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Silero VAD is a voice activity detection model and deep learning speech classifier designed to distinguish human speech from silence across diverse languages and noisy environments. It functions as a pre-trained neural network capable of identifying speech segments within both static audio recordings and real-time data streams. The project includes a language identification tool for classifying spoken languages and a framework for fine-tuning audio models. It provides utilities for optimizing detection thresholds using validation datasets and retraining the model with custom labeled audio to
bootstrap-fileinput is a Bootstrap-compatible HTML5 file upload widget and plugin. It provides a customizable interface for selecting and uploading multiple files, featuring integrated image previews, drag-and-drop support, and client-side validation for file types, sizes, and counts. The project includes a resumable file upload client that slices large files into chunks to ensure stability over intermittent connections and allow transfers to be paused and resumed. It also features a client-side image processor capable of resizing images and reading EXIF metadata to automatically correct imag
Sglang is a high-performance inference engine and serving system designed for large language and multimodal models. It provides a programmable interface for orchestrating complex generation workflows, enabling developers to coordinate multi-turn dialogues, tool invocations, and reasoning chains through a domain-specific language. The platform is built to support production-scale deployments, offering an OpenAI-compatible API that allows for integration with existing application ecosystems. The system distinguishes itself through a disaggregated architecture that separates compute-intensive pr
Tika is a content analysis toolkit and Java library designed for detecting and extracting metadata and text from thousands of different file types. It functions as a universal document text extractor and metadata extraction engine, converting complex files into plain text or XHTML. The system employs a specialized MIME type detector that identifies document formats using magic bytes and metadata to determine the correct parser. It serves as an OCR integration gateway, connecting to external text recognition tools to extract content from image files. The project covers a broad range of extrac
Magika is an AI content type classifier and MIME type prediction engine that uses deep learning to identify file formats based on binary data. It analyzes byte sequences through a neural network to predict the content type of a file and provide associated confidence scores.
The main features of google/magika are: Content Type Detection, Deep Learning Classifiers, File Type Validators, MIME Type Predictors, Prediction Thresholds, Byte-Sequence Tensors, Quantized Inference Runtimes, Sensitivity Tuning.
Projects with overlapping indexed features include: snakers4/silero-vad — Silero VAD is a voice activity detection model and deep learning speech classifier designed to distinguish human… kartik-v/bootstrap-fileinput — bootstrap-fileinput is a Bootstrap-compatible HTML5 file upload widget and plugin. It provides a customizable… sgl-project/sglang — Sglang is a high-performance inference engine and serving system designed for large language and multimodal models. It… richqaq/pastemd — PasteMD is a clipboard-based document processor and productivity tool designed to convert Markdown or HTML content… pymupdf/pymupdf — PyMuPDF is a comprehensive PDF manipulation library and document analysis tool. It serves as a text extraction tool,… apache/tika — Tika is a content analysis toolkit and Java library designed for detecting and extracting metadata and text from…