OpenBMB@OpenBMB · X面壁智能 MiniCPM-V 4.6 演示工业仪表读取，模型需同时理解指针角度、刻度范围、单位、数字显示、液位比例等视觉信号，输出结构化 JSON（pressure_bar, temp_c, flow_lpm, level_pct）。测试使用合成控制面板，评分标准为 pass（满量程5%内）、drift（10%内）、miss。数字显示和液位较易，模拟指针更困难。该方案通过摄像头+视觉模型低成本改造传统仪表，无需更换硬件，在工厂、数据中心等场景有巨大应用潜力。
Really impressive "gauge reader" demo by @aijoey MiniCPM-V 4.6 👀
What makes this interesting is that it goes far beyond OCR： The model needs to understand multiple visual signals at once， including pointer angles， scale ranges， units， value mapping， digital displays， and liquid level proportions， often within the same scene.💥
This demonstrates strong visual reasoning ability， not just text reading 🧠 Even more importantly， the real-world setup matters here. Many factories， data centers， labs， and energy systems still rely on traditional gauges and legacy panels.👍In the industrial automation field， this will have huge application scenarios. Relying on MiniCPM-V 4.6's structured output and powerful multimodal capabilities， many traditional instruments without sensors can be retrofitted at low cost using this solution.