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Description
Fovea is a cutting-edge culling solution tailored for professional photographers, emphasizing high performance and efficiency. Developed using Swift, Metal, and optimized for Apple Silicon, it addresses workflow inefficiencies through its unique "Precision Vision" methodology. In contrast to cloud-based alternatives, Fovea’s Privacy-First AI operates entirely on the device, thereby guaranteeing both instantaneous responsiveness and complete security for your RAW image collections.
Notable Features:
Style Learning: An AI model that learns your individual preferences for selecting photos over time.
Smart Culling: Automatically groups similar shots and identifies the sharpest and most well-composed image through on-device focus analysis.
Close-Ups Panel: Quickly evaluate facial focus and expressions among subjects without the need for manual zoom adjustments.
Omni-Channel Preview: Provides live overlays for social media platforms (like Instagram and TikTok) with intelligent face centering.
Pro Shot Lists: Offers ready-to-use templates for specific events such as Weddings and Real Estate, complete with automatic renaming for exports.
Seamless Workflow: Directly incorporates ratings into XMP files for enhanced organization. Furthermore, Fovea’s intuitive interface ensures that users can navigate through their images effortlessly, making the culling process a breeze.
Description
LiteRT, previously known as TensorFlow Lite, is an advanced runtime developed by Google that provides high-performance capabilities for artificial intelligence on devices. This platform empowers developers to implement machine learning models on multiple devices and microcontrollers with ease. Supporting models from prominent frameworks like TensorFlow, PyTorch, and JAX, LiteRT converts these models into the FlatBuffers format (.tflite) for optimal inference efficiency on devices. Among its notable features are minimal latency, improved privacy by handling data locally, smaller model and binary sizes, and effective power management. The runtime also provides SDKs in various programming languages, including Java/Kotlin, Swift, Objective-C, C++, and Python, making it easier to incorporate into a wide range of applications. To enhance performance on compatible devices, LiteRT utilizes hardware acceleration through delegates such as GPU and iOS Core ML. The upcoming LiteRT Next, which is currently in its alpha phase, promises to deliver a fresh set of APIs aimed at simplifying the process of on-device hardware acceleration, thereby pushing the boundaries of mobile AI capabilities even further. With these advancements, developers can expect more seamless integration and performance improvements in their applications.
API Access
Has API
API Access
Has API
Screenshots View All
No images available
Integrations
C++
Google AI Edge Gallery
JAX
Java
Kotlin
Objective-C
PyTorch
Python
Swift
TensorFlow
Integrations
C++
Google AI Edge Gallery
JAX
Java
Kotlin
Objective-C
PyTorch
Python
Swift
TensorFlow
Pricing Details
$60/year
Free Trial
Free Version
Pricing Details
Free
Free Trial
Free Version
Deployment
Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook
Deployment
Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook
Customer Support
Business Hours
Live Rep (24/7)
Online Support
Customer Support
Business Hours
Live Rep (24/7)
Online Support
Types of Training
Training Docs
Webinars
Live Training (Online)
In Person
Types of Training
Training Docs
Webinars
Live Training (Online)
In Person
Vendor Details
Company Name
Fovea
Founded
2026
Country
Australia
Website
get-fovea.app/
Vendor Details
Company Name
Founded
1998
Country
United States
Website
ai.google.dev/edge/litert
Product Features
Product Features
Artificial Intelligence
Chatbot
For Healthcare
For Sales
For eCommerce
Image Recognition
Machine Learning
Multi-Language
Natural Language Processing
Predictive Analytics
Process/Workflow Automation
Rules-Based Automation
Virtual Personal Assistant (VPA)