Aimed at the problem of too large model parameters and low sorting precision of the traditional flower classification algorithm in industrial automation sorting application, a flower recognition algorithm based on deep learning was proposed. The application of flower classification algorithm in industrial flower packaging sorting system was introduced. According to the actual demand, a deep separable convolutional neural network was used as the flower feature extraction, and the model structure of the network was analyzed in detail. In order to improve the speed of model training, a fine-tuned model training method was proposed. The experimental results showed that the flower classification algorithm used in the industrial flower automatic sorting application had higher accuracy, better stability and wider application than traditional algorithms.