The invention discloses a logistics violation behavior identification method and device, equipment and a storage medium. The method comprises the steps of: S1, collecting and obtaining a plurality ofpictures of logistics violation behaviors; S2, carrying out
data labeling on logistics violation behaviors occurring in the plurality of pictures, and carrying out conversion to generate a picture
data set in a TFRecord format; S3, based on a TensorFlow
object detection API, training a YOLOv3 model which is converted into a TensorFlow solidification model in advance through a picture
data set, verifying the trained YOLOv3 model, and obtaining a violation identification model; and S4, identifying the logistics scene through the violation identification model, and judging whether a logistics violation behavior exists or not to obtain an identification result. According to the invention, the YOLOv3 and the TensorFlow
object detection API are combined and applied to the field of logistics to carry out violation behaviors; the invention greatly improves the training speed of the model and the precision and speed in the training and supervision process, guarantees the interests of the user,provides the
service quality of the user, reduces the loss of the logistics industry, improves the
transfer efficiency and quality, and enables the logistics to be closer on an intelligent road.