RRepoGEO

REPOGEO REPORT · LITE

jizhishutong/YOLOU

Default branch master · commit 8f5fd6cf · scanned 6/9/2026, 8:07:35 PM

GitHub: 768 stars · 128 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)

2 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 jizhishutong/YOLOU, 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
  • highabout#1
    Rewrite the repository description to clearly state its purpose

    Why:

    CURRENT
    YOLOv3、YOLOv4、YOLOv5、YOLOv5-Lite、YOLOv6-v1、YOLOv6-v2、YOLOv7、YOLOX、YOLOX-Lite、PP-YOLOE、PP-PicoDet-Plus、YOLO-Fastest v2、FastestDet、YOLOv5-SPD、TensorRT、NCNN、Tengine、OpenVINO
    COPY-PASTE FIX
    A unified platform for learning, comparing, and deploying various YOLO object detection models, including support for TensorRT, NCNN, Tengine, and OpenVINO.
  • hightopics#2
    Add more specific and comprehensive topics

    Why:

    CURRENT
    ncnn, openvino, tengine, tensorrt, yolo, yoloe, yolov5, yolov6
    COPY-PASTE FIX
    ncnn, openvino, tengine, tensorrt, yolo, yoloe, yolov5, yolov6, object-detection, computer-vision, deep-learning, model-deployment, ai-framework, unified-framework, machine-learning
  • mediumhomepage#3
    Add a homepage URL to the repository metadata

    Why:

    COPY-PASTE FIX
    https://github.com/jizhishutong/YOLOU

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 jizhishutong/YOLOU
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
ultralytics/ultralytics
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. ultralytics/ultralytics · recommended 2×
  2. WongKinYiu/yolov7 · recommended 1×
  3. ultralytics/yolov5 · recommended 1×
  4. AlexeyAB/darknet · recommended 1×
  5. PaddlePaddle/PaddleDetection · recommended 1×
  • CATEGORY QUERY
    What are the best open-source real-time object detection models for various applications?
    you: not recommended
    AI recommended (in order):
    1. YOLOv8 (ultralytics/ultralytics)
    2. Ultralytics (ultralytics/ultralytics)
    3. YOLOv7 (WongKinYiu/yolov7)
    4. YOLOv5 (ultralytics/yolov5)
    5. YOLOv4 (AlexeyAB/darknet)
    6. PP-YOLOE (PaddlePaddle/PaddleDetection)
    7. NanoDet-Plus (RangiLyu/nanodet)

    AI recommended 7 alternatives but never named jizhishutong/YOLOU. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    How can I efficiently deploy deep learning object detection models on different hardware platforms?
    you: not recommended
    AI recommended (in order):
    1. NVIDIA TensorRT
    2. OpenVINO
    3. ONNX Runtime
    4. TVM
    5. TFLite
    6. PyTorch Mobile

    AI recommended 6 alternatives but never named jizhishutong/YOLOU. 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 jizhishutong/YOLOU?
    pass
    AI named jizhishutong/YOLOU explicitly

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

  • If a team adopts jizhishutong/YOLOU in production, what risks or prerequisites should they evaluate first?
    pass
    AI named jizhishutong/YOLOU 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 jizhishutong/YOLOU solve, and who is the primary audience?
    pass
    AI named jizhishutong/YOLOU 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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MARKDOWN (README)
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jizhishutong/YOLOU — 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