RT-DETR is a real-time object detection model based on the detection transformer architecture. It is implemented as a computer vision model for both the PyTorch and PaddlePaddle deep learning platforms, designed to identify and locate multiple objects in images and video streams. The model eliminates the need for anchor generation and non-maximum suppression by utilizing a transformer-based approach. It focuses on high-performance detection, balancing precision and low latency for live environment deployment. The system employs a hybrid encoder and multi-scale feature fusion to extract globa
A collection of reference implementations and code samples for integrating Android camera hardware and software APIs. The project provides demonstrations for using both the Jetpack CameraX library and the low-level Camera2 API to implement photo and video capture features. The repository includes specialized implementations for high-performance recording, such as high-frame-rate slow motion and high-dynamic-range video. It also features examples of machine learning vision, demonstrating how to analyze live camera frames for object detection and QR code scanning. The project covers broad imag
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 framework includes a dedicated system for running AI models and custom analysis on live camera streams using high-performance worklets. It also functions as a real-time detection and decoding system for QR codes and barcodes. Broad capabilities cover the capture of high-resolution photos and videos with controls for zoom, HDR, and frame rates. The projec