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Source channel @githubtrending · Post #15271 · Nov 5

#cplusplus#arm#baidu#deep_learning#embedded#fpga#mali#mdl#mobile#mobile_deep_learning#neural_network Paddle Lite is a lightweight, high-performance deep learning inference framework designed to run AI models efficiently on mobile, embedded, and edge devices. It supports multiple platforms like Android, iOS, Linux, Windows, and macOS, and languages including C++, Java, and Python. You can easily convert models from other frameworks to PaddlePaddle format, optimize them for faster and smaller deployment, and run them with ready-made examples. This helps you deploy AI applications quickly on various devices with low memory use and fast speed, making it ideal for real-time, resource-limited environments. It also supports many hardware accelerators for better performance. https://github.com/PaddlePaddle/Paddle-Lite

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Libreware

@libreware · Post #894 · 02/04/2021, 06:15 PM

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PCAPdroid Capture traffic on Android devices and send the PCAP via UDP without root PCAPdroid lets you capture the Android traffic and analyze it remotely (e.g. via Wireshark). The traffic can be easily captured on a remote PC via an UDP socket. 💡 Features: ✅ Capture apps traffic without root privileges ✅ Send captured traffic via UDP ✅ Download the traffic PCAP via the integrated HTTP server ✅ Show captured traffic real time statistics ✅ Apply a filter to only capture traffic for the selected app ✅ Decrypt HTTPS/TLS traffic via a remote mitmproxy https://f-droid.org/packages/com.emanuelef.remote_capture/ #PCAPdroid#android#fdroid#app

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