def cross_ref_replace_dict(t_file_name):
#This function creates the cross reference dictionary used by
#insert_mods_into_js_file
import pandas as pd
from digit_capture import set_file_name_prefix
from digit_capture import get_global_settings as gs
colab_choice_save=['not_colab_output(imgData)','colab_output(imgData)']
colab_choice_label=['change_class_label_no_colab()',
'change_class_label_colab()']
t_full_side_size=gs('grid_count')*gs('pxl')
cross_ref_dict={'?width?':t_full_side_size,'?height?':t_full_side_size}
test_keys = ["?class00?",
"?class01?",
"?class02?",
"?class03?",
"?class04?",
"?class05?",
"?class06?",
"?class07?",
"?class08?",
"?class09?",
"?selval?",
"?width?",
"?height?"]
test_values = [0,0,0,0,0,0,0,0,0,0,3,t_full_side_size,t_full_side_size]
# using dictionary comprehension
# to convert lists to dictionary
res = {test_keys[i]: test_values[i] for i in range(len(test_keys))}
res['?selval?']=get_val_from_dict_csv('?selval?')
#fname_pfx=set_file_name_prefix(0)[0]
#print(fname_pfx)
#df=pd.read_csv(fname_pfx+t_file_name,header=None)
#t_df=df.iloc[:,0:2]
#t_list=['class','replace_dict']
#t_df.columns = t_list
#dd=t_df.groupby('class').count().to_dict()
dd=get_class_counts(t_file_name)
#print(dd['replace_dict'])
for k, v in dd['replace_dict'].items():
#print(k,dd['replace_dict'][k])
res[k]=dd['replace_dict'][k]
res['?grid_count?']=get_dict()['grid_count']
res['?pxl?']=get_dict()['pxl']
res['?line_wd?']=get_dict()['line_wd']
res['?output_data?']=colab_choice_save[in_colab()]
res['?class_label_choice?']=colab_choice_label[in_colab()]
return res
def get_val_from_dict_csv(t_key):
#input is a key. That is the row entry key in the dictionary_inputs.csv file.
#Read the file into pandas. Convert the Name column into a list. Find the
#index where the lest entry = the_key. Use the index to get the value
#from a list made from th Value column in the file. Return the value as
#a string
import pandas as pd
t_prefix=set_file_name_prefix(in_colab())[0]
t_file=t_prefix+'dictionary_inputs.csv'
df=pd.read_csv(t_file)
t_list_n=list(df['Name'])
t_pos=t_list_n.index(t_key)
t_list_v=list(df['Value'])
return str(t_list_v[t_pos])
def set_file_name_prefix(colab):
# Gets pathname etc based on there it is run.
# if colab=1, set up structure for colab.
# if colab=0, set up structure for local.
# if colab=2, set up structure when in /content/drive
import sys
import os
t_prefix=""
t_path=""
if(in_colab()==1):
colab=1
if(colab==1):
t_path='/content/drive/My Drive/Colab Notebooks/digit_data_entry/digit_data_entry'
t_prefix=t_path+"/"
else:
if(colab==0):
t_prefix="/content/drive"
st=os.getcwd()
t_path=st+"/"+t_prefix
t_prefix=t_path+"/"
return (t_prefix,t_path)
def update_class_number(nw_class_index):
#reads in dictionary_inputs.csv which holds values for global
#variable where the name is the global variable name. Once read in,
#it updates class label. This needs to be done via user so it can be changed
#as a user enters different digit classes.
import pandas as pd
t_list02=[]
for i in range(0,10):
t_class='?class0'+str(i)+'?'
t_list02.append(t_class)
nw_class=t_list02[nw_class_index]
t_prefix=set_file_name_prefix(in_colab())[0]
t_file=t_prefix+'dictionary_inputs.csv'
df=pd.read_csv(t_file)
t_list=list(df['Name'])
t_pos=t_list.index('t_class')
df.at[t_pos, 'Value']=nw_class
t_pos=t_list.index('?selval?')
df.at[t_pos, 'Value']=nw_class_index
df.to_csv(t_file,index=False)
return df
def mount_drive():
#Used to mount google drive when run in colab
if(not in_colab()):
return
from google.colab import drive
drive.mount('/content/drive')