A method for monitoring poultry quantity in a breeding farm based on depth learning analysis

Abstract

The invention discloses a method for monitoring poultry quantity in a breeding farm based on depth learning analysis. The method comprises the following steps: (1) according to a fixed sampling frequency, converting the monitoring video into a static chart to obtain a training picture data set; (2), marking that picture data set; (3), performing Gaussian convolution on each labeled picture to convert it into a density map, and the actual quantity of poultry in each picture is calculated; (4), dividing the picture data set at a ratio of 8:2 into training set and test set as the input of training model and test model respectively, training depth learning model offline(as shown in Figure 3), selecting the best model for poultry quantity monitoring by comparing the MAE of different parameter models on the test set; (5), real-time decoding the poultry quantity monitoring video obtained in step (4), inputting into the trained model, integrating the density map output by the model, and obtaining the poultry quantity within the monitoring range. The invention realizes the real-time monitoring of the poultry quantity more accurately.

Description

technical field [0001] The invention relates to various fields such as monitoring technology, video coding, deep learning, etc., in particular, a model scheme for analyzing farm monitoring video and monitoring the number of poultry based on deep learning. Background technique [0002] In recent years, a number of new poultry farms have been built nationwide. Under the proper management of the farmers, they have received considerable economic and social benefits, and have been highly praised by experts and recognized by all walks of life. A lot of safe meat. As poultry farms grow in size and the number of poultry kept increases, the task of poultry management becomes more difficult. In order to strengthen management and reduce the burden on staff, many farms have successively installed network surveillance cameras, hoping to use technology to help management. However, due to the large number of poultry, the installation angles of the cameras are different, and the poultry i...

AI Technical Summary

Problems solved by technology

However, due to the large number of poultry, the installation angles of the cameras are different, and the poultry is too dense to cause problems such as occlusion, which makes the network monitoring method ineffective and has little effect

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