Research on Apple Target Recognition and Counting Method Based on Yolov5.
DOI:
https://doi.org/10.54097/b9hpck27Keywords:
YOLOv5, Apple Recognition, Object detection, image processing, Deep Learning.Abstract
In this study, a YOLOv5 target recognition model was established to extract apple feature information and predict the number and location of apples in 200 pictures. First, the model is trained using the training data set, and the validation data set is validated to obtain the best model weight and parameter information. Secondly, this paper specifies that the training times are 50 times, the batch size of one read is 16 times, and the training is carried out through data enhancement operations to enrich the training data set. Finally, the weight and parameter information with the highest average verification accuracy and recall rate were selected for the 20th time to predict 200 pictures, and then the number of apples in each picture was counted.
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