Fer2013表情识别数据集还原为jpg

Fer2013数据集下载

https://www.kaggle.com/c/challenges-in-representation-learning-facial-expression-recognition-challenge/data

把csv文件分为train、test、val三类

# -*- coding: utf-8 -*-
import csv
import os

database_path = r'/Users/zhaodongyu/Desktop/vision and image/Project'
datasets_path = r'/Users/zhaodongyu/Desktop/vision and image/Project/datasets'
csv_file = os.path.join(database_path, 'fer2013.csv')
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')


with open(csv_file) as f:
    csvr = csv.reader(f)
    header = next(csvr)
    rows = [row for row in csvr]

    trn = [row[:-1] for row in rows if row[-1] == 'Training']
    csv.writer(open(train_csv, 'w+')).writerows([header[:-1]] + trn)
    print(len(trn))

    val = [row[:-1] for row in rows if row[-1] == 'PublicTest']
    csv.writer(open(val_csv, 'w+')).writerows([header[:-1]] + val)
    print(len(val))

    tst = [row[:-1] for row in rows if row[-1] == 'PrivateTest']
    csv.writer(open(test_csv, 'w+')).writerows([header[:-1]] + tst)
    print(len(tst))

把每个csv按照标签还原为jpg图像

# -*- coding: utf-8 -*-
import csv
import os
from PIL import Image
import numpy as np


datasets_path = r'/Users/zhaodongyu/Desktop/vision and image/Project/datasets'
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)