REPOGEO REPORT · LITE

Labellerr/Hands-On-Learning-in-Computer-Vision

Default branch main · commit 95e52caa · scanned 6/17/2026, 6:51:46 AM

GitHub: 506 stars · 98 forks

AI VISIBILITY SCORE

22 /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

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 Labellerr/Hands-On-Learning-in-Computer-Vision, 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's opening to emphasize hands-on learning

Why:

CURRENT

👋 Welcome to Labellerr This repository, **Labellerr Notebooks**, offers a growing collection of latest tutorials and notebooks related to AI Agents, computer vision, LLMs, and AI from Labellerr. Dive in to explore the exciting world of AI-powered vision for tasks ranging from object detection and segmentation to robust object tracking and OCR.

COPY-PASTE FIX

👋 Welcome to Labellerr: Your Hands-On Learning Hub for Computer Vision. This repository, **Labellerr Notebooks**, is a dedicated and growing collection of practical tutorials and notebooks designed for hands-on learning in computer vision, AI agents, and LLMs. Dive in to explore the exciting world of AI-powered vision for tasks ranging from object detection and segmentation to robust object tracking and OCR, all with ready-to-run code examples.

hightopics#2

Add specific topics for computer vision learning

Why:

CURRENT

(none)

COPY-PASTE FIX

computer-vision, hands-on-learning, tutorials, notebooks, object-detection, image-segmentation, machine-learning, deep-learning, ai-agents, llms

mediumhomepage#3
Add Labellerr's main website as the repository homepage
Why:
CURRENT
```
(none)
```
COPY-PASTE FIX
```
https://www.labellerr.com/
```

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 Labellerr/Hands-On-Learning-in-Computer-Vision

Avg rank

—

Lower is better. #1 = top recommendation.

Share of voice

Of all named tools, what % are you?

Top rival

PyTorch

Recommended in 2 of 2 queries

COMPETITOR LEADERBOARD

PyTorch · recommended 2×
Keras · recommended 2×
OpenCV · recommended 2×
Towards Data Science · recommended 2×
TensorFlow · recommended 1×

CATEGORY QUERY
Where can I find practical tutorials and notebooks for hands-on computer vision learning?
you: not recommended
AI recommended (in order):
1. PyTorch
2. TensorFlow
3. Keras
4. fast.ai
5. fastai
6. Kaggle
7. OpenCV
8. Towards Data Science
9. Medium
10. GitHub
11. Awesome Computer Vision
AI recommended 11 alternatives but never named Labellerr/Hands-On-Learning-in-Computer-Vision. This is the gap to close.
Show full AI answer
CATEGORY QUERY
What are some good resources for learning object detection and image segmentation with code examples?
you: not recommended
AI recommended (in order):
1. PyTorch
2. TensorFlow Object Detection API
3. Keras
4. OpenCV
5. Papers With Code
6. Towards Data Science
7. Fast.ai
AI recommended 7 alternatives but never named Labellerr/Hands-On-Learning-in-Computer-Vision. 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 Labellerr/Hands-On-Learning-in-Computer-Vision?
pass
AI did not name Labellerr/Hands-On-Learning-in-Computer-Vision — 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 Labellerr/Hands-On-Learning-in-Computer-Vision in production, what risks or prerequisites should they evaluate first?
pass
AI named Labellerr/Hands-On-Learning-in-Computer-Vision 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 Labellerr/Hands-On-Learning-in-Computer-Vision solve, and who is the primary audience?
pass
AI did not name Labellerr/Hands-On-Learning-in-Computer-Vision — 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 Labellerr/Hands-On-Learning-in-Computer-Vision. 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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Deep reports10 / month
Brand-free category queries5 vs 2 in Lite
Prioritized action items8 vs 3 in Lite