The invention provides a YOLOV3-based smoke and fire automatic detection and early warning method. The method comprises the steps of S1, constructing a sample set of a training detection model; S2, establishing a deep learning target detection network architecture based on YOLOV3; S3, configuring training parameters, and training a detection model; S4, acquiring to-be-detected image information; acquiring image frames of an on-site video picture from monitoring equipment on a to-be-detected site, and processing frame-by-frame images by utilizing an image preprocessing method; S5, detecting smoke and flame targets, and sending the video image frames processed in the step S4 into a pre-trained detection model in the step S3 for target detection, and outputting a detection result; S6, carrying out post-processing on a detection result; and S7, continuously analyzing the detection results of the multiple frames of images, confirming that the target is valid and outputting an alarm. According to the YOLOV3-based smoke and fire automatic detection and early warning method, second-level detection and alarm can be realized, the fire early warning time is greatly shortened, timely notification and timely rescue are realized, and fire spreading is effectively prevented.