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import numpy as np


    

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# 1 of 20: cat, dog, bike, bus .... 
# vec 30
out = np.random.rand(7,7,30)
i=5
j=0
one = out[i,j,:]
cls = one[11:30] # 1 hot of 20 possible classes
0< cls <1->prob

box1 = one[0:5]-> c(object),x,y,w,h

box2 = one[5:10]

info we need-> centerx, centery, width, height 
centerx = which i, and which j , 0<x<1

x/grid_size(16)
mean(0.5) var
c(0.5)
w_real = 50 
h_real = 100
img_size = 448
w = w_real/img_size
h


out.shape = (7,7,5)->c, x,y,w,h
there is a cat if c==1, no cat if c==0, # of clase is 1, use either 0 or 1 to identify if there is a cat 


i ,j , x ,h ->cx ,cy 

cx = i*dscale(2**how many stride==2)+x*dscale
cy = j*dscale(2**how many stride==2)+y*dscale