Comparison
autokeras vs face.evoLVe
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.
Markdown twin · autokeras alternatives · face.evoLVe alternatives
GraphCanon updated 2d
vs
Trust & integrity
| Signal | autokeras | face.evoLVe |
|---|---|---|
| Maintenance | Slowing (251d since push) As of 3w · github_public_v1 | Dormant (521d since push) As of 2d · github_public_v1 |
| Provenance | Not a fork · Organization account As of 3w · github_public_v1 | Not a fork · Personal account As of 2d · github_public_v1 |
| OSV dependency advisories | No lockfile (source not queried) As of 1mo · osv@v1 | No lockfile (source not queried) As of 1mo · 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
- autokeras
- AutoML library for deep learning
- face.evoLVe
- High-Performance Face Recognition Library on PaddlePaddle & PyTorch
Stars
- autokeras
- 9.3k
- face.evoLVe
- 3.6k
Forks
- autokeras
- 1.4k
- face.evoLVe
- 760
Open issues
- autokeras
- 161
- face.evoLVe
- 96
Language
- autokeras
- Python
- face.evoLVe
- Python
Adopt for
- autokeras
- 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
- face.evoLVe offers a high-performance face recognition solution using both PaddlePaddle and PyTorch frameworks.
Persona
- autokeras
- -
- face.evoLVe
- -
Runtime
- autokeras
- -
- face.evoLVe
- -
License
- autokeras
- Apache-2.0
- face.evoLVe
- MIT License allows free use and distribution with attribution.
Last pushed
- autokeras
- Nov 25, 2025
- face.evoLVe
- Mar 20, 2025
Categories
- autokeras
- Developer Tools, Model Training
- face.evoLVe
- Computer Vision, Model Training
Trust and health
Maintenance
- autokeras
- Slowing (36%)
- face.evoLVe
- Dormant (18%)
Days since push
- autokeras
- 251d
- face.evoLVe
- 521d
Open issues (now)
- autokeras
- 161
- face.evoLVe
- 96
Stars delta
- autokeras
- Unknown
- face.evoLVe
- +3 (30d)
Open issues delta
- autokeras
- Unknown
- face.evoLVe
- 0 (30d)
Owner type
- autokeras
- Organization
- face.evoLVe
- User
Full report
- autokeras
- Trust report
- face.evoLVe
- Trust report
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.
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.
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 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.
Explore
Sources
Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.
- GitHub stars (keras-team/autokeras) · observed Aug 4, 2026
- GitHub forks (keras-team/autokeras) · observed Aug 4, 2026
- Last push (keras-team/autokeras) · observed Nov 25, 2025
- License file (Apache-2.0) · observed Aug 4, 2026
- Decision facts (enrichment) · observed Jul 17, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
- GitHub stars (ZhaoJ9014/face.evoLVe) · observed Aug 23, 2026
- GitHub forks (ZhaoJ9014/face.evoLVe) · observed Aug 23, 2026
- Last push (ZhaoJ9014/face.evoLVe) · observed Mar 20, 2025
- License file (MIT) · observed Aug 23, 2026
- Decision facts (enrichment) · observed Jul 12, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
GitHub stars on cards: autokeras 9.3k · face.evoLVe 3.6k (synced Aug 4, 2026).
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 and face.evoLVe alternatives (autokeras markdown twin, face.evoLVe 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, 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; face.evoLVe trust report.