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I have a NumPy array with a shape of (893, 3). It is storing color data that I'm trying to convert into a file format that only support 255 unique colors. Is there a way to average the differences between the range of colors to produce 255 unique colors that are closest in value to the original 893?
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I would like to make a number array with numpy based on user inputs then find the mean median and mode of this array.
Here you go:
import numpy as np
array = np.asarray([int(i) for i in input().split()])
print(array.mean())
print(array.mode())
print(array.median())
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I have images (about 1000) with different numbers. Using opencv I extracted ROI from these images. Here's a small sample:
And I don't know how to extract these numbers or identify them. For opencv have a small threshold. I tried VGGnet keras (I rotated each image 1 degree to create 360 images as input for tensorflow), but the control image was mostly not recognized. Does anyone have an idea?
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I am working on a FFT program, and I would like to get the frequency which has the largest amplitude or intensity in a sound. I checked out some codes on internet, but I couldn't find how to get the amplitude on a python program.
Check librosa.core.stft This gives magnitude of each frequency bin at given time. More details here:
https://librosa.github.io/librosa/generated/librosa.core.stft.html?highlight=stft#librosa.core.stft
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What is the fastest method to write a function for time series calculation that counts consecutive values in the same series ? A For loop or vector
Here is what my data looks like:
enter image description here
You can use rolling function to calculate the sum of 4 consecutive hours
df.consumption4hr = df.Consumption.groupby(level='Accounts').rolling(window=4).sum()
with that you can just find the list of accounts that has 0 in that column. for example:
df[df.consumption4hr == 0].Accounts.unique()
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I have a mask of an object I've detected. Now I want to calculate the average color of the object. Is there a way to just check the unmasked pixels?
And what would be the best way to get the average color?
Should I use a Cluster or get the average g,b and r values ?
(I'm using python 3.5 and opencv 3.1 with extras.)
Thanks in advance
Use cv::mean with mask. It will give you Scalar with color components.