Lightweight deep network image target detection method suitable for Raspberry Pi

A lightweight deep network image target detection method applicable to Raspberry Pi belongs to the field of deep learning and target detection, and comprises the following steps: firstly, collecting an image containing a to-be-detected target, and preprocessing the collected image for network training; secondly, inputting the preprocessed image into a depth separable expansion convolutional neural network for feature extraction to obtain feature maps with different resolutions; inputting the feature maps with different resolutions into a feature pyramid network for feature fusion, and generating a fusion feature map carrying richer information; and then carrying out classification and positioning of a to-be-detected target on the fusion feature map by adopting a detection network, and finally carrying out non-maximum suppression to obtain an optimal target detection result. The image target detection method based on the deep neural network overcomes the difficulties that the image target detection method base