用 MiniCPM-V 4.7 搭建开源猫咪喝水监测系统 esp32-eye
OpenBMB 社区拿 MiniCPM-V 4.7 加两块 ESP32 做了猫喝水计数器，1B 模型筛帧、35B 模型认猫，三天 89 次全对，小模型+大模型配合的玩法很值得抄。
@emwstudio 基于 MiniCPM-V 4.7 构建了开源项目 esp32-eye，用两块 ESP32-S3 和一台 MacBook 识别并记录每只猫的喝水行为。系统先用 MiniCPM-V 4.7 1B 在 MacBook 本地过滤有无猫出现的帧，再由 MiniCPM-V 4.7 35B-A3B 对照参考照片确认猫的身份。四只猫的家用环境中，三天内 89 次经人工核对的喝水事件全部识别正确，另有单独的 ESP32-S3 AMOLED 屏显示实时画面与每日计数。
🐱 Who’s been drinking from the water bowl? MiniCPM-V helps keep track.
Our ambassador @emwstudio built esp32-eye, an open-source monitor that recognizes individual cats and logs their daily drinking events, using MiniCPM-V 4.7, two ESP32-S3 boards, and a MacBook. 💧
From camera feed to daily counts, here’s how it works: 📷 Capture: An ESP32-S3 camera streams video from beside the water bowl to the MacBook. ⚡ Detect: MiniCPM-V 4.7 1B runs locally on the MacBook to check whether a cat is in view, filtering frames before calling the larger model. 🔍 Identify: MiniCPM-V 4.7 35B-A3B checks the scene and compares reference photos to identify the cat. 📊 Track: A separate ESP32-S3 AMOLED display shows live video and each cat’s daily count. The system also saves event clips with audio.
🐾 In a home setup with four cats, @emwstudio reports 89 manually checked drinking events over three days, with all cat identities correctly recognized.
A practical example of complementary models at work: an intelligent model handles frequent detection, while a larger model handles identity confirmation.
We love seeing our community turn MiniCPM’s visual understanding into creative tools for everyday life. What would you build? 💙
🎬 Watch @emwstudio’s demo on Instagram: https://t.co/1OZwOr3RxN
🛠️ Explore @emwstudio’s project: https://t.co/5GASJzefLw
🚀 Build with MiniCPM-V: GitHub: https://t.co/msjm2QlrvX 🤗 Hugging Face: https://t.co/crJ549ztb2
#MiniCPM #OpenBMB #ESP32 #OpenSource
