--- title: "ailia-models vs metric-learn" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/ailia-ai-ailia-models-vs-scikit-learn-contrib-metric-learn" tools: ["ailia-ai-ailia-models", "scikit-learn-contrib-metric-learn"] --- # ailia-models vs metric-learn *GraphCanon updated Aug 22, 2026* ## 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. [ailia-models](https://github.com/ailia-ai/ailia-models) reports 2.4k GitHub stars, 363 forks, and 321 open issues, last pushed Aug 21, 2026. [metric-learn](http://contrib.scikit-learn.org/metric-learn/) has 1.4k stars, 231 forks, and 51 open issues, last pushed Mar 19, 2026. Figures are from public GitHub metadata via [ailia-models's repository](https://github.com/ailia-ai/ailia-models) and [metric-learn's repository](https://github.com/scikit-learn-contrib/metric-learn). | | [ailia-models](/tools/ailia-ai-ailia-models.md) | [metric-learn](/tools/scikit-learn-contrib-metric-learn.md) | | --- | --- | --- | | Tagline | Repository of pre-trained AI models for ailia SDK | Metric learning algorithms in Python | | Stars | 2,365 | 1,438 | | Forks | 363 | 231 | | Open issues | 321 | 51 | | Language | Python | Python | | Adopt for | Pre-trained AI models for ailia SDK, covering broad applications from action recognition to audio processing. | 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 | - | - | | Runtime | - | - | | License | - | MIT | | Categories | Computer Vision, Model Training, Speech & Audio | Model Training | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [ailia-models](/tools/ailia-ai-ailia-models.md) | [metric-learn](/tools/scikit-learn-contrib-metric-learn.md) | | --- | --- | --- | | Maintenance | Very active (96%) | Slowing (36%) | | Days since push | 0d | 136d | | Open issues (now) | 321 | 51 | | Stars delta | +8 (30d) | Unknown | | Open issues delta | +5 (30d) | Unknown | | Full report | [trust report](/tools/ailia-ai-ailia-models/trust.md) | [trust report](/tools/scikit-learn-contrib-metric-learn/trust.md) | ## Shared compatibility - **Python**: [ailia-models](/tools/ailia-ai-ailia-models.md) - Python runtime; [metric-learn](/tools/scikit-learn-contrib-metric-learn.md) - Python runtime ## Decision facts: ailia-models - **Adopt for:** Pre-trained AI models for ailia SDK, covering broad applications from action recognition to audio processing. ## Decision facts: metric-learn - **Requirements:** The application requires Python version 3.6 or higher and specific dependencies such as numpy, scipy, and scikit-learn. - **Adopt for:** 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. ## Choose when ### 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 ### 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 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 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. ## 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 (2,365 vs 1,438). 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](/tools/ailia-ai-ailia-models/alternatives) and [metric-learn alternatives](/tools/scikit-learn-contrib-metric-learn/alternatives) ([ailia-models markdown twin](/tools/ailia-ai-ailia-models/alternatives.md), [metric-learn markdown twin](/tools/scikit-learn-contrib-metric-learn/alternatives.md)), 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](/compare/ailia-ai-ailia-models-vs-scikit-learn-contrib-metric-learn.md) 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](/tools/ailia-ai-ailia-models/trust); [metric-learn trust report](/tools/scikit-learn-contrib-metric-learn/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=ailia-ai-ailia-models`](/api/graphcanon/graph?tool=ailia-ai-ailia-models) - LLM index: [/llms.txt](/llms.txt) - Full corpus: [/llms-full.txt](/llms-full.txt) _GraphCanon - The knowledge graph for AI development. https://www.graphcanon.com/_