so I wrote a script to get the average grey value of each image in a folder. when I execute print(np.mean(img) I get all the values on the terminal. But i don't know how to get the values to a csv data.
import glob
import cv2
import numpy as np
import csv
import pandas as pd
files = glob.glob("/media/rene/Windows8_OS/PROMON/Recorded Sequences/6gParticles/650rpm/*.png")
for file in files:
img = cv2.imread(file)
finalArray = np.mean(img)
print(finalArray)
so far it works but I need to have the values in a csv data. I tried csvwriter and pandas but did not mangage to get a file containing the grey scale values.
Is this what you're looking for?
files = glob.glob("/media/rene/Windows8_OS/PROMON/Recorded Sequences/6gParticles/650rpm/*.png")
mean_lst = []
for file in files:
img = cv2.imread(file)
mean_lst.append(np.mean(img))
pd.DataFrame({"mean": mean_lst}).to_csv("path/to/file.csv", index=False)
Related
` from deepface import DeepFace
import pandas as pd
import os, os.path
from os import path
test = '(path to jpg images)'
csv_records = '(path to save csv records)'
df = pd.DataFrame()
for file in os.listdir(test):
if file.endswith('.jpg'):
thisframe = 0
filename = str(os.path.join(test, str(thisframe) + '.jpg'))
predictions = DeepFace.analyze(filename, actions = ['emotion'])
df2 = pd.DataFrame(predictions)
df3 = df.append(df2)
df3.to_csv(os.path.join(csv_records, 'record.csv'))
thisframe += 1`
I'm making an emotion recognition program and the images are obtained from a program which exports frames in jpg format from real-time footage. I want to pass those images into the deepface.analyze program and then combine the 'emotion' part of the analysis for all of the frames into a dataframe and subsequently export the results into a csv file. So if there's 24 frames, there should be 24 'emotion' results in the csv file.
I've tried searching other questions here but they either don't answer my question or I don't understand them. Thanks in advance.
My dataframe is originally a text file, where the columns are separated by a tab.
I first changed these tabs to spaces by hand (sep=" "), loaded and plotted the data, my plot looked the way it should.
Since I have multiple files to plot, its not really handy to change the separator of each file. That's why I changed the seper<tor to sep="\s+".
Suddenly the x-axis of my new plot takes every single position value and overlaps them.
Anyone knows why this is happening and how to prevent it?
My first code looked like:
import pandas as pd
import numpy as np
from functools import reduce
data1500 = pd.read_csv('V026-15.000-0.1.txt', sep = " ", index_col='Position')
plt.plot(data_merged1.ts1500, label="ts 15.00")
and the second:
import pandas as pd
import numpy as np
from functools import reduce
from matplotlib import pyplot as plt
data1500 = pd.read_csv('V025-15.000-0.5.txt', sep = "\s+", index_col='Position')
plt.plot(data_merged2.ts1500, label="ts 15.00")
you could do this to import a tab-delimited file:
import re
with open('V026-15.000-0.1.txt.txt') as f:
data = [re.split('\t',x) for x in f.read().split('\n')]
or do this:
import csv
with open('data.txt', newline = '') as mytext:
data = csv.reader(mytext, delimiter='\t')
then to plot your data you should do as follow:
Read each line in the file using for loop.
Append required columns into a list.
After reading the whole file, plot the required data
something like this:
for row in data:
x.append(row[0])
y.append(row[1])
plt.plot(x, y)
I'm hoping to get some help here. I'm trying to create some simple bar/line graphs from a csv file, however, it gives me an empty graph until I open this csv file manually in excel and change the data type to numeric. I've tried changing the data type with pd.to_numeric but it still gives an empty graph.
The csv that I'm trying to visualise is web data that I scraped using Beautiful Soup, I used .text method do get rid of all of the HTML tags so maybe it's causing the issue?
Would really appreciate some help. thanks!
Data file: https://dropmefiles.com/AYTUT
import numpy
import matplotlib
from matplotlib import pyplot as plt
import pandas as pd
import csv
my_data = pd.read_csv('my_data.csv')
my_data_n = my_data.apply(pd.to_numeric)
plt.bar(x=my_data_n['Company'], height=my_data_n['Market_Cap'])
plt.show()
Your csv file is corrupt. There are commas at the end of each line. Remove them and your code should work. pd.to_numeric is not required for this sample dataset.
Test code:
from matplotlib import pyplot as plt
import pandas as pd
my_data = pd.read_csv('/mnt/ramdisk/my_data.csv')
fig = plt.bar(x=my_data['Company'], height=my_data['Market_Cap'])
plt.tick_params(axis='x', rotation=90)
plt.title("Title")
plt.tight_layout()
plt.show()
I want python to take ANY .xls file from given location and save it as .xlsx with original file name? How I can do that so anytime I paste file to location it will be converted to xlsx with original file name?
import pandas as pd
import os
for filename in os.listdir('./'):
if filename.endswith('.xls'):
df = pd.read_excel(filename)
df.to_excel(??)
Your code seems to be perfectly fine. In case you are only missing the correct way to write it with the given name, here you go.
import pandas as pd
import os
for filename in os.listdir('./'):
if filename.endswith('.xls'):
df = pd.read_excel(filename)
df.to_excel(f"{os.path.splitext(filename)[0]}.xlsx")
A possible extension to convert any file that gets pasted inside the folder can be implemented with an infinite loop, for instance:
import pandas as pd
import os
import time
while True:
files = os.listdir('./')
for filename in files:
out_name = f"{os.path.splitext(filename)[0]}.xlsx"
if filename.endswith('.xls') and out_name not in files:
df = pd.read_excel(filename)
df.to_excel(out_name)
time.sleep(10)
Using Python can I open a text file, read it into an array, then save the file as a NetCDF?
The following script I wrote was not successful.
import os
import pandas as pd
import numpy as np
import PIL.Image as im
path = 'C:\path\to\data'
grb = [[]]
for fn in os.listdir(path):
file = os.path.join(path,fn)
if os.path.isfile(file):
df = pd.read_table(file,skiprows=6)
grb.append(df)
df2 = pd.np.array(grb)
#imarray = im.fromarray(df2) ##cannot handle this data type
#imarray.save('Save_Array_as_TIFF.tif')
i once used xray or xarray (they renamed them selfs) to get a NetCDF file into an ascii dataframe... i just googled and appearantly they have a to_netcdf function
import xarray and it allows you to treat dataframes just like pandas.
so give this a try:
df.to_netcdf(file_path)
xarray slow to save netCDF