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Professional-grade AI automated image and video correction for high-volume enterprise workflows.

EyeQ, formerly known as Perfectly Clear, is a technical leader in automated image and video correction. Their architecture leverages a combination of physics-based corrections and sophisticated AI models to replicate human eye perception. Unlike standard filters, EyeQ's AI Scene Detection analyzes each pixel to apply 20+ specific corrections ranging from exposure and color vibrancy to noise reduction and skin tone accuracy. By 2026, the platform has matured its 'Real-Time Video' engine, allowing for sub-millisecond per-frame enhancement, making it a critical component for streaming platforms and high-capacity photo printing labs. The technology is primarily delivered via SDKs (C++, Java, Swift) and a RESTful API, catering to developers who need to integrate professional-grade retouching into mobile apps, e-commerce platforms, or automated school/portrait photography workflows. Their market position is established as the 'gold standard' for high-volume batch processing where manual intervention is cost-prohibitive but quality cannot be compromised.
EyeQ, formerly known as Perfectly Clear, is a technical leader in automated image and video correction.
Explore all tools that specialize in ai face retouching. This domain focus ensures EyeQ (Perfectly Clear) delivers optimized results for this specific requirement.
Analyzes the content of an image to identify specifically what it is (landscape, portrait, night, etc.) and applies a custom set of corrections.
Locates faces, eyes, and mouths to apply specialized beautification like teeth whitening and eye enhancement without affecting the background.
A proprietary noise reduction algorithm that targets sensor noise specifically in low-light areas without losing edge detail.
Uses a massive database of human skin tones to ensure AI corrections do not shift ethnicity or natural color during exposure correction.
Enhances video content frame-by-frame while maintaining temporal consistency across the timeline.
Uses EXIF data to identify camera hardware and automatically fix wide-angle distortion and vignetting.
Recovers details in shadows and highlights that appear lost, mimicking the high dynamic range of the human eye.
Request an API key or SDK license via the official EyeQ portal.
Choose deployment method: Cloud API, On-Premise Server, or Client-Side SDK.
Integrate the SDK into your dev environment (C++, C#, Java, Swift, or Objective-C).
Initialize the AI Scene Detection module to analyze incoming assets.
Define 'Preset' parameters or utilize the 'Auto-Intelligence' default settings.
Implement face-aware logic for portrait-specific enhancements like skin smoothing.
Configure output parameters (resolution, file format, color profile).
Run local unit tests against the EyeQ evaluation dataset.
Deploy to production with scalable containerization (Docker supported).
Monitor performance via the EyeQ dashboard for credit usage and throughput.
All Set
Ready to go
Verified feedback from other users.
"Users praise the speed and the 'natural' look of the AI, noting it avoids the artificial 'AI-generated' plastic look of competitors."
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