photo-standardization

Standardize photo capture with lighting, angle, and distance guidance using Swift and Vision.

1|Updated Jan 1, 2026

Search Tags:#swiftui #on-device #standardize-photo #lighting-detection #vision-framework #face-angle #distance-detection

Ready to run

npx skills add https://github.com/raydocs/SkinLab --skill photo-standardization

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: photo-standardization
Source: https://github.com/raydocs/SkinLab/tree/main/.factory/skills/photo-standardization
Command: npx skills add https://github.com/raydocs/SkinLab --skill photo-standardization

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill standardizes photo capture to ensure consistent lighting, angle, and distance for reliable skincare progress tracking.

Core Features & Use Cases

Lighting and angle guidance to standardize captures during daily skincare check-ins.
Real-time feedback for adjustments to lighting, framing, and distance.
Use Case: A user wants to compare before/after skin condition over a 28-day cycle with verifiable photos.

Quick Start

Capture a standardized skincare photo following the on-screen lighting, angle, and distance guidance.

Frequently Asked Questions about photo-standardization

High-intent search queries and answers about installing and using this skill.

FAQPage Schema

How do I standardize photo capture for reliable skincare progress tracking?▼

To standardize photo capture for reliable skincare progress tracking, you use a guided UI with on-device detection to enforce consistent lighting, face angle, and camera distance during daily photo sessions.

How does on-device lighting and face angle detection work in SwiftUI?▼

On-device lighting and face angle detection in SwiftUI uses the Vision framework to analyze camera input and provide real-time feedback, guiding users to adjust framing and distance before capturing the image.

Can I use the Vision framework to detect camera distance for standardized photo capture?▼

Yes, you can use the Vision framework to detect camera distance for standardized photo capture by analyzing facial landmarks on-device, ensuring the user maintains the correct distance from the camera for verifiable results.

What is the best way to compare before and after skin condition over a 28-day cycle?▼

The best way to compare before and after skin condition over a 28-day cycle is to use standardized photo capture that applies consistent lighting, framing, and distance guidance during daily check-ins to ensure verifiable comparisons.

Does this photo standardization approach require any external dependencies?▼

No, this photo standardization approach requires no external dependencies, relying entirely on the native SwiftUI and Vision framework capabilities to fulfill on-device detection requirements.

Why does my skincare photo comparison look inconsistent despite using the same lighting?▼

Skincare photo comparison looks inconsistent if face angle and camera distance vary between sessions, which is why applying real-time on-device detection for standardized photo capture is necessary to achieve verifiable results.