In view of the low detection efficiency of waste plastic bottles, limited environment and limited color recognition by current waste sorting algorithms, this paper proposes an effective method for identifying and locating waste plastic bottles, which extracts original pictures based on high-pixel images. , Through the shallow enhancement feature of the YOLOv3 algorithm, the target in the picture is subjected to a series of convolutions to obtain different features, and each detection branch is input for detection, and the feature maps of different scales are processed by the k-means clustering algorithm as anchor boxes, and the position is used Predict to achieve the final recognition and location detection results. Through model testing, the YOLOv3 algorithm is superior to other algorithms in terms of recognition speed and complexity of the algorithm. The average recognition accuracy is 90%, the detection time is within 0.4s, and the positioning accuracy is about ±5cm. It proves the effectiveness and practicability of this algorithm for target detection of waste plastic bottles in complex environments.