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yolo v3学习笔记 #100

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any86 opened this issue Feb 6, 2023 · 0 comments
Open

yolo v3学习笔记 #100

any86 opened this issue Feb 6, 2023 · 0 comments

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@any86
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any86 commented Feb 6, 2023 •
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还在学习中, 先记录一些关键点 , 稍后补充文字, 形成完整的笔记

遍历3种特征图的每一个像素, 输出tx,ty.tw,th,confidence, classes

image

tx/ty是特征图中的偏移量, 实际特征图中的每一个像素对应到原图上是多个像素, 所以特征图下的位置bx其实是个小数, 公式如下: bx = cx + sigmoid(tx), 这样保证调整偏差后bx依旧和cx是同一个格子内的点

th/tw是预设锚框缩放的比例, pw/ph是预设锚框的尺寸, 所以bw = pw * exp(tw), 这里是exp是指数运算, 具体为什么用exp我也没太弄明白, 总之就好求导, 因为指数的导数还是自己本身, 后续再深入研究明白他.
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