Deep learning-based smoke and fire identification model establishment method and smoke and fire identification method
A recognition model and deep learning technology, applied in the field of image processing, can solve problems such as indistinct features, abstract and non-specific pyrotechnic features, etc.
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Embodiment 1
[0034] This embodiment discloses a method for establishing a firework recognition model based on deep learning, such as figure 1 shown, including the following steps:
[0035] S01), image collection, the collected images include two types, one is fireworks pictures, and the other is normal pictures of the area to be detected, and the normal pictures are used as background images;
[0036] S02), gan network synthesis, using gan network synthesis technology to synthesize two types of pictures to generate a synthetic picture with a normal picture as the background, to increase the number of samples of the data set in the actual application scene;
[0037] S03), image labeling, during the image labeling process, compare whether the proportion of fireworks in the labeling frame exceeds 1 / 2, if yes, go to step S04, if not, go to step S05;
[0038] S04), directly mark the pyrotechnics;
[0039] S05), carry out pyrotechnics relabeling, divide the pyrotechnics part, and ensure that t...
Embodiment 2
[0044] This embodiment discloses a pyrotechnic recognition method based on deep learning. This method is based on the pyrotechnic recognition model established in Embodiment 1. After the pyrotechnic recognition model is imported into the detection system, as figure 2 shown, perform the following steps:
[0045] S21), start normal line inspection, and the camera performs line inspection along with the gimbal;
[0046] S22), detecting the images in the process of line inspection, giving an early warning when a target with a confidence degree greater than the threshold T1 is found, and judging the number of current early warning targets;
[0047] S23), record the current position of the pan / tilt and the focal length of the camera, for subsequent return of the pan / tilt and the camera to the initial position;
[0048] S24), start early warning detection from the point with the highest confidence;
[0049] S25), transfer the abscissa and ordinate in the image to the bottom platform...
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