Pengklasifikasian Warna dan Bentuk Produk Menggunakan Kamera ELP- USB8MP02G-MFV dengan Berbasis YOLOV7
DOI:
https://doi.org/10.30871/ji.v17i1.9266Keywords:
Raspberry Pi 4b, ELP-USB8MP02G-MFV, object detection, YOLOv7Abstract
The development of artificial intelligence technology allows the system to detect various objects. In the research on the classification of color and shape of products using the ELP-USB8MP02G-MFV camera based on YOLOV7, it aims to modify the conveyor on the molding machine. Because the conveyor only has the function of distributing goods from the molding machine to the bin and the length of time used to wait for the bin to be full is the reason why this conveyor is modified. Modifications are made by adding a camera that has been connected to the Raspberry Pi 4B on the conveyor, the camera functions to take pictures of passing product objects then the image is detected by the system on the Raspberry Pi 4B so that this conveyor machine can classify the objects produced by the molding machine. The system detects objects using the YOLOv7 algorithm. This study was carried out with three tests, namely object model detection testing, color detection testing and program and relay output testing where 98.11% was for object model detection testing, 97.37% for color detection and 100% for program and relay output testing. The results of this research will contribute to the development of object detection, especially product object detection and the results of molding machines.
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References
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