understanding the dimensions in python arrays is a little bit tricky. one should understand its basics before jumping into its application and making operations.
prerequisite: having idea behind basic array in numpy, coding in python
let understand it through an example:
suppose we have a 2d array denoted by np_array_2d…
SITUATION: you and your boss are arguing about whether more sleep will make you more productive. you sleep for 7 hours every day and your boss is also aware of that fact.
first, we will make a hypothesis and NULL hypothesis from your perspective and then we will move on…
Fast RCNN are modified version of RCNN where a lot of differ comes with SPPNet.
for i in range(yvalue.size): #this yvalue and loop is only for using ploting y-axis (0-255)
for x in range(img.shape):
for y in range(img.shape):
rvalue[img[x,y,0]] = rvalue[img[x,y,0]]+1
gvalue[img[x,y,1]] = gvalue[img[x,y,1]]+1
bvalue[img[x,y,2]] = bvalue[img[x,y,2]]+1
#want to know the number of pixels
for ccc in range(rvalue.size):
for ccc in range(gvalue.size):
for ccc in range(bvalue.size):
#just showing the image
imgaa = Image.fromarray(img, 'RGB')
lets say A implies B (i.e A=>B).
Now consider A is son and B is Father. they both are arguing something. so if the father is wrong then son is also wrong (A is false and B is false=true) if the son is right then father must be right(A is true and B is true = true)
the son can be wrong but not the father (A is false and B is true= true)
but never can be son right and father false (A true and B is false= false)