prairiewolf11,github

minigpt-4

MiniGPT-4: Enhancing Vision-language Understanding with Advanced Large Language Models

mlx90641

Adaptation of official Melexis MLX90641 library for Raspberry Pi

mockingbird

🚀AI拟声: 5秒内克隆您的声音并生成任意语音内容 Clone a voice in 5 seconds to generate arbitrary speech in real-time

openpose

OpenPose: Real-time multi-person keypoint detection library for body, face, hands, and foot estimation

paddlegan

PaddlePaddle GAN library, including lots of interesting applications like First-Order motion transfer, Wav2Lip, picture repair, image editing, photo2cartoon, image style transfer, GPEN, and so on.

paddlehub

Awesome pre-trained models toolkit based on PaddlePaddle. (400+ models including Image, Text, Audio, Video and Cross-Modal with Easy Inference & Serving)

Easy-to-use Speech Toolkit including Self-Supervised Learning model, SOTA/Streaming ASR with punctuation, Streaming TTS with text frontend, Speaker Verification System, End-to-End Speech Translation and Keyword Spotting. Won NAACL2022 Best Demo Award.

physo

Physical Symbolic Optimization

python_speech_features

This library provides common speech features for ASR including MFCCs and filterbank energies.

python_st7789

Python library for using ST7789-based IPS LCD with Raspberry Pi (240x240 pixels, SPI interface, 7 pins without CS pin)

pythonwin7

Python 3.9 to 3.11 installers that support Windows 7 and Windows Server 2008 R2

quasar

Remote Administration Tool for Windows

quivr

Dump all your files and thoughts into your GenerativeAI Second Brain and chat with it

raspberrypi-kdxf

科大讯飞在线语音听写（流式版）树莓派版本SDK

raspi-python-st7735

Python library for using ST7735-based TFT LCDs with a Raspberry Pi

rat-hodin-v2.9

Remote Administration Tool for Linux

real-esrgan

Real-ESRGAN aims at developing Practical Algorithms for General Image/Video Restoration.

scrcpy

Display and control your Android device

smp_lpr

利用树莓派实现车牌识别，其中借鉴了大神的代码，调用摄像头，实现了车牌识别，设计一款基于树莓派实现车牌识别的智能限高杆。系统可以分为辨识部分和警示部分，辨识部分以树莓派3B+为核心处理器，基于Linux平台，利用激光对准模块来判断车辆是否超出限定高度，若超过则辅以摄像头来作为抓取车辆信息。通过python3.5和OpenCV来对含有车牌信息的图片，进行高斯去噪、灰度化、边缘检测、二值化、闭操作、字符分割、字符识别匹配等一系列图像处理操作最终实现车牌识别这个系统，最后通过串口将车牌信息发送给警示部分，考虑到要提高数据传输之间的可靠性，本系统自定义了串口之间传输的协议帧组。警示部分主要以STC12C5A32S2为处理核心，辅以点阵屏做为警示。单片机在接收到辨识部分发过来的车牌信息之后，将车牌信息显示在点阵屏上面，不断闪烁以警示超高司机注意安全。

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