Photo and video workspaces
Separate workspaces support video remuxing, compression, cleanup, natural upscale, photo conversion, resize options, metadata handling, and export summaries.
Portfolio Case Study
ClearFrame local media utility.
A local-first media app for inspecting, converting, compressing, cleaning, and preparing photo and video files on Apple devices.
Project Context
Media cleanup without sending files to the cloud.
ClearFrame is built as a local-first media utility with a React interface, Tauri shell, Rust command layer, FFmpeg/FFprobe processing, SQLite preferences, and app packaging. The current app focuses on practical file handling before promising model-driven enhancement.
The work includes video and photo workspaces, drag-and-drop imports, metadata inspection, conversion presets, compression controls, cleanup filters, processing history, export summaries, and AI engine boundaries for later Core ML or Real-ESRGAN validation.
Queue and history system
Jobs move through queued, running, completed, failed, and canceled states with progress, output paths, size changes, and history cleanup.
Replaceable AI boundaries
AI restoration is framed honestly with model-folder detection, runtime checks, install guidance, and queue messages when local models are missing.
Local processing.
FFmpeg, FFprobe, macOS metadata tools, hardware encoding, and local app storage keep media handling on the user's machine.
Honest AI roadmap.
The interface separates current cleanup features from future AI inference so generated detail is not described as recovered truth.
Packaged app path.
The build produces a macOS app bundle and includes icon assets used for platform packaging and installation workflows.
Need a practical app concept made usable?
Greenhouse can help define product scope, interface behavior, local processing, AI boundaries, and packaging paths.