workbench for learning and practicing on-device AI technology in real scenario with online-TV on Android phone, powered by ggml(llama.cpp,whisper.cpp...) and FFmpeg and opencv-mobile

the original reference implementation of a specified llama.cpp backend for Qualcomm Hexagon NPU on Android phone, history of ggml-hexagon: https://github.com/zhouwg/ggml-hexagon/discussions/18.

On-device CLIP inference on Android with ExecuTorch + Qualcomm QNN backend. Zero-shot image classification and vision-language understanding powered by hardware-accelerated AI on Snapdragon devices.

Catalog of projects that build upon Qualcomm's platforms

Lightweight UAV-SAR perception system for aerial human detection, monocular GPS geolocation, and automated rescue alerting using standard UAV telemetry and edge AI.

QNN LLM binding for React Native

Rust bindings SDK for Qualcomm Genie/QNN on Snapdragon's chip.

Qualcomm lib Genie binding for Node.js

Lightweight underwater pipeline perception using YOLOv8n segmentation, PCA-based geometry extraction, and embedded AI deployment.

Complete guide and scripts for setup, execution and testing the AI models (ONNX) performance on NPU architectures (Qualcomm QNN & Intel OpenVINO) on Windows.