RRepoGEO

REPOGEO REPORT · LITE

bubbliiiing/yolox-pytorch

Default branch main · commit bbd4ef97 · scanned 6/11/2026, 7:41:02 AM

GitHub: 948 stars · 185 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 bubbliiiing/yolox-pytorch, 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
  • highreadme#1
    Add an English summary sentence to the README's opening

    Why:

    CURRENT
    ## YOLOX：You Only Look Once目标检测模型在Pytorch当中的实现
    COPY-PASTE FIX
    Add the following sentence directly below the main title in the README: 'This repository provides a PyTorch implementation of the YOLOX object detection model, optimized for training custom datasets and real-time inference.'
  • mediumabout#2
    Add an English description to the repository's 'About' section

    Why:

    CURRENT
    这是一个yolox-pytorch的源码，可以用于训练自己的模型。
    COPY-PASTE FIX
    A PyTorch implementation of the YOLOX object detection model, enabling users to train custom models for various computer vision tasks.

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 bubbliiiing/yolox-pytorch
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
facebookresearch/detectron2
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. facebookresearch/detectron2 · recommended 1×
  2. tensorflow/models · recommended 1×
  3. ultralytics/ultralytics · recommended 1×
  4. open-mmlab/mmdetection · recommended 1×
  5. fizyr/keras-retinanet · recommended 1×
  • CATEGORY QUERY
    How can I train a custom object detection model using a Python deep learning framework?
    you: not recommended
    AI recommended (in order):
    1. Detectron2 (facebookresearch/detectron2)
    2. TensorFlow Object Detection API (tensorflow/models)
    3. Ultralytics YOLOv5/YOLOv8 (ultralytics/ultralytics)
    4. MMDetection (open-mmlab/mmdetection)
    5. Keras-RetinaNet (fizyr/keras-retinanet)

    AI recommended 5 alternatives but never named bubbliiiing/yolox-pytorch. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What are efficient deep learning models for real-time object detection with multi-GPU support?
    you: not recommended
    AI recommended (in order):
    1. YOLOv8
    2. YOLOv7
    3. YOLOv5
    4. YOLOv6
    5. PP-YOLOE+
    6. PaddlePaddle
    7. EfficientDet

    AI recommended 7 alternatives but never named bubbliiiing/yolox-pytorch. 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 bubbliiiing/yolox-pytorch?
    pass
    AI named bubbliiiing/yolox-pytorch explicitly

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

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

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

Embed your GEO score

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bubbliiiing/yolox-pytorch — 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