1. A fluoroscopic inspection method for automatic classification and recognition of cargoes, comprising: performing scanning and imaging for a container by using an X-ray scanning device to acquire a scanned image; segmenting the scanned image into small regions according to gray scales and texture features, such that the gray scales and the texture features of the image in each small region are uniform; extracting features of the small regions; generating a classifier according to annotated images, and/or storing or updating an existing classifier; and recognizing the small regions by using the classifier according to the extracted features, to obtain a probability of each small region pertaining to a certain category of cargoes, and merging small regions to obtain large regions each representing a category, wherein the method further comprises a training stage, and wherein, in the training stage, firstly, after scanned images of cargoes in containers are acquired, each of the scanned images is pre-segmented into small regions according to similarities in terms of gray scales and texture features, and features of the small regions are extracted; subsequently, each of the scanned images is annotated according to a Manifest corresponding to the scanned image, and small regions that pertain to the same category and are adjacent to or interconnected with each other are merged into a large region; and finally, features of all the small regions in each of the large regions constitute a feature cluster, and the classifier is trained according to the feature clusters of the known categories, for subsequent recognition.