Flexible LandingLens Deployment Options

Cloud and edge device deployment capabilities make integration into existing environments easy – deploy and test your model with just a few mouse clicks.

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Cloud Deployment
Reduce deployment complexity

  • Reduce time to deploy without needing edge device (IPC) configuration
  • Quickly re-train models upon detecting performance changes
  • Easily scale and manage projects in different locations

Edge Deployment using LandingEdge
Deploy on edge devices

  • An all-in-one application for end-to-end AI deployment
  • Seamless communication with industrial cameras and programmable logic controllers (PLC) for real-time decisions
  •  In-app support for pre-processing and post-processing scripts to manage images and output results

Docker
for advanced integration

A packaged model and inference application that can be installed in different environments.

  • Total API control (including remote access) for model and inference
  • Deployable on a private cloud or on any OS (Windows, Linux, or Mac) with or without a GPU
  • Can be used with existing machine vision system
In App Features
Cloud Deployment
(LandingLens hosted)

Edge Deployment
(LandingEdge)

Docker

Inference Speed (latency)
1 FPS
Up to 2048 x 2048

Up to 30 FPS
(Depends on configuration)

Depends on configuration

OS
OS Agnostic
(Windows, Linux, Mac)

Windows, Linux

OS Agnostic
(Windows, Linux, Mac)

API (upload images, return result in JSON)

Metadata Input/Output

Image Acquisition

Webcam

(GenICam)

PLC
Folder Input/Output
Offline Mode
Post-Processing Scripts
Multi-Inspection Point
Result Dashboard