A method and apparatus for accurate animal detection through YOLO-based lightweight bounding box detection and image processing are presented. An animal detection method according to an embodiment includes: acquiring an edge detection image and a full background separation image from an infrared image of one channel of an animal in a specific space through an image preprocessing process; synthesizing the infrared image, the edge detection image, and the entire background separation image into a three-channel composite image; learning a network through an image pyramid by generating an image of at least one size using the three-channel composite image; lightening the network through filter clustering so that it can be operated on an embedded board based on the YOLO algorithm; measuring a speed of a network to which scheduling is to be applied in the embedded board to which scheduling is to be applied, and then determining whether to compress or restore the network; compressing or decompressing the network according to the determination; and performing individual animal detection satisfying real-time requirements in the embedded board according to compression or restoration of the network.
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