Upscale images and videos with open-source super-resolution models.
npx skills add https://github.com/damionrashford/media-os --skill media-upscale
Please help me install this Agent Skill. Skill: media-upscale Source: https://github.com/damionrashford/media-os/tree/main/skills/media-upscale Command: npx skills add https://github.com/damionrashford/media-os --skill media-upscale
AI super-resolution for images and video beyond ffmpeg's outdated built-in DNN models (SRCNN 2014 / ESPCN 2016 / EDSR 2017). Open-source + commercial-safe only: Real-ESRGAN (BSD-3-Clause, the current default for photos/video), Real-CUGAN (MIT, anime-optimized), SwinIR (Apache 2.0, transformer-based), HAT (Apache 2.0, 2023 SOTA), GFPGAN (Apache 2.0, face restoration), waifu2x-ncnn-vulkan (MIT, classic anime), Upscayl (AGPL-3.0, GUI wrapper around Real-ESRGAN), chaiNNer (GPL-3.0, node pipeline for arbitrary models). Realistic 2x / 4x / 8x SR for photos, film scans, low-res archives, anime, screenshots, game textures. Use when the user asks to upscale an image, super-resolution a video, enhance an old photo, restore a face, upscale anime, rescale game textures, do AI upscaling, or when ffmpeg's built-in SRCNN/ESPCN/EDSR isn't good enough.
Invoke the driver script to upscale a single image or video by selecting a model and scale and providing input and output paths.
High-intent search queries and answers about installing and using this skill.
AI super-resolution for video is handled frame-by-frame using open-source models like Real-ESRGAN. The driver script automates the pipeline, validating model availability and composing the correct command sequence for batch or single file processing.
Real-CUGAN (MIT) and waifu2x-ncnn-vulkan (MIT) are anime-optimized open-source models for AI upscaling. SwinIR and HAT offer transformer-based alternatives, while GFPGAN specializes in face restoration for animated and real subjects.
ffmpeg's built-in DNN super-resolution models (SRCNN, ESPCN, EDSR) are outdated. Modern AI upscaling uses open-source, commercial-safe models like Real-ESRGAN, SwinIR, and HAT to achieve realistic 2x, 4x, or 8x scaling for photo restoration.
Yes, batch processing for upscaling game textures and low-res archives is supported through the driver script. The pipeline applies models like Real-ESRGAN or SwinIR across multiple files, validating scale factors and composing sequences automatically.
The super-resolution models used are open-source and commercial-safe, including Real-ESRGAN (BSD-3-Clause), SwinIR (Apache 2.0), and HAT (Apache 2.0). The Skill includes guidance on model selection and license safety via reference documentation.
HAT (2023 SOTA) and SwinIR are transformer-based super-resolution models that often outperform Real-ESRGAN on certain image processing tasks. Real-ESRGAN remains the default for general photos and video, while HAT excels at archival media pipelines.
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eryetUpscale images with waifu2x-ncnn-vulkan and save outputs in the input directory.
