title: Ð¡ÐµÐ³Ð¼ÐµÐ½ÑÐ¸ÑÐ¾Ð²Ð°Ð½Ð¸Ðµ Ð¿Ð¾ÑÐµÑÐ¸ÑÐµÐ»ÐµÐ¹ Ð¼Ð°Ð³Ð°Ð·Ð¸Ð½Ð° Ð¿Ð¾ Ð²Ð¸Ð´ÐµÐ¾Ð¸Ð·Ð¾Ð±ÑÐ°Ð¶ÐµÐ½Ð¸Ñ
title: Ð²ÑÐ¿ÑÑÐºÐ½Ð°Ñ ÐºÐ²Ð°Ð»Ð¸ÑÐ¸ÐºÐ°ÑÐ¸Ð¾Ð½Ð½Ð°Ñ ÑÐ°Ð±Ð¾ÑÐ° Ð±Ð°ÐºÐ°Ð»Ð°Ð²ÑÐ°
titleType: Subtitle
title: Segmentation of store visitors by video image
Creators: name: ÐÐµÐ±ÐµÐ´ÐµÐ², ÐÐ²Ð°Ð½
Publisher: name: Ð¡Ð°Ð½ÐºÑ-ÐÐµÑÐµÑÐ±ÑÑÐ³ÑÐºÐ¸Ð¹ Ð¿Ð¾Ð»Ð¸ÑÐµÑÐ½Ð¸ÑÐµÑÐºÐ¸Ð¹ ÑÐ½Ð¸Ð²ÐµÑÑÐ¸ÑÐµÑ ÐÐµÑÑÐ° ÐÐµÐ»Ð¸ÐºÐ¾Ð³Ð¾
Year: 2023
Subjects: ÑÐ²ÑÑÑÐ¾ÑÐ½ÑÐµ Ð½ÐµÐ¹ÑÐ¾Ð½Ð½ÑÐµ ÑÐµÑÐ¸
ÑÑÐ°Ð½ÑÑÐ¾ÑÐ¼ÐµÑÑ
ÐºÐ»Ð°ÑÑÐ¸ÑÐ¸ÐºÐ°ÑÐ¸Ñ
Ð²ÐµÐºÑÐ¾ÑÐ¸Ð·Ð°ÑÐ¸Ñ
Ð¾Ð±Ð½Ð°ÑÑÐ¶ÐµÐ½Ð¸Ðµ Ð¾Ð±ÑÐµÐºÑÐ¾Ð²
Python
PyTorch
convolutional neural networks
transform
classification
vectorization
object detection

description: Ð¢ÐµÐ¼Ð° Ð²ÑÐ¿ÑÑÐºÐ½Ð¾Ð¹ ÐºÐ²Ð°Ð»Ð¸ÑÐ¸ÐºÐ°ÑÐ¸Ð¾Ð½Ð½Ð¾Ð¹ ÑÐ°Ð±Ð¾ÑÑ: Â«Ð¡ÐµÐ³Ð¼ÐµÐ½ÑÐ¸ÑÐ¾Ð²Ð°Ð½Ð¸Ðµ Ð¿Ð¾ÑÐµÑÐ¸ÑÐµÐ»ÐµÐ¹ Ð¼Ð°Ð³Ð°Ð·Ð¸Ð½Ð° Ð¿Ð¾ Ð²Ð¸Ð´ÐµÐ¾Ð¸Ð·Ð¾Ð±ÑÐ°Ð¶ÐµÐ½Ð¸ÑÂ». ÐÐ°Ð½Ð½Ð°Ñ ÑÐ°Ð±Ð¾ÑÐ° Ð¿Ð¾ÑÐ²ÑÑÐµÐ½Ð° Ð¸ÑÑÐ»ÐµÐ´Ð¾Ð²Ð°Ð½Ð¸Ñ Ð¸ Ð¿ÑÐ¸Ð¼ÐµÐ½ÐµÐ½Ð¸Ñ ÑÐ°Ð·Ð»Ð¸ÑÐ½ÑÑ Ð½ÐµÐ¹ÑÐ¾Ð½Ð½ÑÑ ÑÐµÑÐµÐ¹ Ð´Ð»Ñ ÑÐµÐ°Ð»Ð¸Ð·Ð°ÑÐ¸Ð¸ Ð°Ð»Ð³Ð¾ÑÐ¸ÑÐ¼Ð° ÑÐµÐ³Ð¼ÐµÐ½ÑÐ¸ÑÐ¾Ð²Ð°Ð½Ð¸Ñ Ð»ÑÐ´ÐµÐ¹. Ð ÑÐ¾Ð´Ðµ Ð¸ÑÑÐ»ÐµÐ´Ð¾Ð²Ð°Ð½Ð¸Ñ Ð±ÑÐ»Ð¾ Ð¿ÑÐ¾Ð¸Ð·Ð²ÐµÐ´ÐµÐ½Ð¾ ÑÑÐ°Ð²Ð½ÐµÐ½Ð¸Ðµ Ð¸ Ð°Ð½Ð°Ð»Ð¸Ð· ÑÐ°Ð·Ð»Ð¸ÑÐ½ÑÑ Ð¼Ð¾Ð´ÐµÐ»ÐµÐ¹ Ð½ÐµÐ¹ÑÐ¾Ð½Ð½ÑÑ ÑÐµÑÐµÐ¹, Ð¸Ð·ÑÑÐµÐ½Ð° Ð°ÑÑÐ¸ÑÐµÐºÑÑÑÐ° Ð¸ Ð¿ÑÐ¸Ð½ÑÐ¸Ð¿Ñ ÑÐ°Ð±Ð¾ÑÑ. Ð ÑÐ¾Ð´Ðµ ÑÐ°Ð±Ð¾ÑÑ Ñ Ð¿ÑÐ¸Ð¼ÐµÐ½ÐµÐ½Ð¸ÐµÐ¼ ÑÐ·ÑÐºÐ° Ð¿ÑÐ¾Ð³ÑÐ°Ð¼Ð¼Ð¸ÑÐ¾Ð²Ð°Ð½Ð¸Ñ Python Ð¸ Ð±Ð¸Ð±Ð»Ð¸Ð¾ÑÐµÐºÐ¸ Pytorch Ð±ÑÐ»Ð° ÑÐµÐ°Ð»Ð¸Ð·Ð¾Ð²Ð°Ð½Ð° Ð¿ÑÐ¾Ð³ÑÐ°Ð¼Ð¼Ð°, ÑÐ¿Ð¾ÑÐ¾Ð±Ð½Ð°Ñ Ð¾ÑÐ½Ð¾ÑÐ¸ÑÑ Ð»ÑÐ´ÐµÐ¹ Ðº