YOLOv7-Based Microplastic Detection: Crafting a Custom Dataset for Environmental Analysis

As the increase in plastic pollution rises, we face a significant setback of microplastics removal. The larger plastics are easily discarded but their smaller counterparts are indiscernible to the naked eye and in most cases take years to reduce. The presence of microplastics then creates innumerable health and environmental problems. To address this, we have used object detection models to detect and count microplastics using a novel dataset. The paper uses 3 versions of You Only Look Once model (YOLO) for the detection and counting of microplastics. Among them, YOLOv8 performed the best with 81.4%, followed by YOLOv7 with 80.73% and YOLOv9 with 77.2%. However, YOLOv7 performs best with test data and real-time detection.