Leaf shielding detection method based on deep learning and traditional algorithm
A detection method and deep learning technology, applied in the field of image processing, can solve problems such as public security impact and missing monitoring scenes, and achieve the effect of reducing the impact of public security, preventing missing, and strong generalization ability
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Embodiment 1
[0037] A method for detecting leaf occlusion based on deep learning and traditional algorithms, comprising the following steps:
[0038] S1, adjust the size of each test set image and each training set image collected so that all images have the same size, and the size of all images in this embodiment is 64*64; for each test set image and each The training set images are rotated to the left and right, and each test set image and each training set image can derive two images, which increases the sample size; adjust the contrast of each test set image and each training set image, Make the same image have multiple contrasts, increase the sample size, and adjust the brightness of each test set image and each training set image to increase the sample size of the test set image and training set image.
[0039] Specific steps are as follows:
[0040] S10, adjusting the size of each collected image so that all the collected images have the same size, and the resized image is set as t...
Embodiment 2
[0056] On the basis of embodiment 1, table 1 is the test set image, sample number unit: Zhang
[0057] Table 1
[0058]
[0059] In Table 1: the image without leaf occlusion is an image without leaf occlusion including urban and rural multi-scenes;
[0060] Detection rate = the number of images detected to be occluded by leaves / the number of images actually occluded by leaves
[0061] Accuracy rate = the number of images detected to be occluded by leaves and actually occluded by leaves / the number of images detected to be occluded by leaves.
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