RRepoGEO

REPOGEO REPORT · LITE

Fafa-DL/Opencv-project

Default branch main · commit 9a0342ab · scanned 6/5/2026, 3:03:03 PM

GitHub: 566 stars · 171 forks

AI VISIBILITY SCORE
30 /100
Critical
Category recall
0 / 2
Not recommended in any query
Rule findings
1 pass · 0 warn · 1 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 Fafa-DL/Opencv-project, 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
    Reposition the README's opening statement

    Why:

    CURRENT
    Awesome Opencv Project
    COPY-PASTE FIX
    This repository is a consolidated collection of practical computer vision projects implemented with OpenCV, offering ready-to-use examples for tasks like object detection, OCR, face recognition, and hand tracking.
  • hightopics#2
    Add relevant topics to the repository

    Why:

    COPY-PASTE FIX
    opencv, computer-vision, object-detection, ocr, face-detection, hand-tracking, pose-estimation, image-processing, python, projects, examples
  • highlicense#3
    Add a LICENSE file to the repository

    Why:

    COPY-PASTE FIX
    Create a LICENSE file (e.g., MIT or Apache-2.0) in the repository root to clarify usage rights.

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 Fafa-DL/Opencv-project
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
PyImageSearch
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. PyImageSearch · recommended 2×
  2. OpenCV-Python Tutorials · recommended 1×
  3. tensorflow/models · recommended 1×
  4. keras-team/keras · recommended 1×
  5. pytorch/pytorch · recommended 1×
  • CATEGORY QUERY
    Looking for practical code examples for various computer vision tasks like OCR and object detection.
    you: not recommended
    AI recommended (in order):
    1. OpenCV-Python Tutorials
    2. PyImageSearch
    3. TensorFlow Object Detection API (tensorflow/models)
    4. Keras (keras-team/keras)
    5. PyTorch (pytorch/pytorch)
    6. Tesseract OCR (tesseract-ocr/tesseract)

    AI recommended 6 alternatives but never named Fafa-DL/Opencv-project. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Where can I find a comprehensive collection of beginner-friendly computer vision projects?
    you: not recommended
    AI recommended (in order):
    1. OpenCV-Python (opencv/opencv-python)
    2. Kaggle Learn
    3. PyImageSearch
    4. Towards Data Science
    5. freeCodeCamp.org
    6. Coursera
    7. edX
    8. Udacity

    AI recommended 8 alternatives but never named Fafa-DL/Opencv-project. This is the gap to close.

    Show full AI answer

Objective checks

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

  • Metadata completeness
    fail

    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 Fafa-DL/Opencv-project?
    pass
    AI named Fafa-DL/Opencv-project explicitly

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

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

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

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MARKDOWN (README)
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Fafa-DL/Opencv-project — 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