Showing 401-420 of 1,012 projects
A collection of pre-trained, state-of-the-art AI models for the ailia SDK, supporting a wide range of computer vision and natural language processing tasks.
Automation scripts for Taobao, JD, and Alipay 11.11 shopping festivals with full rewards and anti-detection measures.
A curated collection of ICCV conference papers, code, and interpretations for computer vision developers.
Advanced web scraping and bot prevention library for building privacy-focused web applications.
Turn any computer or edge device into a command center for your computer vision projects.
An open-source library for deep learning on satellite and aerial imagery using Python and PyTorch.
A subdomain takeover tool for attackers, bug bounty hunters, and security teams to detect and mitigate security vulnerabilities.
A C-based loader that mitigates VMware Hardened VM detection to bypass anti-VM protections.
A Java library for Android that provides computer vision capabilities like object detection, tracking, and face recognition.
An experimental host-based intrusion detection system (HIDS) written in Go.
A high-level machine learning and deep learning library for the PHP language.
A Java library that makes it easy to detect performance bottlenecks in Android apps when they are blocked.
YOLOP is a Python-based autonomous-driving perception project for panopitic driving perception.
This is a collection of Endpoint Detection and Response (EDR) tools for security researchers and developers.
A static analysis tool for securing Go code, focused on code security and vulnerability detection.
A PyTorch implementation of the YOLOv4 object detection algorithm, suitable for training custom models.
A powerful MCP server that provides an all-in-one solution for public web access and data extraction.
A JavaScript library for detecting touch gestures on the modern web without dependencies.
A PyTorch pre-trained model for real-time interest point detection, description, and sparse tracking.
SparseML provides a library for applying sparsification recipes to neural networks with a few lines of code, enabling faster and smaller models.
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