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GithubOpenMVShieldsLensRoboticsBookVideoDownloadDocsForumOpenMV.ioGithubSingTown AI Vision Technology enables more accurate, stable, and intelligent counting on packaging production lines.
In packaging production lines, traditional infrared or mechanical counting methods are susceptible to interference from light, speed, and object shapes, leading to inaccurate counts or response delays.
To enhance detection accuracy and automation levels, packaging equipment manufacturers have introduced SingTown's OpenMV intelligent camera AI image recognition technology. Utilizing AI machine vision and image recognition algorithms, this system automatically detects and counts packaging bags on the conveyor belt, achieving real-time signal output and coordinated control.
The packaging counting system utilizes SingTown Technology's OpenMV intelligent camera AI image recognition technology to monitor the quantity of packaging bags in real-time on the operating conveyor belt.
Ang camera ay naka-install nang 1.5–2 metro ang layo mula sa conveyor belt upang kumuha ng mga larawan at magsagawa ng edge AI recognition para sa mga packaging bag na may sukat na humigit-kumulang 70cm × 40cm. Ginagamit ng sistema ang mga computer vision algorithm (edge detection + motion recognition + target tracking) upang matukoy ang kalagayan ng pagpasok at paglabas ng packaging. Kapag nakita ang isang kumpletong package na dumadaan sa recognition area, awtomatiko itong maglalabas ng counting signal.
The OpenMV intelligent camera enables flexible edge deployment, featuring edge computing capabilities and multiple I/O control interfaces. It can directly send pulse signals to PLCs, microcontrollers, or host computers via GPIO or serial ports, achieving production synchronization and output statistics.
The system response time is below 20 milliseconds, ensuring stable adaptation to varying conveying speeds and lighting conditions.
Through SingTown Technology's OpenMV intelligent camera image recognition solution, packaging production lines have been upgraded from manual or photoelectric counting to AI visual counting, significantly enhancing detection accuracy, stability, and production efficiency.
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