A universal hardware accelerator system platform oriented to a YOLO algorithm and capable of being rapidly deployed belongs to the technical field of computers, considers the deployment requirements of the YOLO target detection algorithm on rapidness, high performance and low power consumption, and has a wide application scene. The platform is composed of an ARM subsystem, an FPGA subsystem and an off-chip memory, the ARM subsystem is responsible for parameter initialization, image preprocessing, model parameter preprocessing, data field address allocation, FPGA accelerator driving and image post-processing, and the FPGA subsystem is responsible for high-density calculation of a YOLO algorithm. After the platform is started, a YOLO algorithm configuration file is read, accelerator driving parameters are initialized, a to-be-detected image is preprocessed, then model weight and bias data are read, quantization, fusion and reordering are executed, an FPGA subsystem is driven to execute model calculation, and a calculation result is post-processed to obtain a target detection image. According to the method, the YOLO algorithm can be quickly deployed on the premise of high performance and low power consumption.