我正在尝试解析视觉基因组区域描述中的短语json将数据分为训练和测试集

如何解决我正在尝试解析视觉基因组区域描述中的短语json将数据分为训练和测试集

from sklearn.model_selection import train_test_split
    
parser = argparse.ArgumentParser(description='Splits visual_genome file into training and test sets.')
parser.add_argument('phrase',Metavar='phrase',type=str,help='Path to visual_genome annotations file.')
parser.add_argument('train',help='Where to store visual_genome training annotations')
parser.add_argument('test',help='Where to store visual_genome test annotations')
parser.add_argument('-s',dest='split',type=float,required=True,help="A percentage of a split; a number in (0,1)")
args = parser.parse_args()
    
def save_visual_genome(file,id,x,y,width,height,phrase,images):
    with open(file,'wt',encoding='UTF-8') as vg:
        json.dump({ 'id': id,'x': x,'y': y,'width': width,'height': height,'phrase': phrase,'image': image},vg,indent=2,sort_keys=True)
    
def main(args):
    with open(args.phrase,'rt',encoding='UTF-8') as phrase:
        vg = json.load(phrase)
        id = vg['id']
        x = vg['x']
        y = vg['y']
        width = vg['width']
        height = vg['height']
        phrase = vg['phrase']
        image = vg['image']
    
        a,b = train_test_split(phrase,train_size=args.split)
    
        save_visual_genome(args.train,a,image)
        save_visual_genome(args.test,b,image)
    
        print("Saved {} entries in {} and {} in {}".format(len(a),args.train,len(b),args.test))
    
if __name__ == "__main__":
    main(args)

我收到此错误：

id = vg['id']    # this line throws the error
TypeError: list indices must be integers or slices,not str

这里可能出现什么问题？是否会有更有效或更简单的方法来执行相同任务？

解决方法

尝试替换

vg = json.load(phrase)

使用

vg = json.loads(phrase.read())

也

• train_test_split方法将一个numpy数组作为输入。检查https://scikit-learn.org/stable/modules/generated/sklearn.model_selection.train_test_split.html
• 两次使用相同的变量名（即词组）时要小心