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This project is a cross-platform mobile camera framework and real-time computer vision library. It provides a high-performance interface for mobile applications to handle hardware control, media capture, and live camera frame processing.
The main features of mrousavy/react-native-vision-camera are: Cross-Platform Camera Components, Camera Feed Decoders, Computer Vision Libraries, Real-Time Object Detection, Pixel-Buffer Memory Mapping, Worklet Threading, Mobile Photo and Video Capture, Real-Time Model Inference on Frames.
Projects with overlapping indexed features include: thu-mig/yolov10 — YOLOv10 is a PyTorch computer vision library and real-time vision framework designed for locating and identifying… itseez/opencv — OpenCV is an open-source computer vision library and visual analysis toolkit. It provides a framework for processing… react-native-camera/react-native-camera — This project provides cross-platform programmatic interfaces and UI components for integrating camera hardware into… lyuwenyu/rt-detr — RT-DETR is a real-time object detection model based on the detection transformer architecture. It is implemented as a… alexeyab/darknet — Darknet is a high-performance C-based inference engine and computer vision library designed for real-time object… dm77/barcodescanner — This is an Android barcode scanning library designed to detect and decode barcode data from a live camera feed. It…
YOLOv10 is a PyTorch computer vision library and real-time vision framework designed for locating and identifying multiple objects in images and video streams. It functions as an end-to-end object detector that optimizes for high-speed deployment and detection precision. The project is distinguished by an NMS-free detection architecture that predicts a single bounding box per object, eliminating the need for non-maximum suppression post-processing to reduce inference latency. It further optimizes for edge hardware through scalable weights and a quantization-friendly structure that facilitates
OpenCV is an open-source computer vision library and visual analysis toolkit. It provides a framework for processing static images and dynamic video frames to analyze visual data and extract information using deep learning. The project functions as a real-time image processing framework, enabling the execution of vision algorithms on live video streams for immediate analysis and data processing. The toolkit covers a broad range of capabilities including image pattern recognition, real-time video analysis, and visual data extraction. It also supports automated visual inspection for detecting
This project provides cross-platform programmatic interfaces and UI components for integrating camera hardware into mobile applications. It serves as a tool for implementing image and video capture, as well as specialized scanning and recognition tasks. The library includes specialized capabilities for computer vision, including a barcode scanner for decoding various barcode types, a face detection tool to identify human faces in a live feed, and an optical character recognition engine for extracting written text from the camera stream. The system covers hardware configuration and control, i
This is an Android barcode scanning library designed to detect and decode barcode data from a live camera feed. It provides the core infrastructure for translating visual patterns into text on mobile devices. The library includes a camera preview manager that adjusts aspect ratios and feed sizes to fit various screen dimensions, as well as a hardware controller for managing flash, autofocus, and sensor selection. It also features a barcode format filter to restrict scanning to specific barcode types to increase detection speed and accuracy. The project covers camera hardware control, live ba