dromara/wgai
开箱即用的JAVA AI 图片、视频语音识别&OCR平台AI合集包含旦不仅限于(车牌识别、安全帽识别、开门关门、常用类物识别等) 图片和视频识别 可自主 融合了AI图像识别opencv、yolo、ocr、esayAI内核识别;AI智能客服、AI语言模型、 无任何第三方API接口可定制化自主离线化部署并自主化行业化使用 避免占用内存、GPU消耗训练与识别分开使用;
What it solves
WGAI provides an all-in-one management platform for multimodal AI capabilities, enabling users to deploy industrial-grade AI services—such as computer vision, speech recognition, and robotics navigation—without needing to build separate infrastructures for each modality.
How it works
The platform integrates multiple AI kernels including OpenCV, YOLO, OCR, and ChatGPT. It uses an architecture that separates training from recognition to prevent excessive memory and GPU consumption, allowing for efficient offline deployment. It supports a full-stack server setup that handles everything from online data labeling and model training to real-time video analysis and AGV (Automated Guided Vehicle) navigation.
Who it’s for
It is designed for industrial users and developers who need a centralized, offline-capable platform to manage multimodal AI tasks like face recognition, license plate detection, and autonomous robot navigation.
Highlights
- Multimodal Integration: Combines vision (YOLO, OpenCV), text/speech (OCR, speech recognition), and robotics (AGV navigation).
- Robot Intelligence: Includes features for map scanning, path planning, and automatic obstacle avoidance.
- End-to-End Workflow: Provides built-in tools for online data labeling, model training, and real-time result evaluation.
- Industrial Deployment: Supports fully offline deployment to ensure data privacy and resource efficiency.
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