The invention discloses a hyperspectral image camouflage target detection method based on deep learning, and the method comprises the following steps: a, constructing a hyperspectral data set: collecting, preprocessing, dividing and marking the hyperspectral data set, and obtaining a training data set and a test data set; b, constructing a target detection model: using an open-source Mask R-CNN model, adjusting the Mask R-CNN model for an input hyperspectral data set, and constructing the target detection model; c, model training: training the target detection model constructed in the step b by using a training data set; and d, testing the model: detecting and identifying the test data set by using the target detection model trained in the step c. According to the invention, the target detection model based on deep learning is used, and the spectral dimension and spatial dimension information of the hyperspectral image is used at the same time, thereby achieving the positioning and classification of camouflage targets.