In order to achieve fast and accurate image retrieval for large-scale clothing image sets and break through the limitations of current conventional retrieval methods, this study proposes a new deep learning model:Fashion-16 clothing image retrieval model. Based on the idea of first classification and intra-class retrieval, based on the powerful image feature extraction ability of VGG-16 model, the convolutional neural network Softmax classifier is used for classification, and the nearest neighbor search is performed for the idea of locally sensitive hashing under the same category. An image retrieval model correction for clothing category attributes is implemented. The experimental results show that the model has good stability, accuracy, and retrieval speed, and has practical value and research significance.