Garbage Classification and Recognition Model based on YOLOv5 - Zhao, Hongxuan; Hu, Xudong (Journal of Theory and Practice in Engineering and Technology, 2024)
In response to the garbage classification implemented by the state and to assist citizens in effectively sorting and discarding garbage, we studied the image-based garbage detection and classification model to realize the recognition and detection of garbage. The garbage classification model based on YOLOv5s is trained on the GPU server. Then the trained model is deployed to the server, and the user of wechat applet takes photos and uploads photos to the server. The server processes the images through the model and returns the processed images to the wechat applet. Users can determine the category of garbage through photos, so as to classify the garbage. Finally, the trained model can identify 44 types of garbage, and has good performance in recognition accuracy and response speed.