Possible memory leak when using mplfinance/matplotlib. How to solve it?

I am trying to make a lot (~1.7 mil) of images (candlesticks charts with volume) for a CNN. However, the script I currently have keeps increasing its memory usage after each iteration with about 2-5mb per iteration as far is I can tell. This increases until my memory is completely full no matter how many instances I am running of the script. (16gb of which the script eventually uses 11-12 gb's).

The goal is to run multiple instances of the script at the same time. I tried parallel processing, this did not turn out that well. Therefore, I am simply using multiple kernels. I have tried a lot of methods to reduce memory usage, but nothing seems to work.

I am using Jupyter notebooks (Python 3.8.5) (anaconda) in VS code, have a 64 bit Windows system. 16GB of RAM and a Intel i7 8th gen.

First Cell calls the packages, loads the data and sets the parameters.

# import required packages 
import matplotlib.dates as mpdates 
import matplotlib.pyplot as plt 
import mplfinance as mpf
import matplotlib as mpl
from PIL import Image
import pandas as pd 
import math as math
import numpy as np
import io   as io
import gc   as gc
import os as os


#set run instance number
run=1

#timeframe
tf = 20

#set_pixels
img_size=56

#colors
col_up = '#00FF00'
col_down = '#FF0000'
col_vol = "#0000FF"

#set directory
direct = "C:/Users/robin/1 - Scriptie/images/"

#loading the data
data1 = pd.read_csv(r'D:\1 - School\Econometrics\2020 - 2021\Scriptie\Explainable AI\Scripts\Data\test_data.csv',header=[0, 1] , index_col = 0 )
data1.index=pd.to_datetime(data1.index)

#subsetting the data
total_symbols = math.floor(len(data1.columns.unique(level=0))/6)
symbols1 = data1.columns.unique(level=0)[(run-1)*total_symbols:run*total_symbols]

#set the plot parameters
mc = mpf.make_marketcolors(up = col_up ,down = col_down, edge='inherit', volume= col_vol, wick='inherit')
s  = mpf.make_mpf_style(marketcolors=mc)   

The second cell defines the function used to plot the charts:

# creating candlestick chart with volume
def plot_candle(i,j,data,symbols,s,mc,direct,img_size, tf):
     
    #slicing data into 30 trading day windows
    data_temp=data[symbols[j]][i-tf:i]  

    #creating and saving the candlestick charts
    buf = io.BytesIO()
    save = dict(fname= buf, rc = (["boxplot.whiskerprops.linewidth",10]), 
                    pad_inches=0,bbox_inches='tight')
    mpf.plot(data_temp,savefig=save, type='candle',style=s, volume=True, axisoff=True,figratio=(1,1),closefig=True)
    buf.seek(0)
    im = Image.open(buf).resize((img_size,img_size))
    im.save(direct+"/"+str(symbols[j])+"/"+str(i-tf+1)+".png", "PNG")
    buf.close()
    plt.close("all")

The third cell loops through the data and calls the functions in the 2nd cell.

#check if images folder excists, if not, create it. 
if not os.path.exists(direct):
    os.mkdir("C:/Users/robin/1 - Scriptie/images")

for j in range(0,len(symbols1)):

    #Check if symbol folder excists, if not, create it 
    if not os.path.exists(direct+"/"+symbols1[j]):
             os.mkdir(direct + "/"+symbols1[j])

    for i in range(tf,len(data1)) :

        #check if the file has already been created
        if not os.path.exists(direct+"/"+str(symbols1[j])+"/"   +str(i-tf+1)+".png"):
            #call the functions and create the 
            plot_candle(i , j , data1 , symbols1 ,s ,mc ,direct , img_size, tf)
            gc.collect()