GibbonPfp 0.1.0

GibbonPfp 0.1.0 is an offline Qt desktop application and CLI for preparing profile pictures.

• Single-photo and batch workflows, with default 360 × 480 portrait output and optional uncapped/custom sizes.
• Face-aware cropping, adjustable headroom, manual framing, and review gates for uncertain photos.
• Perceptual brightness, reference matching, lightweight background removal, mask brushes, and JPEG/PNG output.
• JPEG, PNG, TIFF, WebP, SDR HEIC, and camera RAW input; RAW white balance and highlight controls.
• Presets, sessions, collision-safe exports, reports, and Strider-inspired light/dark themes.

Download	Target
Windows installer or ZIP	Windows 11 x64
AppImage	Ubuntu 24.04+ x64
macos-x64 DMG	macOS 14+ Intel
macos-arm64 DMG	macOS 14+ Apple Silicon

Windows packages are unsigned. Mac applications are ad-hoc signed, not notarized; operating-system publisher checks may require explicit approval to open them. No Python or Qt installation is needed to run the packages.

Linux: make the AppImage executable, then open it. If FUSE is unavailable, run APPIMAGE_EXTRACT_AND_RUN=1 ./GibbonPfp-0.1.0-x86_64.AppImage. Windows ZIP: extract the entire archive and run bin/gibbonpfp.exe. macOS: open the DMG and copy gibbonpfp.app to Applications.

The small face and Fast segmentation models are bundled. The optional High Quality model is a separate 973 MB download and can use about 7 GB RAM on CPU. Photos are processed locally.

Validation includes native core/controller tests, GUI startup, relocated-package checks without Qt SDK search paths, RAW/HEIC decoding, and 16 MP/24 MP CLI inputs. CI uses Ubuntu 24.04, Windows Server 2022, and macOS 15 Intel/ARM runners. The Linux AppImage is additionally checked on EndeavourOS. Minimum target OS versions are not each tested separately.

See README for usage and limitations, and building/distribution for dependencies and signing. SHA256SUMS.txt lists the package hashes.

Verified build: all four native CI jobs passed, commit 153f8ae.