This repository features a generative AI image generator designed to run on the RP2350 microcontroller (Raspberry Pi Pico 2). The model uses a latent flow diffusion transformer (DiT) architecture, similar to Flux, but scaled down significantly with only 1.7 or 2.9 million parameters—thousands of times smaller than typical local diffusion models. It can generate $128 times 128$ RGB images of human faces in approximately 5-20 seconds and supports conditional generation for five classes based on gender, smile, and neutral expressions.
- The model architecture includes a VAE decoder and a DiT component.
- Hardware output can be displayed via a VGA monitor or streamed over USB.
- Includes an int8 pipeline involving calibration, distillation-QAT (Quantization-Aware Training), and folding.
- Two variants are provided: a high-quality flagship model and a faster build version.
- The model architecture includes a VAE decoder and a DiT component.
- Hardware output can be displayed via a VGA monitor or streamed over USB.
- Includes an int8 pipeline involving calibration, distillation-QAT (Quantization-Aware Training), and folding.
- Two variants are provided: a high-quality flagship model and a faster build version.
The author explores the potential of running an AI agent framework on low-cost hardware by testing MimiClaw, an OpenClaw-inspired assistant, on an ESP32-S3 microcontroller. Unlike traditional AI setups, MimiClaw operates without Node.js or Linux, requiring the user to flash custom firmware using the ESP-IDF framework. The setup integrates with Telegram for interaction and utilizes Anthropic and Tavily APIs for intelligence and web searching. Despite the technical hurdles of installation and potential API costs, the project successfully demonstrates a functional, sandboxed, and low-power personal assistant capable of persistent memory and routine tracking.
Discussion thread about using a Seeed Studio reTerminal E1002 color ePaper display as a Home Assistant dashboard.
Aircraft radar display with retro styling. Visualises real-time aircraft positions and metadata from a local tar1090 server, with a retro interface.
>/u/Quantum-Stability writes: I got this working with just a free public api! Here is the base_url that you can use for TAR1090_URL in the config.ini file. No other set up is needed <https://opendata.adsb.fi/api/v2/lat/{your_latitude}/lon/{your_longitude}/dist/{your_distance}>
>/u/Quantum-Stability writes: I got this working with just a free public api! Here is the base_url that you can use for TAR1090_URL in the config.ini file. No other set up is needed <https://opendata.adsb.fi/api/v2/lat/{your_latitude}/lon/{your_longitude}/dist/{your_distance}>
The Explorer HAT is a fantastic way to get started with physical computing and add-on boards for your Raspberry Pi. It provides a standardised way to connect a wide range of components, making it easy to build interactive projects.
A Raspberry Pi project that displays the city and country where it is currently 5:00 p.m., updating every 15 minutes. It uses accurate timezone data and is a fun, lightweight build with potential for educational and practical applications.
Something similar to the Spotify Car Thing, built with a cheap ESP32 Screen. Connects to your Spotify account and displays your currently playing song with its album art.
Firmware and software to run an ESP32-CAM module on your Flipper Zero device. Allows capturing images and streaming live video to the Flipper Zero.
A curated list of resources for the M5Stack Cardputer, a $30 credit-card sized mini computer based on the ESP32-S3. Includes specs, pre-installed apps, community apps, and resources.
The M5Stack Cardputer v1.1 is a high-performance card computer featuring a StampS3A microcontroller, 56-key keyboard, 1.14-inch TFT screen, and various interfaces for expansion and control. It's ideal for rapid prototyping, industrial control, and IoT projects.
