"实时图像识别：基于Apache Spark的未来计算"

In the presented document "Real-Time Image Recognition with Apache Spark" by Nikita Shamgunov, CTO of MemSQL, the future of computing is highlighted as being visual and numerical. The document emphasizes the use of Apache Spark and TensorFlow in training models for image recognition, as well as the extraction of feature vectors from images. The real-time image recognition workflow is detailed, including the training of models with Spark and TensorFlow, the use of the model to extract feature vectors from images, and the storage of feature vectors in a MemSQL table. The document specifically mentions the implementation of apple image recognition and how image recognition can be put to work in practical applications today. The process of training the model with Spark and TensorFlow is explained in detail, along with the technique for extracting feature vectors from images using the model. The document emphasizes the importance of storing feature vectors in a MemSQL table for efficient retrieval and analysis. Overall, the document provides a comprehensive overview of the real-time image recognition process, highlighting the role of Apache Spark, TensorFlow, and MemSQL in implementing this technology. It serves as a valuable resource for anyone interested in understanding the technical aspects of real-time image recognition and its practical applications.