Comparison
ailia-models vs metric-learn
Verdict
Pick ailia-models if pre-trained AI models for ailia SDK, covering broad applications from action recognition to audio processing; pick metric-learn if metric-learn is a Python library for metric learning that offers a range of algorithms compatible with scikit-learn's API and supports various methods like LMNN, ITML, LFDA among others.
Markdown twin · ailia-models alternatives · metric-learn alternatives
GraphCanon updated Sep 26, 2026
13views this month
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Trust & integrity
| Signal | ailia-models | metric-learn |
|---|---|---|
| Maintenance | Very active (3d since push) As of Sep 20, 2026 · github_public_v1 | Slowing (190d since push) As of Sep 26, 2026 · github_public_v1 |
| Provenance | Not a fork · Organization account As of Sep 20, 2026 · github_public_v1 | Not a fork · Organization account As of Sep 26, 2026 · github_public_v1 |
| OSV dependency advisories | No lockfile (source not queried) As of Jul 11, 2026 · osv@v1 | No lockfile (source not queried) As of Jul 11, 2026 · osv@v1 |
| deps.dev advisories | Not queried deps.dev@v1 | Not queried deps.dev@v1 |
| OpenSSF Scorecard | Not queried openssf-scorecard@v1 | Not queried openssf-scorecard@v1 |
Tagline
- ailia-models
- Repository of pre-trained AI models for ailia SDK
- metric-learn
- Metric learning algorithms in Python
Stars
- ailia-models
- 2.4k
- metric-learn
- 1.4k
Forks
- ailia-models
- 365
- metric-learn
- 232
Open issues
- ailia-models
- 323
- metric-learn
- 51
Language
- ailia-models
- Python
- metric-learn
- Python
Adopt for
- ailia-models
- Pre-trained AI models for ailia SDK, covering broad applications from action recognition to audio processing.
- metric-learn
- Metric-learn is a Python library for metric learning that offers a range of algorithms compatible with scikit-learn's API and supports various methods like LMNN, ITML, LFDA among others.
Persona
- ailia-models
- -
- metric-learn
- -
Runtime
- ailia-models
- -
- metric-learn
- -
License
- ailia-models
- -
- metric-learn
- MIT
Last pushed
- ailia-models
- Sep 16, 2026
- metric-learn
- Mar 19, 2026
Categories
- ailia-models
- Computer Vision, Model Training, Speech & Audio
- metric-learn
- Model Training
Trust and health
Maintenance
- ailia-models
- Very active (96%)
- metric-learn
- Slowing (36%)
Days since push
- ailia-models
- 3d
- metric-learn
- 190d
Open issues (now)
- ailia-models
- 323
- metric-learn
- 51
Stars delta
- ailia-models
- +35 (30d)
- metric-learn
- -7 (30d)
Open issues delta
- ailia-models
- +7 (30d)
- metric-learn
- 0 (30d)
Full report
- ailia-models
- Trust report
- metric-learn
- Trust report
Shared compatibility
- Python · ailia-models: Python runtime · metric-learn: Python runtime
Choose ailia-models if…
- Tags unique to ailia-models: action-recognition, anomaly-detection, audio-processing, background-removal.
- Also covers Computer Vision, Speech & Audio.
- When developing apps that integrate with the ailia SDK
When NOT to use ailia-models
- If your project does not align with ailia SDK or its specific model categories
- When you require customization beyond what is offered by pre-trained models in this repository
Choose metric-learn if…
- Requirements: The application requires Python version 3.6 or higher and specific dependencies such as numpy, scipy, and scikit-learn..
- Tags unique to metric-learn: machine-learning, metric-learning, python, scikit-learn.
- When you need to use specific metric learning techniques such as Large Margin Nearest Neighbor (LMNN) or Neighborhood Components Analysis (NCA), which are implemented efficiently in Python.
When NOT to use metric-learn
- If your development environment does not already use Python, as metric-learn is specific to this language and its ecosystem.
- For applications that require real-time performance critical operations, since the library may rely on computationally intensive algorithms that could affect latency in real-time systems.
Explore
Sources
Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.
- GitHub stars (ailia-ai/ailia-models) · observed Sep 20, 2026
- GitHub forks (ailia-ai/ailia-models) · observed Sep 20, 2026
- Last push (ailia-ai/ailia-models) · observed Sep 16, 2026
- License file (unknown) · observed Sep 20, 2026
- Decision facts (enrichment) · observed Jul 12, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
- GitHub stars (scikit-learn-contrib/metric-learn) · observed Sep 26, 2026
- GitHub forks (scikit-learn-contrib/metric-learn) · observed Sep 26, 2026
- Last push (scikit-learn-contrib/metric-learn) · observed Mar 19, 2026
- License file (MIT) · observed Sep 26, 2026
- Decision facts (enrichment) · observed Jul 17, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
GitHub stars on cards: ailia-models 2.4k · metric-learn 1.4k (synced Sep 20, 2026).
Common questions
- What is the difference between ailia-models and metric-learn?
- ailia-models: Repository of pre-trained AI models for ailia SDK. metric-learn: Metric learning algorithms in Python. See the comparison table for live GitHub stats and shared categories.
- When should I choose ailia-models over metric-learn?
- Choose ailia-models over metric-learn when Tags unique to ailia-models: action-recognition, anomaly-detection, audio-processing, background-removal; Also covers Computer Vision, Speech & Audio; When developing apps that integrate with the ailia SDK.
- When should I choose metric-learn over ailia-models?
- Choose metric-learn over ailia-models when Requirements: The application requires Python version 3.6 or higher and specific dependencies such as numpy, scipy, and scikit-learn.; Tags unique to metric-learn: machine-learning, metric-learning, python, scikit-learn; When you need to use specific metric learning techniques such as Large Margin Nearest Neighbor (LMNN) or Neighborhood Components Analysis (NCA), which are implemented efficiently in Python.
- When should I avoid ailia-models?
- If your project does not align with ailia SDK or its specific model categories When you require customization beyond what is offered by pre-trained models in this repository
- When should I avoid metric-learn?
- If your development environment does not already use Python, as metric-learn is specific to this language and its ecosystem. For applications that require real-time performance critical operations, since the library may rely on computationally intensive algorithms that could affect latency in real-time systems.
- Is ailia-models or metric-learn more popular on GitHub?
- ailia-models has more GitHub stars (2,392 vs 1,431). Stars measure visibility, not whether either tool fits your constraints.
- Are ailia-models and metric-learn open source?
- Yes - both are open-source projects on GitHub.
- Where can I find alternatives to ailia-models or metric-learn?
- GraphCanon lists graph-backed alternatives at ailia-models alternatives and metric-learn alternatives (ailia-models markdown twin, metric-learn markdown twin), ranked by typed relationship edges rather than popularity votes.
- Is there a machine-readable version of this comparison?
- Yes. The markdown twin at this comparison mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers.
- Which is better maintained, ailia-models or metric-learn?
- ailia-models: Very active. metric-learn: Slowing. Compare maintenance labels, days since push, and release cadence in the trust section below - stars alone do not measure maintenance.
- Where are the full trust reports for ailia-models and metric-learn?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: ailia-models trust report; metric-learn trust report.