Home/Compare/TengineKit vs face.evoLVe

Comparison

TengineKit vs face.evoLVe

Verdict

Pick TengineKit if tengineKit is an easy-to-integrate AI algorithm SDK targeting mobile platforms for real-time detection and recognition tasks like face and body landmarks, attributes, hand detections; pick face.evoLVe if face.evoLVe offers a high-performance face recognition solution using both PaddlePaddle and PyTorch frameworks.

Markdown twin · TengineKit alternatives · face.evoLVe alternatives

GraphCanon updated 2d

TengineKit logo

TengineKit

OAID/TengineKit

2.3kpushed Oct 18, 2021
vs
face.evoLVe logo

face.evoLVe

ZhaoJ9014/face.evoLVe

3.6kpushed Mar 20, 2025

Trust & integrity

SignalTengineKitface.evoLVe
Maintenance
Dormant (1746d 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

TengineKit
TengineKit - Real-Time Mobile AI Algorithm SDK
face.evoLVe
High-Performance Face Recognition Library on PaddlePaddle & PyTorch

Stars

TengineKit
2.3k
face.evoLVe
3.6k

Forks

TengineKit
307
face.evoLVe
760

Open issues

TengineKit
32
face.evoLVe
96

Language

TengineKit
C++
face.evoLVe
Python

Adopt for

TengineKit
TengineKit is an easy-to-integrate AI algorithm SDK targeting mobile platforms for real-time detection and recognition tasks like face and body landmarks, attributes, hand detections.
face.evoLVe
face.evoLVe offers a high-performance face recognition solution using both PaddlePaddle and PyTorch frameworks.

Persona

TengineKit
-
face.evoLVe
-

Runtime

TengineKit
-
face.evoLVe
-

License

TengineKit
Other
face.evoLVe
MIT License allows free use and distribution with attribution.

Last pushed

TengineKit
Oct 18, 2021
face.evoLVe
Mar 20, 2025

Categories

TengineKit
Computer Vision
face.evoLVe
Computer Vision, Model Training

Trust and health

Days since push

TengineKit
1746d
face.evoLVe
521d

Open issues (now)

TengineKit
32
face.evoLVe
96

Stars delta

TengineKit
Unknown
face.evoLVe
+3 (30d)

Open issues delta

TengineKit
Unknown
face.evoLVe
0 (30d)

Owner type

TengineKit
Organization
face.evoLVe
User

Full report

TengineKit
Trust report
face.evoLVe
Trust report

Choose TengineKit if…

  • TengineKit is primarily C++; face.evoLVe is Python.
  • License: TengineKit is Other, face.evoLVe is MIT.
  • Requirements: The tool requires C++ skills to be effectively utilized in development.; Performance optimization is reported on select mobile platforms, mainly focusing on Kirin and Qualcomm series..
  • Tags unique to TengineKit: ai, android, deep-neural-networks, face-api.
  • You aim to integrate comprehensive real-time AI algorithms on mobile devices such as face detection, landmarks, and attributes with low latency.

When NOT to use TengineKit

  • Your project does not require features like hand or body detection/landmarks in real-time on mobile devices, as these are not fully supported yet on the mobile platform provided by this SDK.
  • The necessity of using an open-source license is a critical factor for your decision since TengineKit's license is listed as 'Other', suggesting restrictions may apply.

Choose face.evoLVe if…

  • face.evoLVe is primarily Python; TengineKit is C++.
  • License: face.evoLVe is MIT, TengineKit is Other.
  • Tags unique to face.evoLVe: convolutional-neural-network, data-augmentation, deep-learning, face-detection.
  • Also covers Model Training.
  • 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 on cards: TengineKit 2.3k · face.evoLVe 3.6k (synced Jul 31, 2026).

Common questions

What is the difference between TengineKit and face.evoLVe?
TengineKit: TengineKit - Real-Time Mobile AI Algorithm SDK. 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 TengineKit over face.evoLVe?
Choose TengineKit over face.evoLVe when TengineKit is primarily C++; face.evoLVe is Python; License: TengineKit is Other, face.evoLVe is MIT; Requirements: The tool requires C++ skills to be effectively utilized in development.; Performance optimization is reported on select mobile platforms, mainly focusing on Kirin and Qualcomm series.; Tags unique to TengineKit: ai, android, deep-neural-networks, face-api; You aim to integrate comprehensive real-time AI algorithms on mobile devices such as face detection, landmarks, and attributes with low latency.
When should I choose face.evoLVe over TengineKit?
Choose face.evoLVe over TengineKit when face.evoLVe is primarily Python; TengineKit is C++; License: face.evoLVe is MIT, TengineKit is Other; Tags unique to face.evoLVe: convolutional-neural-network, data-augmentation, deep-learning, face-detection; Also covers Model Training; Prefer this when developing applications that need integration with Tencent's PaddlePaddle framework.
When should I avoid TengineKit?
Your project does not require features like hand or body detection/landmarks in real-time on mobile devices, as these are not fully supported yet on the mobile platform provided by this SDK. The necessity of using an open-source license is a critical factor for your decision since TengineKit's license is listed as 'Other', suggesting restrictions may apply.
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 TengineKit or face.evoLVe more popular on GitHub?
face.evoLVe has more GitHub stars (3,589 vs 2,320). Stars measure visibility, not whether either tool fits your constraints.
Are TengineKit and face.evoLVe open source?
Yes - both are open-source projects on GitHub (TengineKit: Other, face.evoLVe: MIT).
Where can I find alternatives to TengineKit or face.evoLVe?
GraphCanon lists graph-backed alternatives at TengineKit alternatives and face.evoLVe alternatives (TengineKit 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, TengineKit or face.evoLVe?
TengineKit: Dormant. 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 TengineKit and face.evoLVe?
GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: TengineKit trust report; face.evoLVe trust report.

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