The invention relates to a
bacterial colony intelligent
analysis method and device based on
deep learning and a storage medium, which are applied to the technical field of microbiological detection and
image analysis, and comprise the steps of performing model optimization on the characteristics of a
bacterial colony image based on a YOLOv11
deep learning model in combination with a transfer learning method, remarkably improving the accuracy and robustness of
bacterial colony detection, and improving the accuracy and robustness of bacterial colony detection. The problems of missing detection and
false detection caused by overlapping of bacterial colonies, various forms and complex backgrounds can be effectively solved; the method supports the simultaneous recognition and classification statistics of a plurality of bacterial colonies, automatically generates a structured Excel report containing rich information, does not need manual secondary data arrangement, improves the
standardization and
traceability of bacterial colony analysis, and provides reliable data support for
experimental research and detection evaluation. The full-process
automation of bacterial colony detection, classification, counting and
report generation is realized, manual intervention is not needed, the labor intensity of workers is greatly reduced, the bacterial colony analysis efficiency is improved, and the high-
throughput detection requirement is met.