How do I create a Image Segmentation Dataset

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I am also trying to create an image segmentation dataset and I am struggling with how to do that.

The dataset I want to upload to HF is the aisegmentcn-matting-human datasets, which you also can find at Kaggle.

I also have the dataset in my machine in a folder named data:

└── data/
    ├── clip_img/
    │   └── {group-id}/
    │       └── clip_{subgroup-id}/
    │           └── {group-id}-{img-id}.jpg
    └── matting/
        └── {group-id}/
            └── matting_{subgroup-id}/
                └── {group-id}-{img-id}.png

all matting images are of the kind {group-id}-{img-id}.png are exactly equal to the input image {group-id}-{img-id}.jpg but with the background removed. So, if labels are background and foreground, if the color is 0 it is background, anything else is foreground. Just 2 classes of labels.

The primary reason I want this dataset in HF is to use it in a HF space and notebook.
It seems I have to process the raw data into an expected format. If I just try to:

>>> from datasets import load_from_disk
>>> ds = load_from_disk('./data')
...
FileNotFoundError: Directory data is neither a dataset directory nor a dataset dict directory.

So, I guess I have to create a DatasetDict with image and label columns, right?
Is there a How To guide for this kind of image dataset?