RRepoGEO

REPOGEO REPORT · LITE

Esri/deep-learning-frameworks

Default branch main · commit 1210b410 · scanned 5/31/2026, 6:12:10 PM

GitHub: 624 stars · 136 forks

AI VISIBILITY SCORE
17 /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
1 / 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 Esri/deep-learning-frameworks, 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 sentence to clarify the repo's role as an installer

    Why:

    CURRENT
    ArcGIS Pro, Server and the ArcGIS API for Python all include tools to use AI and Deep Learning to solve geospatial problems, such as feature extraction, pixel classification, and feature categorization.
    COPY-PASTE FIX
    This repository provides the official installers and a curated collection of deep learning libraries and frameworks specifically designed for seamless integration and use within ArcGIS Pro, ArcGIS Server, and the ArcGIS API for Python.
  • hightopics#2
    Add relevant topics to the repository

    Why:

    COPY-PASTE FIX
    deep-learning, machine-learning, geospatial, arcgis, python, pytorch, tensorflow, transformers, fastai, scikit-learn, installer
  • highlicense#3
    Add a LICENSE file to the repository

    Why:

    COPY-PASTE FIX
    Add a LICENSE file to the repository root, containing the text of a standard open-source license such as Apache-2.0 or MIT, or the appropriate Esri license.

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 Esri/deep-learning-frameworks
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
ArcGIS API for Python
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. ArcGIS API for Python · recommended 1×
  2. PyTorch Geometric · recommended 1×
  3. Deep Graph Library · recommended 1×
  4. TensorFlow · recommended 1×
  5. Keras · recommended 1×
  • CATEGORY QUERY
    I need a curated collection of deep learning libraries for geospatial applications.
    you: not recommended
    AI recommended (in order):
    1. ArcGIS API for Python
    2. PyTorch Geometric
    3. Deep Graph Library
    4. TensorFlow
    5. Keras
    6. rasterio
    7. geopandas
    8. shapely
    9. fastai
    10. OpenCV

    AI recommended 10 alternatives but never named Esri/deep-learning-frameworks. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    How can I easily install deep learning packages for Python-based spatial analysis?
    you: not recommended
    AI recommended (in order):
    1. Anaconda/Miniconda
    2. Google Colaboratory (Colab)
    3. Docker
    4. Pip with Virtual Environments
    5. ArcGIS Pro

    AI recommended 5 alternatives but never named Esri/deep-learning-frameworks. 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 Esri/deep-learning-frameworks?
    pass
    AI did not name Esri/deep-learning-frameworks — 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?

  • If a team adopts Esri/deep-learning-frameworks in production, what risks or prerequisites should they evaluate first?
    pass
    AI named Esri/deep-learning-frameworks 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 Esri/deep-learning-frameworks solve, and who is the primary audience?
    pass
    AI did not name Esri/deep-learning-frameworks — 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?

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  • Brand-free category queries5 vs 2 in Lite
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