RRepoGEO

REPOGEO REPORT · LITE

PINTO0309/onnx2tf

Default branch main · commit cb24e238 · scanned 5/31/2026, 7:31:47 PM

GitHub: 961 stars · 100 forks

AI VISIBILITY SCORE
28 /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
2 / 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 PINTO0309/onnx2tf, 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
  • mediumabout#1
    Add a homepage URL to the repository's 'About' section

    Why:

    COPY-PASTE FIX
    https://github.com/PINTO0309/onnx2tf
  • mediumreadme#2
    Enhance README's initial description to highlight mobile deployment

    Why:

    CURRENT
    A tool for converting ONNX files to LiteRT/TFLite/TensorFlow, PyTorch native code (nn.Module), TorchScript (.pt), state_dict (.pt), Exported Program (.pt2), and Dynamo ONNX. It also supports direct conversion from LiteRT to PyTorch.
    COPY-PASTE FIX
    onnx2tf is a versatile tool for converting ONNX deep learning models to formats optimized for various platforms, including LiteRT, TFLite, and TensorFlow for efficient mobile and edge device deployment, as well as PyTorch native code, TorchScript, state_dict, Exported Program, and Dynamo ONNX.

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 PINTO0309/onnx2tf
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
tensorflow/tensorflow
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. tensorflow/tensorflow · recommended 2×
  2. microsoft/onnxruntime · recommended 2×
  3. pytorch/pytorch · recommended 2×
  4. apple/coremltools · recommended 1×
  5. alibaba/MNN · recommended 1×
  • CATEGORY QUERY
    How can I convert ONNX deep learning models for deployment on mobile devices?
    you: not recommended
    AI recommended (in order):
    1. Core ML Tools (apple/coremltools)
    2. TensorFlow Lite (TFLite) Converter (tensorflow/tensorflow)
    3. ONNX Runtime Mobile (microsoft/onnxruntime)
    4. PyTorch Mobile (pytorch/pytorch)
    5. MNN (alibaba/MNN)
    6. NCNN (Tencent/ncnn)

    AI recommended 6 alternatives but never named PINTO0309/onnx2tf. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What tools exist for converting deep learning models between ONNX, PyTorch, and TensorFlow formats?
    you: not recommended
    AI recommended (in order):
    1. ONNX Runtime (microsoft/onnxruntime)
    2. MMdnn (Microsoft/MMdnn)
    3. ONNX-TensorFlow (onnx/onnx-tensorflow)
    4. ONNX-PyTorch (Torch.onnx) (pytorch/pytorch)
    5. TensorFlow Lite Converter (TFLite Converter) (tensorflow/tensorflow)
    6. Keras to ONNX (keras2onnx) (onnx/keras-onnx)

    AI recommended 6 alternatives but never named PINTO0309/onnx2tf. 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 PINTO0309/onnx2tf?
    pass
    AI named PINTO0309/onnx2tf explicitly

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

  • If a team adopts PINTO0309/onnx2tf in production, what risks or prerequisites should they evaluate first?
    pass
    AI named PINTO0309/onnx2tf 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 PINTO0309/onnx2tf solve, and who is the primary audience?
    pass
    AI did not name PINTO0309/onnx2tf — likely talking about a different project

    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 PINTO0309/onnx2tf. 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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MARKDOWN (README)
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PINTO0309/onnx2tf — 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