Abstract
This article presents a Python-oriented solution for automatic classification of plants based on image analysis, applicable in agriculture, ecology and botany. Traditional plant identification methods, which require expert analysis, are often time-consuming and error-prone. The developed application uses convolutional neural networks (CNN) implemented on the basis of TensorFlow to recognize plants by their visual characteristics, which allows you to accurately and quickly classify species. An important role is played by the OpenCV library, which is used for image preprocessing, including resizing, color normalization and noise filtering, which improves classification accuracy. The model achieves an accuracy of 86.97%, which confirms its effectiveness and suitability for practical use. The system is equipped with an intuitive interface, which makes it accessible to users of different levels of training. In the future, it is planned to e