Bus passenger flow statistics method and system based on deep learning
A technology of deep learning and statistical methods, applied in the field of bus passenger flow statistics system, can solve problems such as crowding, caps, backpacks, etc., and achieve the effect of low cost, high efficiency and congestion
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[0052] Such as figure 1 Shown, the bus passenger flow statistics method based on deep learning of the present invention comprises the following steps:
[0053] The offline training stage of passenger flow head detection includes steps A1, A2, and A3, mainly to obtain ideal head detection model parameters through training, which are used for online detection in the online stage; the online real-time passenger flow statistics stage includes steps A4 and A5 , A6, A7, online detection, passenger flow statistics.
[0054] : Passenger flow sample data is collected offline, divided into training and test samples, and converted into the LMDB format required by the caffe deep learning framework.
[0055] : Build a deep learning model of passenger flow, train and test based on the sample data through the caffe deep learning framework, and learn to obtain the final model parameter file.
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