Object counting and mass estimation of floating plastic litters using YOLO and DeepSort
2023 Volume 4 Issue 3 Pages 932-941
Details
2023 Volume 4 Issue 3 Pages 932-941
In this study, we estimated the type, the number, the areas, the weights of floating plastic litters in the images by using YOLO and DeepSort. The images of floating plastic litters were taken in an open channel by using visible and infrared cameras. The areas of them are estimated by using the Bounding Boxes by YOLO considering the litter’s rotation. The weights of them are estimated by the relationship between the areas of the plastic products and the weights of that. As a result, the accuracy of type detection was 0.83, F-measure was about 0.8 for number counting by DeepSort model and R2 (coefficient of determination) was about 0.8 for the area estimation. For the weight estimation of each plastic types, the accuracy was lower compared to the estimation of the areas. However, the MAPEm errors in the total weight of bottles and the packages were small (10 ~ 30 %). Therefore, we conclude that this proposed method is applicable for estimating the weights of floating bottles and packages, in the conditions of the experiment.
