运行了autopep8，但是缩进问题没有解决

Question

我是一个完整的python新手，曾尝试运行和理解ardamavi的代码（https://github.com/ardamavi/Game-Bot），但我无法解决这些缩进问题。你知道吗

你有什么想法吗？你知道吗

我试过： -用单个空格替换制表符 -我使用了IDLEs缩进函数 -我终于用上了autopep8

# Arda Mavi
import os
import numpy as np
from keras.utils import to_categorical
from scipy.misc import imread, imresize, imsave
from sklearn.model_selection import train_test_split


def get_img(data_path):
    # Getting image array from path:
    img = imread(data_path)
    img = imresize(img, (150, 150, 3))
    return img


def save_img(img, path):
    imsave(path, img)
    return

def get_dataset(dataset_path='Data/Train_Data'): s
    # Getting all data from data path:
    try:
        X = np.load('Data/npy_train_data/X.npy')
        Y = np.load('Data/npy_train_data/Y.npy')
    except:
        labels = os.listdir(dataset_path)  # Geting labels
        X = []
        Y = []
        count_categori = [-1, '']  # For encode labels
        for label in labels:
            datas_path = dataset_path + '/' + label
            for data in os.listdir(datas_path):
                img = get_img(datas_path + '/' + data)
                X.append(img)
                # For encode labels:
                if data != count_categori[1]:
                    count_categori[0] += 1
                    count_categori[1] = data.split(',')
                Y.append(count_categori[0])
        # Create dateset:
        X = np.array(X).astype('float32') / 255.
        Y = np.array(Y).astype('float32')
        Y = to_categorical(Y, count_categori[0] + 1)
        if not os.path.exists('Data/npy_train_data/'):
            os.makedirs('Data/npy_train_data/')
        np.save('Data/npy_train_data/X.npy', X)
        np.save('Data/npy_train_data/Y.npy', Y)
    X, X_test, Y, Y_test = train_test_split(
        X, Y, test_size=0.1, random_state=42)
    return X, X_test, Y, Y_test


File "get_dataset.py", line 23
    try:
    ^
IndentationError: unexpected indent