REPOGEO REPORT · LITE

ZhaoJ9014/face.evoLVe

Default branch master · commit a9897bda · scanned 5/11/2026, 6:12:55 PM

GitHub: 3,587 stars · 761 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 ZhaoJ9014/face.evoLVe, 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
Add homepage URL to repository About section
Why:
COPY-PASTE FIX
```
https://zhaoj9014.github.io
```

highreadme#2

Strengthen README's opening value proposition

Why:

CURRENT

* Evolve to be more comprehensive, effective and efficient for face related analytics & applications! (WeChat News)
* About the name:
  * "face" means this repo is dedicated for face related analytics & applications.
  * "evolve" means unleash your greatness to be better and better. "LV" are capitalized to acknowledge the nurturing of Learning and Vision (LV) group, Nation University of Singapore (NUS).

COPY-PASTE FIX

face.evoLVe is a high-performance, comprehensive, and efficient library for face recognition and related analytics, built on both PaddlePaddle and PyTorch. It aims to provide state-of-the-art models and tools for researchers and developers in computer vision and AI applications.

mediumtopics#3

Add 'paddlepaddle' to repository topics

Why:

CURRENT

artificial-intelligence, computer-vision, convolutional-neural-network, data-augmentation, deep-learning, face-alignment, face-detection, face-landmark-detection, face-recognition, feature-extraction, fine-tuning, hard-negative-mining, imbalanced-learning, machine-learning, model-training, nus, pytorch, supervised-learning, tencent, transfer-learning

COPY-PASTE FIX

artificial-intelligence, computer-vision, convolutional-neural-network, data-augmentation, deep-learning, face-alignment, face-detection, face-landmark-detection, face-recognition, feature-extraction, fine-tuning, hard-negative-mining, imbalanced-learning, machine-learning, model-training, nus, paddlepaddle, pytorch, supervised-learning, tencent, transfer-learning

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 ZhaoJ9014/face.evoLVe

Avg rank

—

Lower is better. #1 = top recommendation.

Share of voice

Of all named tools, what % are you?

Top rival

OpenCV

Recommended in 2 of 2 queries

COMPETITOR LEADERBOARD

OpenCV · recommended 2×
PyTorch · recommended 2×
TensorFlow · recommended 2×
InsightFace · recommended 1×
FaceNet · recommended 1×

CATEGORY QUERY
What are reliable deep learning libraries for high-performance face recognition and analytics?
you: not recommended
AI recommended (in order):
1. InsightFace
2. FaceNet
3. Dlib
4. OpenCV
5. PyTorch
6. TensorFlow
AI recommended 6 alternatives but never named ZhaoJ9014/face.evoLVe. This is the gap to close.
Show full AI answer
CATEGORY QUERY
Looking for a flexible deep learning framework for face detection, alignment, and feature extraction.
you: not recommended
AI recommended (in order):
1. PyTorch
2. TensorFlow
3. MMDetection
4. MMFace
5. OpenCV
6. MXNet
AI recommended 6 alternatives but never named ZhaoJ9014/face.evoLVe. 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 ZhaoJ9014/face.evoLVe?
pass
AI did not name ZhaoJ9014/face.evoLVe — 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 ZhaoJ9014/face.evoLVe in production, what risks or prerequisites should they evaluate first?
pass
AI named ZhaoJ9014/face.evoLVe 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 ZhaoJ9014/face.evoLVe solve, and who is the primary audience?
pass
AI named ZhaoJ9014/face.evoLVe explicitly
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 ZhaoJ9014/face.evoLVe. It auto-updates whenever the report is rescanned and links back to the latest report — easy public proof that you care about AI discoverability.

Live preview

MARKDOWN (README)

[![RepoGEO](https://repogeo.com/badge/ZhaoJ9014/face.evoLVe.svg)](https://repogeo.com/en/r/ZhaoJ9014/face.evoLVe)

HTML

<a href="https://repogeo.com/en/r/ZhaoJ9014/face.evoLVe"><img src="https://repogeo.com/badge/ZhaoJ9014/face.evoLVe.svg" alt="RepoGEO" /></a>

Pro

Subscribe to Pro for deep diagnoses

ZhaoJ9014/face.evoLVe — 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