InsightFace vs LandingLens
InsightFace
github.comLandingLens
landing.aiSide by side
| Figure | InsightFace | LandingLens |
|---|---|---|
| Price from | Free | Free |
| Free plan | Yes | Yes |
| Free trial | — | — |
| Open source | Yes | — |
| Web | Yes | Yes |
| Windows | — | Yes |
| macOS | Yes | — |
| Linux | Yes | — |
| iOS | Yes | — |
| API | Yes | Yes |
| Self-hosted | Yes | Yes |
| Plans published | 3 | 2 |
| Spec score · AI Image Recognition Software | 8.7 (#7) | 8.5 (#10) |
| Intended users | The maker presents the product for enterprise use cases including identity verification and KYC, access control, mobile and edge authentication, and large-scale face search. | The maker describes LandingLens as a platform that can scale from a single production line to operations across multiple locations and teams. |
| Support | The open-source offering lists community support through GitHub Issues; commercial model licensing lists email support. | The pricing page lists community and in-product support, while customer success is included with Enterprise. |
Plans
InsightFace
- Open SourceFree
- Enterprise & APIPriced on request
- Model LicensingPriced on request
In their own words
InsightFace
InsightFace provides software for face detection, recognition, alignment, and attribute analysis, with optional liveness, person analysis, video face redaction, and face swapping. PersonAnalysis detects people and faces, then matches them to registered identities using face and body references. PrivateFrame supports local video face tracking and blur or mosaic redaction through desktop, command-line, and Python workflows. Integration options include Python, a C/C++ SDK, and a self-hosted REST API. InsightFace Server runs in a Linux container and offers a web interface, REST API, and Python SDK for detection, comparison, enrollment, search, and RTSP monitoring. The Python package uses ONNX Runtime and requires Python 3.10 or newer. The code is MIT licensed, but pretrained models are limited to non-commercial research unless separately licensed for commercial use. The maker presents enterprise applications such as identity verification, access control, mobile and edge authentication, and large-scale face search. Commercial model use requires a separate license.
LandingLens
LandingLens is a computer vision platform for building, training, and deploying image-based AI models without complex programming. Its workflow moves from uploading and labeling images to model training and deployment. A label book helps teams align on class and label definitions, and labeling tools can detect mislabeled images; multiple users can label together to build consensus. Models can be deployed to cloud or edge environments through options that include a Windows App and programmatic API, and teams can bring deployment data back for retraining. The platform supports managing projects across locations and teams. Deployment choices also include a Snowflake Native App that runs in the customer’s Snowflake environment and a VPC installation in customer AWS, Azure, or GCP environments on Kubernetes. The Free plan costs nothing and provides 1,000 credits per month, unlimited projects, three users, and up to 10,000 images per project. Training and inference stop at the credit limit; model downloads are limited to one active project and use is noncommercial. Enterprise pricing is available by contacting sales.