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The learning content in the field of machine vision is abstract and difficult to understand, The related experimental teaching products are insufficient, Based on the Python language, the open-source opencv-python image processing library and the TensorFlow machine learning framework are used to construct a machine vision experimental teaching platform. The system covers the classical methods of machine vision, including vector machine, K proximity image classification, neural network, convolutional neural network target recognition, fusion of commonly used functions based on classical methods, and system sub-module design. After testing, the system has good interactivity and scalability, can adapt to the experimental requirements of machine vision, training data, sample test data import flexibility, machine vision parameter optimization, code iteration is convenient, and can compile and generate .exe executable The document assists students in learning the real application scenarios of machine vision technology and improving students' ability to solve problems and innovate.