# Examples of reading raw binary images and extracting statistical information in Python

Time：2021-4-19

Using Python language to read binary image files and extract non-zero data statistics (for example: Max, min, skewness and kurtosis)

Python novice, notes less, welcome to teach

``````
import struct
import math
import numpy
import scipy.stats

filename = input('enter file name')
f = open(filename, 'rb')
f.seek(0, 0)

c = 0
numOfZero = 0
s = 0
num = []
m = 0

while True:
if len(temp) == 0:
break
else:
c = c + 1
print(c)
print(numOfZero)

sum = 0
squSum = 0
min = 2000
max = 0
list = []
num = []
f.seek(0, 0)

for i in range(0, c):
b = struct.unpack('<f', a)
list.append(b[0])
if list[i] == 0:
numOfZero = numOfZero + 1
else:
num.append(b[0])
if list[i] > max:
max = list[i]
if list[i] < min and list[i] != 0:
min = list[i]
sum = sum + list[i]

stan_Dev = numpy.std(num)
median = numpy.median(num)
sk = scipy.stats.skew(num)
ku = scipy.stats.kurtosis(num)

print('numOfZero = ', numOfZero)
print('sum = ', sum)
print('meanValue = ',sum / (c - numOfZero))
print('maxValue = ', max)
print('minValue = ', min)
print('median = ', median)
print('stdev = ', stan_Dev)
print('skewness = ', sk)
print('kurtosis = ', ku)

f.close()
``````

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