Embedded pedestrian volume detection method based on light deep learning framework

The invention discloses an embedded pedestrian volume detection method based on a light deep learning framework. The embedded pedestrian volume detection method comprises the following steps of S1, building a hardware platform; S2, sampling, labeling and standardizing pedestrians by using a hardware platform, collecting training data and preprocessing the data; S3, improving a light SSD300 deep learning framework, and building a pedestrian volume detection deep learning model; S4, training the built pedestrian volume detection deep learning model according to the collected data and transplanting the model to a hardware platform; and S5, analyzing a result and carrying out visual display. Embedded equipment is selected to be connected with a camera to serve as a detection platform, a light improved SSD300 pedestrian volume detection deep learning model is carried, pedestrian volume detection is conducted on collected images, and pedestrian volume data is transmitted to a cloud server in real time to be display