Refocused vs RestoraX

Refocused is desktop software for enhancing and restoring video with AI models that process footage on the user's machine. Its seven model families cover super-resolution, diffusion restoration, interpolation, denoising, depth estimation, and segmentation. The Refocus model provides motion-aware 4× super-resolution, and a flagship workflow chains it with Regenerate-Q. In the Refine workspace, users can apply tracked object masks, select by depth threshold, reprocess specific regions, and create synthetic depth-of-field focus. Compare offers synchronized A/B playback and up to 8× zoom for inspecting frames. Output can reach 8K and includes 10-bit ProRes, HDR, and image sequences; listed formats include H.265/H.264, ProRes, VP9, AV1, PNG, JPEG, and TIFF. Processing works offline after installation and activation, though license validation and model updates periodically need internet access. A free trial includes full processing and all models, with watermarked output. The Full license is $64.99 as a one-time purchase and includes unlimited local processing, up to five devices, and one year of updates.

RestoraX is a free, open-source toolkit for restoring old films, home videos, and archival footage, as well as anime, VHS, and newsreels. It describes 25 models for tasks including super-resolution, colorization, face restoration, frame interpolation, scratch and dust removal, deinterlacing, stabilization, SDR-to-HDR conversion, and audio restoration. A visual pipeline builder connects processing steps in a DAG, with typed ports, parallel branches, merge strategies, retry policies, and per-branch progress. RestoraX provides a React web interface, a FastAPI REST API with WebSocket progress, a command-line interface, and a ComfyUI node pack. It is self-hostable, with Docker Compose configurations documented for development and production. Third-party restorers can be added through separate PyPI plugins. Model weights download from HuggingFace Hub on first use. The stated minimums are Python 3.11, 8 GB RAM, 5 GB disk, and FFmpeg; CPU works, while CUDA 12.1 or later with at least 8 GB GPU VRAM is recommended. It is released under the MIT License.