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convert_csv2gray.py
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convert_csv2gray.py
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import csv
import os
from PIL import Image
import numpy as np
datasets_path = r'.\fer2013'
train_csv = os.path.join(datasets_path, 'train.csv')
val_csv = os.path.join(datasets_path, 'val.csv')
test_csv = os.path.join(datasets_path, 'test.csv')
train_set = os.path.join(datasets_path, 'train')
val_set = os.path.join(datasets_path, 'val')
test_set = os.path.join(datasets_path, 'test')
for save_path, csv_file in [(train_set, train_csv), (val_set, val_csv), (test_set, test_csv)]:
if not os.path.exists(save_path):
os.makedirs(save_path)
num = 1
with open(csv_file) as f:
csvr = csv.reader(f)
header = next(csvr)
for i, (label, pixel) in enumerate(csvr):
pixel = np.asarray([float(p) for p in pixel.split()]).reshape(48, 48)
subfolder = os.path.join(save_path, label)
if not os.path.exists(subfolder):
os.makedirs(subfolder)
im = Image.fromarray(pixel).convert('L')
image_name = os.path.join(subfolder, '{:05d}.jpg'.format(i))
#print(image_name)
im.save(image_name)