In the early stage of fire, different amounts of smoke are often generated, so the high-precision and sensitive detection of smoke plays an important role in preventing the spread of fire.A SmokeNet algorithm based on optical flow estimation and target detection is proposed to detect smoke.The algorithm firstly converts the color space of the input image, then estimates smoke spreading by using the optical flow estimation algorithm LiteFlowNet, and eliminates the interference of moving objects by using the target detection algorithm YOLOv4.Finally, the smoke area size, shape and spreading track in the image can be obtained via noise reduction,so that the smoke can be evaluated.In the indoor smoke evaluation experiment, the method achieved 93.53% detection accuracy.