RRepoGEO

REPOGEO REPORT · LITE

axodox/axodox-machinelearning

Default branch main · commit 41cfb3eb · scanned 6/14/2026, 7:08:09 AM

GitHub: 633 stars · 42 forks

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 axodox/axodox-machinelearning, 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 README introduction to emphasize pure C++ and target audience

    Why:

    CURRENT
    This repository contains a **fully C++ implementation of Stable Diffusionbased image synthesis, including the original txt2img, img2img and inpainting capabilities and the safety checker. This solution **does not depend on Python** and **runs the entire image generation process in a single process with competitive performance**, making deployments significantly simpler and smaller, essentially consisting a few executable and library files, and the model weights. Using the library it is possible to integrate Stable Diffusion into almost any application - as long as it can import C++ or C functions, but it is **most useful for the developers of realtime graphics applications and games**, which are often realized with C++.
    COPY-PASTE FIX
    This repository offers a **pure C++ implementation of advanced AI models for real-time graphics and games**, including Stable Diffusion (1.5 and XL), ControlNet, Midas, HED, and OpenPose. It provides a complete, Python-free solution for image synthesis, txt2img, img2img, and inpainting, running the entire process in a single, performant C++ application. This makes integration into C++ game engines and graphics applications significantly simpler and more efficient.
  • highhomepage#2
    Add a homepage URL to the repository

    Why:

    COPY-PASTE FIX
    Add the official project homepage URL (e.g., a documentation site or project page) to the repository settings.
  • mediumtopics#3
    Add more specific topics for native C++ AI in games/graphics

    Why:

    CURRENT
    controlnet, cpp, directml, holistically-nested-edge-detection, image-generation, midas, mit-license, native, nuget, onnx, openpose, stable-diffusion, stable-diffusion-xl
    COPY-PASTE FIX
    controlnet, cpp, directml, game-development, game-engine, graphics, holistically-nested-edge-detection, image-generation, midas, mit-license, native, nuget, onnx, openpose, real-time, stable-diffusion, stable-diffusion-xl, computer-vision

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 axodox/axodox-machinelearning
Avg rank
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
OpenVINO Toolkit
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. OpenVINO Toolkit · recommended 2×
  2. ONNX Runtime · recommended 2×
  3. TensorFlow Lite · recommended 2×
  4. OpenCV · recommended 2×
  5. LibTorch · recommended 1×
  • CATEGORY QUERY
    How to implement image generation and AI models natively in C++ without Python?
    you: not recommended
    AI recommended (in order):
    1. OpenVINO Toolkit
    2. ONNX Runtime
    3. TensorFlow Lite
    4. LibTorch
    5. DirectX 12
    6. Vulkan Compute Shaders
    7. OpenCV
    8. TinyDNN

    AI recommended 8 alternatives but never named axodox/axodox-machinelearning. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Seeking a performant C++ library for integrating advanced computer vision models into games.
    you: not recommended
    AI recommended (in order):
    1. OpenCV
    2. Dlib
    3. TensorFlow Lite
    4. ONNX Runtime
    5. OpenVINO Toolkit
    6. CUDA
    7. cuDNN

    AI recommended 7 alternatives but never named axodox/axodox-machinelearning. 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 axodox/axodox-machinelearning?
    pass
    AI named axodox/axodox-machinelearning explicitly

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

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

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

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  • Brand-free category queries5 vs 2 in Lite
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