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# training_data_stats.py
import cv2
import numpy as np
import time
from collections import Counter
import pandas as pd
def get_count_choices(a,b):
total_count_choices = Counter()
for i in range(a,b):
training_data = np.load(f'training_data-{i}.npy', allow_pickle=True)
choices = [str(data[1]) for data in training_data]
total_count_choices.update(choices)
count_choices_dict = dict(total_count_choices)
print(count_choices_dict)
def get_count_choices_per_file(a,b):
df = pd.DataFrame(columns=['File','W','S','A','D','WA','WD','SA','SD','NK','NONE'])
choice_to_column = {'[1, 0, 0, 0, 0, 0, 0, 0, 0]':'W',
'[0, 1, 0, 0, 0, 0, 0, 0, 0]':'S',
'[0, 0, 1, 0, 0, 0, 0, 0, 0]':'A',
'[0, 0, 0, 1, 0, 0, 0, 0, 0]':'D',
'[0, 0, 0, 0, 1, 0, 0, 0, 0]':'WA',
'[0, 0, 0, 0, 0, 1, 0, 0, 0]':'WD',
'[0, 0, 0, 0, 0, 0, 1, 0, 0]':'SA',
'[0, 0, 0, 0, 0, 0, 0, 1, 0]':'SD',
'[0, 0, 0, 0, 0, 0, 0, 0, 1]':'NK',
'None':'NONE'}
for i in range(a,b):
training_data = np.load(f'training_data-{i}.npy', allow_pickle=True)
choice = [str(data[1]) for data in training_data]
count_choices = Counter(choice)
count_choices_dict = dict(count_choices)
df = df.append({'File': f'training_data-{i}.npy'}, ignore_index=True)
for key in count_choices_dict:
#print(key,':',count_choices_dict[key])
if key == None:
df.loc[i-a,'NONE'] = count_choices_dict['NONE']
else:
df.loc[i-a,choice_to_column[key]] = count_choices_dict[key]
#print(df)
df.replace(np.nan, 0, inplace=True)
df.to_csv('training_data_count_001-100.csv', index=False)
def roi(img, vertices):
# Applies ROI Mask to Image
mask = np.zeros_like(img)
cv2.fillPoly(mask, vertices, color=[255,255,255])
masked = cv2.bitwise_and(img, mask)
return masked
def display_training_data(n):
'''
Displays training data
'''
training_data = np.load(f'training_data-{n}.npy', allow_pickle=True)
mask = False #True
if mask:
# Masking Region of Interest
vertices = np.array([[0,25],[0,270],[100,270],[100,200],[430,200],[430,270],[480,270],[480,25],], np.int32)
for data in training_data:
img = data[0]
choice = data[1]
if mask:
img = roi(img, [vertices])
cv2.imshow('screen', img)
print(choice)
print(img.shape)
if cv2.waitKey(25) & 0xFF == ord('q'):
cv2.destroyAllWindows()
break
if __name__ == "__main__":
start_time = time.time()
#get_count_choices(1,101)
get_count_choices_per_file(1,101)
#display_training_data(74)
print(f'Elapsed time: {time.time() - start_time} seconds')
# Output:
'''
Image Resolution : (270, 480, 3)
'W': [1, 0, 0, 0, 0, 0, 0, 0, 0] : 353725
'S': [0, 1, 0, 0, 0, 0, 0, 0, 0] : 2243
'A': [0, 0, 1, 0, 0, 0, 0, 0, 0] : 14303
'D': [0, 0, 0, 1, 0, 0, 0, 0, 0] : 13114
'WA': [0, 0, 0, 0, 1, 0, 0, 0, 0] : 30877
'WD': [0, 0, 0, 0, 0, 1, 0, 0, 0] : 29837
'SA': [0, 0, 0, 0, 0, 0, 1, 0, 0] : 1952
'SD': [0, 0, 0, 0, 0, 0, 0, 1, 0] : 1451
'NK': [0, 0, 0, 0, 0, 0, 0, 0, 1] : 52256
NONE : 242
'''
# Elapsed time: 181.86165976524353 seconds |