Showing 101-120 of 1,090 projects
The Quick testing framework for Swift and Objective-C, enabling BDD-style testing for iOS apps.
A comprehensive repository for computer vision best practices, code samples, and documentation.
Official implementation of the paper 'Grounding DINO: Marrying DINO with Grounded Pre-Training for Open-Set Object Detection'.
Open-source Markdown editor for macOS with support for Objective-C and Cocoa.
A simple and beautiful chart library for iOS development in Objective-C.
U^2-Net is a deep learning-based salient object detection library for Python that can be used for image processing and background removal.
A conforming Objective-C WebSocket client library for iOS and macOS applications.
Node.js library that provides extra filesystem methods like copy, remove, and mkdirs.
An implementation of the YOLOv9 object detection model, a state-of-the-art computer vision AI.
A fast, modular reference implementation of Instance Segmentation and Object Detection algorithms in PyTorch.
A collection of tutorials and notebooks on state-of-the-art computer vision models and techniques for developers.
MySQL/MariaDB database management tool for macOS developers
Exposed is a Kotlin SQL framework that provides a type-safe, object-oriented way to interact with databases.
A simple and lightweight JSON object mapping library written in Swift.
objection is a runtime mobile exploration tool for Android and iOS that uses the Frida framework for instrumentation.
A PHP library for creating deep copies (clones) of your objects.
A Python library that empowers developers to build applications and systems with self-contained computer vision capabilities.
A macOS app that provides a GUI for the lsof command, showing all open files, directories, sockets, pipes and devices in use by running processes.
A proof-of-concept tool for generating payloads that exploit unsafe Java object deserialization.
A guide to deploying deep-learning inference networks and computer vision primitives with NVIDIA Jetson hardware and TensorRT.
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