An Adafruit GFX Compatible Library for the ESP32/S2/S3/P4 to drive HUB75 LED matrix panels using DMA for high refresh rates. Supports panel chaining.
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Updated
Oct 17, 2026 - C++
An Adafruit GFX Compatible Library for the ESP32/S2/S3/P4 to drive HUB75 LED matrix panels using DMA for high refresh rates. Supports panel chaining.
Tessera: beautiful, easy touch screens for Home Assistant on affordable ESP32 panels, 2.8 to 10.1 inch (CYD, Guition, Waveshare). Drag-and-drop editor, no YAML, no MQTT.
Espressif 32: pioarduino community platform compatible with PlatformIO
🛰️ ESP32 Based GPS Navigator with OSM offline maps. Multi GNSS
Portable touchscreen SDR for M5Stack Tab5 + RTL-SDR dongles — spectrum, waterfall, FM/AM, Shortwave, ADS-B, FT8, P25, LoRa, RF tools, and Wi-Fi analysis without a PC.
Touch dashboards for Home Assistant on ESP32-P4 and ESP32-S3 displays. Lights, climate, sensors, energy, weather and more, set up in your browser.
Handheld T Display P4 & ESP32-P4 SDR scanners - RTL-SDR or LR2021 SDR, P25 Phase 1, FM/AM, ADS-B and POCSAG, plus onboard LoRa/MeshCore, GPS and Flipper .sub capture. No PC.
Waveshare-ESP32-P4-86-Panel-ETH-2RO firmware
Pixel art player built on ESP32-P4
Touchscreen Sonos controller for ESP32-P4 — album art, synced lyrics, multi-room, weather and a StandBy clock. Flash it from your browser.
ESP32-P4 dynamic RISC-V compiler - faster iteration (1-2s vs 30-60s firmware rebuild) | Native performance, zero interpreter overhead | NumPy integration with automatic type conversion & memory management | Multi-file LTO compilation | Call firmware functions (printf, malloc, FreeRTOS) | Type-safe, memory-safe | Ideal for DSP, ML, and audio
Source Code of team Mach Mind - https://swarmdronechallenge.digital/
ESP32-P4 Digital Sticky Notes App
World's First NMS-Free YOLOv26n on ESP32-P4. Features end-to-end Int8 QAT and custom C++ optimizations achieving 30% faster inference than the official ESP-DL YOLOv11n (1.7s vs 2.4s).
Optimized ESP32-S3/P4 fully offline speech to text and text to speech system for Micropython and AtomVM, featuring a finetuned STT model for noisy environments, plus a data generation/field capture/model finetuning framework. Includes high performance 4/8bit int kernels for Xtensa/RiscV PIE vector units
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