RRepoGEO

REPOGEO REPORT · LITE

Ewenwan/MVision

Default branch master · commit 10e9064c · scanned 6/25/2026, 6:12:52 AM

GitHub: 8,658 stars · 2,787 forks

Scan history for this repo

Score trend below includes all ready runs (older left, newer right; scroll horizontally if needed). The table is collapsed by default—expand for newest-first rows, 10 per page.

Score trend (left → right: older → newer)

3 ready scans. Expand the table below for newest-first rows (10 per page, paginated).

AI VISIBILITY SCORE
35 /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
3 / 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 Ewenwan/MVision, 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

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

OVERALL DIRECTION
  • highreadme#1
    Add a clear, concise purpose statement to the README

    Why:

    CURRENT
    The current README starts with "# MVision Machine Vision 机器视觉 AI算法工程师手册 数学基础..."
    COPY-PASTE FIX
    Add a new paragraph immediately after the H1, e.g., 'This repository serves as a comprehensive curated collection of resources, papers, courses, and algorithms for machine vision, mobile robotics, SLAM, deep learning object detection, and autonomous driving. It aims to be a learning path and reference for AI algorithm engineers in these fields.'
  • highlicense#2
    Add a LICENSE file to the repository root

    Why:

    CURRENT
    (no LICENSE file detected)
    COPY-PASTE FIX
    Create a `LICENSE` file in the repository root with the chosen open-source license (e.g., MIT, Apache-2.0, GPL-3.0).
  • mediumabout#3
    Refine the repository description to be a concise sentence

    Why:

    CURRENT
    机器人视觉 移动机器人 VS-SLAM ORB-SLAM2 深度学习目标检测 yolov3 行为检测 opencv PCL 机器学习 无人驾驶
    COPY-PASTE FIX
    A curated collection of resources, papers, and algorithms for machine vision, mobile robotics (VS-SLAM, ORB-SLAM2), deep learning object detection (YOLOv3), behavior detection, and autonomous driving, utilizing OpenCV, PCL, and machine learning.

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 Ewenwan/MVision
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
Cartographer
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. Cartographer · recommended 1×
  2. ORB-SLAM3 · recommended 1×
  3. LOAM · recommended 1×
  4. A-LOAM · recommended 1×
  5. LeGO-LOAM · recommended 1×
  • CATEGORY QUERY
    What are robust open-source solutions for simultaneous localization and mapping in mobile robots?
    you: not recommended
    AI recommended (in order):
    1. Cartographer
    2. ORB-SLAM3
    3. LOAM
    4. A-LOAM
    5. LeGO-LOAM
    6. RTAB-Map
    7. GTSAM

    AI recommended 7 alternatives but never named Ewenwan/MVision. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Seeking libraries for deep learning object detection and computer vision in autonomous vehicles.
    you: not recommended
    AI recommended (in order):
    1. OpenCV
    2. TensorFlow
    3. PyTorch
    4. Detectron2
    5. NVIDIA TensorRT
    6. OpenVINO

    AI recommended 6 alternatives but never named Ewenwan/MVision. 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 Ewenwan/MVision?
    pass
    AI named Ewenwan/MVision explicitly

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

  • If a team adopts Ewenwan/MVision in production, what risks or prerequisites should they evaluate first?
    pass
    AI named Ewenwan/MVision 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 Ewenwan/MVision solve, and who is the primary audience?
    pass
    AI named Ewenwan/MVision explicitly

    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 Ewenwan/MVision. 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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Ewenwan/MVision — Lite scans stay free; this card itemizes Pro deep limits vs Lite.

  • Deep reports10 / month
  • Brand-free category queries5 vs 2 in Lite
  • Prioritized action items8 vs 3 in Lite