RRepoGEO

REPOGEO REPORT · LITE

sparkyniner/Netryx-OpenSource-Next-Gen-Street-Level-Geolocation

Default branch main · commit 293d4a1b · scanned 6/6/2026, 11:23:29 AM

GitHub: 44 stars · 11 forks

AI VISIBILITY SCORE
22 /100
Critical
Category recall
0 / 2
Not recommended in any query
Rule findings
1 pass · 1 warn · 0 fail
Objective metadata checks
AI knows your name
1 / 3
Direct prompts that named your repo
HOW TO READ THIS REPORT

Action plan is what to do next — copy-pasteable changes prioritized by impact. Category visibility is the real GEO test: when a user asks an AI a brand-free question that should surface sparkyniner/Netryx-OpenSource-Next-Gen-Street-Level-Geolocation, does the AI actually recommend you — or your competitors? Objective checks verify the metadata signals AI engines weight first. Self-mention check detects whether AI even knows you exist by name.

Action plan — copy-paste fixes

2 prioritized changes generated by gemini-2.5-flash. Mark items done after you ship the fix.

OVERALL DIRECTION
  • hightopics#1
    Add specific topics to improve categorization

    Why:

    CURRENT
    (none)
    COPY-PASTE FIX
    geolocation, computer-vision, street-level, visual-place-recognition, offline-geolocation, deep-learning, image-matching, local-first
  • mediumreadme#2
    Clarify Netryx's unique computer vision approach in the README's opening

    Why:

    CURRENT
    <p align="center"><strong>Open-Source Street-Level Geolocation Engine</strong></p>
    COPY-PASTE FIX
    <p align="center"><strong>Open-Source Street-Level Geolocation Engine powered by State-of-the-Art Computer Vision</strong></p>

Category GEO backends resolved for this scan: google/gemini-2.5-flash, deepseek/deepseek-v4-flash

Category visibility — the real GEO test

Brand-free queries asked to google/gemini-2.5-flash. Did AI recommend you, or someone else?

Same questions for every model — switch tabs to compare answers and rankings.

Recall
0 / 2
0% of queries surface sparkyniner/Netryx-OpenSource-Next-Gen-Street-Level-Geolocation
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
Mapillary
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. Mapillary · recommended 1×
  2. OpenStreetCam · recommended 1×
  3. Google Street View · recommended 1×
  4. QGIS · recommended 1×
  5. ArcGIS Pro · recommended 1×
  • CATEGORY QUERY
    How to determine precise GPS coordinates from a street-level photograph locally?
    you: not recommended
    AI recommended (in order):
    1. Mapillary
    2. OpenStreetCam
    3. Google Street View
    4. QGIS
    5. ArcGIS Pro
    6. ExifTool
    7. Google Cloud Vision API
    8. Amazon Rekognition
    9. OpenStreetMap
    10. Google Maps

    AI recommended 10 alternatives but never named sparkyniner/Netryx-OpenSource-Next-Gen-Street-Level-Geolocation. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What open-source tools use computer vision for offline street image geolocation?
    you: not recommended
    AI recommended (in order):
    1. OpenSfM (mapillary/OpenSfM)
    2. COLMAP (colmap/colmap)
    3. ORB-SLAM3 (UZ-SLAMLab/ORB_SLAM3)
    4. OpenCV (opencv/opencv)
    5. PCL (PointCloudLibrary/pcl)

    AI recommended 5 alternatives but never named sparkyniner/Netryx-OpenSource-Next-Gen-Street-Level-Geolocation. This is the gap to close.

    Show full AI answer

Objective checks

Rule-based audits of metadata signals AI engines weight most.

  • Metadata completeness
    warn

    Suggestion:

  • README presence
    pass

Self-mention check

Does AI even know your repo exists when asked about it directly?

  • Compared to common alternatives in this category, what is the core differentiator of sparkyniner/Netryx-OpenSource-Next-Gen-Street-Level-Geolocation?
    pass
    AI did not name sparkyniner/Netryx-OpenSource-Next-Gen-Street-Level-Geolocation — likely talking about a different project

    AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?

  • If a team adopts sparkyniner/Netryx-OpenSource-Next-Gen-Street-Level-Geolocation in production, what risks or prerequisites should they evaluate first?
    pass
    AI named sparkyniner/Netryx-OpenSource-Next-Gen-Street-Level-Geolocation explicitly

    AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?

  • In one sentence, what problem does the repo sparkyniner/Netryx-OpenSource-Next-Gen-Street-Level-Geolocation solve, and who is the primary audience?
    pass
    AI did not name sparkyniner/Netryx-OpenSource-Next-Gen-Street-Level-Geolocation — likely talking about a different project

    AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?

Embed your GEO score

Drop this badge into the README of sparkyniner/Netryx-OpenSource-Next-Gen-Street-Level-Geolocation. It auto-updates whenever the report is rescanned and links back to the latest report — easy public proof that you care about AI discoverability.

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  • Brand-free category queries5 vs 2 in Lite
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