ÑÐ°Ð·Ð»Ð¸ÑÐ½ÑÐ¼ Ð¾ÑÐ´ÐµÐ»Ð°Ð¼ Ð¼Ð°Ð³Ð°Ð·Ð¸Ð½Ð°. ÐÑÐ¾Ð³ÑÐ°Ð¼Ð¼Ð° ÑÐ¾Ð´ÐµÑÐ¶Ð¸Ñ Ð² ÑÐµÐ±Ðµ ÑÑÐ¸ ÑÐ¸Ð¿Ð° Ð½ÐµÐ¹ÑÐ¾Ð½Ð½ÑÑ ÑÐµÑÐµÐ¹: Ð¡Ð²ÑÑÑÐ¾ÑÐ½ÑÑ Ð½ÐµÐ¹ÑÐ¾Ð½Ð½ÑÑ ÑÐµÑÑ, Ð¢ÑÐ°Ð½ÑÑÐ¾ÑÐ¼ÐµÑ, ÐÐ¾Ð»Ð½Ð¾ÑÐ²ÑÐ·Ð½ÑÑ ÐÐµÐ¹ÑÐ¾Ð½Ð½ÑÑ ÑÐµÑÑ. ÐÐ»Ñ Ð´ÐµÐ¼Ð¾Ð½ÑÑÑÐ°ÑÐ¸Ð¸ ÑÐ°Ð±Ð¾ÑÑ Ð°Ð»Ð³Ð¾ÑÐ¸ÑÐ¼Ð° Ð¸ ÑÑÐ°Ð²Ð½ÐµÐ½Ð¸Ñ ÐºÐ¾Ð½ÑÐ¸Ð³ÑÑÐ°ÑÐ¸Ð¹ Ð±ÑÐ»Ð¸ ÑÐ¾Ð·Ð´Ð°Ð½Ñ ÑÐ°Ð·Ð»Ð¸ÑÐ½ÑÐµ ÑÐµÑÑÑ. ÐÐ° Ð¾ÑÐ½Ð¾Ð²Ðµ ÑÐµÑÑÐ¸ÑÐ¾Ð²Ð°Ð½Ð¸Ñ Ð±ÑÐ»Ð¸ ÑÐ´ÐµÐ»Ð°Ð½Ñ Ð²ÑÐ²Ð¾Ð´Ñ Ð¾Ð± ÑÑÑÐµÐºÑÐ¸Ð²Ð½Ð¾ÑÑÐ¸ ÐºÐ°Ð¶Ð´Ð¾Ð¹ ÑÐ°ÑÑÐ¸ Ð°Ð»Ð³Ð¾ÑÐ¸ÑÐ¼Ð° Ð¸ Ð²ÑÐ±ÑÐ°Ð½Ð° Ð¾Ð¿ÑÐ¸Ð¼Ð°Ð»ÑÐ½Ð°Ñ ÐºÐ¾Ð½ÑÐ¸Ð³ÑÑÐ°ÑÐ¸Ñ.
description: The theme of the final qualification work: "Segmentation of store visitors by video image." This work is devoted to the study and application of various neural networks for the implementation of the algorithm for segmenting people. During the study, a comparison and analysis of various models of neural networks, a study of the architecture and justification of the work were made. In the course of work, using the Python programming language and the Pytorch library, a program was implemented that can move from people to existing departments of the store. The program contains three types of neural networks: Convolutional Neural Network, Transformer, Fully Connected Neural Network. Various tests were identified to monitor the performance of the algorithm and compare configurations. Based on testing, the results of the analysis of each part of the algorithm were obtained and the optimal configuration was chosen.