Search Results for "image processing netbeans project"

libwebp is the reference codec library for Google’s WebP image format, providing both encoding and decoding along with command-line tools. It supplies cwebp to compress images into WebP and dwebp to decompress them back, making it easy to test quality/size trade-offs across presets and tuning parameters. The GitHub repository is a mirror; the canonical source of truth lives on Chromium’s git, and developer docs are hosted on WebP’s portal. The project underpins WebP support across browsers,...

...Users can increase frame rates by two or four times through Python inference scripts. Configurable scaling options help process high-resolution footage while managing GPU memory requirements. Additional scripts support image sequence processing, comparison previews, and experimental video enhancement using SAFA. Lightweight model variants reduce computational demands. It is primarily intended for developers and engineers integrating frame interpolation into video processing workflows.

flutter_rust_bridge is a toolchain that generates ergonomic bindings between Rust and Dart/Flutter so you can write performance-critical logic in Rust while building UI in Flutter. It abstracts away the low-level FFI details, letting developers define Rust functions and data structures that are safely callable from Dart. The project supports passing complex types, handling async operations and streams, and integrating with Flutter across mobile and desktop targets. By leaning on Rust’s memory safety and zero-cost abstractions, it enables compute-heavy tasks—parsing, crypto, image/audio processing, and more—without sacrificing Flutter’s developer experience. ...

...The repository is built around training, prediction, and mIoU evaluation for VOC-style segmentation data and medical-style datasets. It includes scripts for general training, medical dataset training, prediction, annotation handling, model summaries, and evaluation. The project supports multiple backbones, data processing utilities, extensive comments, and adjustable training parameters. Its README notes that U-Net is better suited to datasets with fewer features and shallow visual structures, such as medical image segmentation, rather than complex VOC-style scenes. It is useful for developers and students who want a clear U-Net implementation for segmentation experiments, custom masks, and biomedical-style image analysis.

...Multiprocessing can use several CPU cores during processing. The project is intended for copyright marking, traceability, and image steganography experiments.

iText is an open-source PDF library available for Java and .NET (C#). iText allows you to effortlessly generate and manipulate standards-compliant PDF documents with a powerful and feature-rich SDK. With iText, you can create archivable and accessible PDFs, split and merge documents, fill and flatten forms, digitally sign documents, and more. iText add-ons enable additional functionality, such as PDF creation from HTML templates, secure redaction, OCR, and much more. The latest...

The fast-neural-style project is an implementation of neural style transfer techniques optimized for real-time image processing. It uses convolutional neural networks to apply artistic styles to images, enabling users to transform photos into stylized outputs inspired by famous artworks. Unlike earlier approaches that required expensive optimization per image, this project leverages feed-forward networks to achieve fast inference, making style transfer practical for real-world applications. ...