage
100%

Estimated share of AI-generated code. Explicit attribution is a lower bound.

Code quality

39/100

poor

Confidence
90%
Coverage
100%

Complexity, duplication, lint density, tests, CI, docs and review process.

Security

82/100

adequate

Confidence
85%
Coverage
100%

Secrets, static analysis, vulnerable dependencies, CI and supply-chain posture.

  • Repository: https://github.com/uzh-rpg/rpg_svo
  • Commit: d6161063b47f36ce78252ee4c4fedf3f6d8f2898
  • Generated: 2026-11-13T23:42:17+00:00
  • Scorer 0.1.0, scoring prov-4+qual-2+sec-2, report schema v2

Scores

Pillar Score Signal Confidence Coverage
AI provenance (estimated AI-generated share) 0 none-detected 65% 100%
Code quality 39 poor 90% 100%
Security 82 adequate 85% 100%

AI provenance

No AI attribution or AI-consistent velocity signals detected.

  • Explicitly attributed share (lower bound): 0.0%

  • Unattributed share in AI-consistent velocity bursts: 0.0%

  • Estimated AI-generated share: 0.0%

  • Stylometry index: 0.34 per 1,000 lines (narrated steps 3, placeholders 0, assistant phrasing 0, emoji 0). Reported as a signal, not scored.

Month Lines added Attributed to AI
2014-05 818 0%
2014-06 111 0%
2014-07 4 0%
2014-08 1 0%
2014-09 6 0%
2014-11 17 0%
2015-02 11 0%
2015-07 1 0%
2015-12 2 0%
2016-02 1 0%
2016-04 2 0%
2017-03 67 0%

Evidence

  • step-by-step narration comment: // finally, sum results of vb1, vb2 and vres_sum (svo/src/feat)
  • step-by-step narration comment: // now we sample along the epipolar line (svo/src/matc)
  • step-by-step narration comment: // Now we go through each grid cell and select one point to match. (svo/src/repr)

AI provenance describes how code was produced; it is not a quality judgment. Unless attribution is explicit, these are signals consistent with AI generation, not proof. Squash/rebase workflows, imported code, and rewritten history reduce accuracy.

Code quality

Code quality is poor: test-to-source ratio 0.12, no CI test run detected; 24% of function code in complex or long functions; 14% duplicated lines. Weakest area: lint.

Area Score
Complexity (lizard) 48
Duplication 44
Code smells (Opengrep) 20
Tests and CI 28
Documentation 65
Type safety 40
Process (Scorecard review/maintenance) n/a
  • Functions: 284; mean complexity 3.2, 90th percentile 8; 10 complex and 5 long functions
  • Duplicated lines: 13.9% of 6,277 compared
  • Tests: 1,032 test lines for 8,956 source lines (ratio 0.12); CI test commands: none detected; 7% of recent source commits also change tests
  • Docs missing or thin: contributing, changelog

Most complex functions:

Security

Security posture is adequate: no high-impact findings. Weakest area: posture.

Area Score
Secrets (gitleaks, tree + history) 100
Static analysis (Opengrep) 100
Vulnerable dependencies (OSV) n/a
CI workflows (zizmor) n/a
Posture (policy, updates, signing, lockfiles) 0
OpenSSF Scorecard n/a
  • Posture checks passed: lockfiles; missing: security policy, dependency updates, signed commits

Static signals only: the scorer never runs the project's code. Secret findings are pattern matches that were not verified, and secret values are never stored.

Repository profile

  • Source lines: 8,956; test lines: 1,032
Language Lines
C++ 5,786
Python 2,139
C 2,063

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