Search Results for "multi-objective optimization"

FFmpeg Quality Metrics is a Python-based tool that evaluates video quality by calculating objective metrics using FFmpeg. It supports widely used metrics such as PSNR, SSIM, VIF, MSAD, and VMAF, enabling detailed comparison between reference and distorted video files. The tool outputs both per-frame data and aggregated statistics like averages and standard deviation, making it useful for research, encoding optimization, and benchmarking.

ImageRevise is a streamlined Tkinter-based application that makes image resizing and optimization effortless. With its intuitive interface, you can easily resize images while maintaining the aspect ratio, add custom watermarks with customizable positions, and optimize images for web use by adjusting quality levels. The application also lets you view and remove EXIF metadata, ensuring privacy and reducing file size. Features like multi-threaded image processing keep the app responsive during operations and enhance the overall user experience. ...

v6.0. Warlock-Studio is a Windows application that uses Real-ESRGAN, BSRGAN, IRCNN, GFPGAN, RealESRNet, RealESRAnime and RIFE Artificial Intelligence models to upscale, restore faces, interpolate frames and reduce noise in images and videos. the application supports GPU acceleration (including multi-GPU setups) and offers batch processing for large workloads. It includes drag-and-drop handling for single or multiple files, optional pre-resize functions, and an automatic tiling system...

TextureAtlas Toolbox is an all-in-one solution for working with texture atlases and sprite sheets. Extract sprites into organized frame collections and GIF/WebP/APNG animations, generate optimized atlases from individual frames, or convert between 15+ atlas formats. Perfect for game developers, modders, and anyone creating showcases of game sprites. Formerly known as TextureAtlas to GIFs and Frames Licensed under AGPL-3.0 Third-party licenses: See...

Encodec is a neural audio codec developed by Meta for high-fidelity, low-bitrate audio compression using end-to-end deep learning. Unlike traditional codecs (like MP3 or Opus), Encodec uses a learned quantizer and decoder to reconstruct complex waveforms with remarkable accuracy at bitrates as low as 1.5 kbps. It employs a convolutional encoder–decoder architecture trained with perceptual loss functions that optimize for human auditory quality rather than raw waveform distance. The model can...