Poisonous Mushroom Detection using YOLOV5

Year 2021, Volume: 16 Issue: 1, 119 - 127, 15.03.2021

Emine Cengil Ahmet Çınar

Abstract

Mantar dünyadaki birçok ülkede yetişen ve tüketilen besin değeri yüksek bir gıdadır. Kolay edinilmesi, insan sağlığına faydalı olması ve lezzeti sebepleriyle tüketim için tercih edilmektedir. Yenilebilir olanları sağlık açısından faydalı olmakla beraber zehirli türleri de bulunmaktadır. Mantarların hangilerinin yenilebilir olduğunu ayırt etmek bu konuda bilgi sahibi olmayan kişiler için zordur. Dolayısıyla bu işlemin otomatik olarak sağlanması faydalı olacaktır. Çalışma, zehirli mantarların tanınmasını sağlayarak yenilmesini önlemeyi amaçlamaktadır. Bu kapsamda, en zehirli 8 mantar türünü içeren bir veri seti oluşturuldu. Oluşturulan veri seti, ön eğitimli YOLOV5 algoritması kullanılarak ince ayar yöntemi ile eğitildi. Yöntemin başarımını göstermek için precision, recall ve mAP kriterleri kullanıldı. İnce ayarlanmış model, sekiz farklı türün tanınmasını 0.77 mean Average Precision olarak sağlamıştır.

Keywords

Object detection, YOLOV5, Poisonous mushroom detection

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