--- title: "autokeras vs face.evoLVe" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/keras-team-autokeras-vs-zhaoj9014-face-evolve" tools: ["keras-team-autokeras", "zhaoj9014-face-evolve"] --- # autokeras vs face.evoLVe *GraphCanon updated Aug 23, 2026* ## Verdict Pick autokeras if autoKeras simplifies deep learning model design through automated neural architecture search and is compatible with Python 3.7+ and TensorFlow 2.8.0+; pick face.evoLVe if face.evoLVe offers a high-performance face recognition solution using both PaddlePaddle and PyTorch frameworks. [autokeras](http://autokeras.com/) reports 9.3k GitHub stars, 1.4k forks, and 161 open issues, last pushed Nov 25, 2025. [face.evoLVe](https://github.com/ZhaoJ9014/face.evoLVe) has 3.6k stars, 760 forks, and 96 open issues, last pushed Mar 20, 2025. Figures are from public GitHub metadata via [autokeras's repository](https://github.com/keras-team/autokeras) and [face.evoLVe's repository](https://github.com/ZhaoJ9014/face.evoLVe). | | [autokeras](/tools/keras-team-autokeras.md) | [face.evoLVe](/tools/zhaoj9014-face-evolve.md) | | --- | --- | --- | | Tagline | AutoML library for deep learning | High-Performance Face Recognition Library on PaddlePaddle & PyTorch | | Stars | 9,328 | 3,589 | | Forks | 1,393 | 760 | | Open issues | 161 | 96 | | Language | Python | Python | | Adopt for | AutoKeras simplifies deep learning model design through automated neural architecture search and is compatible with Python 3.7+ and TensorFlow 2.8.0+. | face.evoLVe offers a high-performance face recognition solution using both PaddlePaddle and PyTorch frameworks. | | Persona | - | - | | Runtime | - | - | | License | Apache-2.0 | MIT License allows free use and distribution with attribution. | | Categories | Developer Tools, Model Training | Computer Vision, Model Training | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [autokeras](/tools/keras-team-autokeras.md) | [face.evoLVe](/tools/zhaoj9014-face-evolve.md) | | --- | --- | --- | | Maintenance | Slowing (36%) | Dormant (18%) | | Days since push | 251d | 521d | | Open issues (now) | 161 | 96 | | Stars delta | Unknown | +3 (30d) | | Open issues delta | Unknown | 0 (30d) | | Owner type | Organization | User | | Full report | [trust report](/tools/keras-team-autokeras/trust.md) | [trust report](/tools/zhaoj9014-face-evolve/trust.md) | ## Decision facts: autokeras - **Adopt for:** AutoKeras simplifies deep learning model design through automated neural architecture search and is compatible with Python 3.7+ and TensorFlow 2.8.0+. ## Decision facts: face.evoLVe - **Adopt for:** face.evoLVe offers a high-performance face recognition solution using both PaddlePaddle and PyTorch frameworks. - **License detail:** MIT License allows free use and distribution with attribution. ## Choose when ### Choose autokeras if… - License: autokeras is Apache-2.0, face.evoLVe is MIT. - Tags unique to autokeras: autodl, automl, keras, machine-learning. - Also covers Developer Tools. - When your project involves deep learning tasks requiring minimal manual intervention in designing models. ### Choose face.evoLVe if… - License: face.evoLVe is MIT, autokeras is Apache-2.0. - Tags unique to face.evoLVe: artificial-intelligence, computer-vision, convolutional-neural-network, data-augmentation. - Also covers Computer Vision. - Prefer this when developing applications that need integration with Tencent's PaddlePaddle framework. ## When NOT to use autokeras - When working with Python versions older than 3.7 or TensorFlow versions older than 2.8.0, as AutoKeras is not compatible. - If your project emphasizes transparent, understandable model architecture over automated generation without human oversight. ## When NOT to use face.evoLVe - Avoid using if your project only supports frameworks besides PaddlePaddle and PyTorch. - If the primary focus of your application is not related to face recognition tasks, this might be overkill. - Steer clear if you do not require advanced feature extraction methods or imbalanced learning support for face data. ## Common questions ### What is the difference between autokeras and face.evoLVe? autokeras: AutoML library for deep learning. face.evoLVe: High-Performance Face Recognition Library on PaddlePaddle & PyTorch. See the comparison table for live GitHub stats and shared categories. ### When should I choose autokeras over face.evoLVe? Choose autokeras over face.evoLVe when License: autokeras is Apache-2.0, face.evoLVe is MIT; Tags unique to autokeras: autodl, automl, keras, machine-learning; Also covers Developer Tools; When your project involves deep learning tasks requiring minimal manual intervention in designing models. ### When should I choose face.evoLVe over autokeras? Choose face.evoLVe over autokeras when License: face.evoLVe is MIT, autokeras is Apache-2.0; Tags unique to face.evoLVe: artificial-intelligence, computer-vision, convolutional-neural-network, data-augmentation; Also covers Computer Vision; Prefer this when developing applications that need integration with Tencent's PaddlePaddle framework. ### When should I avoid autokeras? When working with Python versions older than 3.7 or TensorFlow versions older than 2.8.0, as AutoKeras is not compatible. If your project emphasizes transparent, understandable model architecture over automated generation without human oversight. ### When should I avoid face.evoLVe? Avoid using if your project only supports frameworks besides PaddlePaddle and PyTorch. If the primary focus of your application is not related to face recognition tasks, this might be overkill. Steer clear if you do not require advanced feature extraction methods or imbalanced learning support for face data. ### Is autokeras or face.evoLVe more popular on GitHub? autokeras has more GitHub stars (9,328 vs 3,589). Stars measure visibility, not whether either tool fits your constraints. ### Are autokeras and face.evoLVe open source? Yes - both are open-source projects on GitHub (autokeras: Apache-2.0, face.evoLVe: MIT). ### Where can I find alternatives to autokeras or face.evoLVe? GraphCanon lists graph-backed alternatives at [autokeras alternatives](/tools/keras-team-autokeras/alternatives) and [face.evoLVe alternatives](/tools/zhaoj9014-face-evolve/alternatives) ([autokeras markdown twin](/tools/keras-team-autokeras/alternatives.md), [face.evoLVe markdown twin](/tools/zhaoj9014-face-evolve/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/keras-team-autokeras-vs-zhaoj9014-face-evolve.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, autokeras or face.evoLVe? autokeras: Slowing. face.evoLVe: Dormant. 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 autokeras and face.evoLVe? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [autokeras trust report](/tools/keras-team-autokeras/trust); [face.evoLVe trust report](/tools/zhaoj9014-face-evolve/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=keras-team-autokeras`](/api/graphcanon/graph?tool=keras-team-autokeras) - 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/_