This post tries to answer whether given numbers are comparatively close to each other. This can help if you are using Python for data science or in the area of computer vision doing computing with images. A quick stack-overflow search shows discussion around finding “nearest” value from a set of given values for any given number   . However, there could be a need to limit how much further the nearest number could be. I’d call this limit a “threshold”.
Quite a few times, in my Python (esp. in computer vision related) programming I come across scenarios when I want to tell if the two numbers are close to each other. Some might ask, “Well define close!?” or “How close?”, well … comparatively close.
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While there are some interesting conversations about numpy.argmin() function’s performance (e.g. here, here and here), Continue reading →
As you already know, in order to calculate non-zero elements in your np array, you can use numpy.count_nonzero. But how about 0? How about an expression? Well, Continue reading →
Pillow (PIL) and NumPy libraries can do wonders in Python! I had once he requirement to overlap two images – not watermarking.
I found several alternatives, but curious to see which would work best.
- (x+y)/2 … Mathematically, x/2+y/2 seems equivalent to above, but it is not. We’d be loosing a ton of info by doing so!
- final = (x+y/2) and then addition = addition[addition>256]=256
- Pillow’s Image.blend(x,y,0.5)
- Pillow’s Image.composite(x,y,y)
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