Closed gg22mm closed 4 months ago
我发现是这样的格式:
{
'relpath': array(['n01440764/ILSVRC2012_val_00000293.JPEG',
'n01440764/ILSVRC2012_val_00002138.JPEG',
'n01440764/ILSVRC2012_val_00003014.JPEG', ...,
'n15075141/ILSVRC2012_val_00046353.JPEG',
'n15075141/ILSVRC2012_val_00047144.JPEG',
'n15075141/ILSVRC2012_val_00049174.JPEG'], dtype='<U38'),
'synsets': array(['n01440764', 'n01440764', 'n01440764', ..., 'n15075141',
'n15075141', 'n15075141'], dtype='<U9'),
'class_label': array([ 0, 0, 0, ..., 999, 999, 999]),
'human_label': array(['tench, Tinca tinca', 'tench, Tinca tinca', 'tench, Tinca tinca',
..., 'toilet tissue, toilet paper, bathroom tissue',
'toilet tissue, toilet paper, bathroom tissue',
'toilet tissue, toilet paper, bathroom tissue'], dtype='<U121')
}
另外我已经整好的数据集: https://www.kaggle.com/datasets/weililong/sd-imagenet-val
大老,Imagenet 数据集太大了,有没有测试数据? 我看代码好象也不太对呢?如下: 运行:python main.py --base configs/autoencoder/autoencoder_kl_8x8x64.yaml --train True
代码中写着:self.synsets = [p.split("/")[0] for p in self.relpaths] 但是我看图片是这样的:ILSVRC2012_val_00000001.JPEG
有没有简单的数据测试一下?
标签这几个是什么意思,可以写死的吗 labels = { "relpath": np.array(self.relpaths), #图片转数字 "synsets": np.array([1]), #? "class_label": np.array([2]), #? "human_label": np.array([3]), #? }