# Dataset Card for `face_synthetics`

This is a copy of [Microsoft FaceSynthetics dataset](https://github.com/microsoft/FaceSynthetics), uploaded to Hugging Face Datasets for convenience.

Please, refer to the original [license](LICENSE.txt), which we replicate in this repo.

The dataset was uploaded using the following code, which assumes the original `zip` file was uncompressed to `/data/microsoft_face_synthetics`:

```Python
from datasets import Dataset
from pathlib import Path
from PIL import Image

face_synthetics = Path("/data/microsoft_face_synthetics")

def entry_for_id(entry_id):
    if type(entry_id) == int:
        entry_id = f"{entry_id:06}"
    image = Image.open(face_synthetics/f"{entry_id}.png")
    image_seg = Image.open(face_synthetics/f"{entry_id}_seg.png")
    with open(face_synthetics/f"{entry_id}_ldmks.txt") as f:
        landmarks = f.read()
    return {
        "image": image,
        "image_seg": image_seg,
        "landmarks": landmarks,
    }

def generate_entries():
    for x in range(100000):
        yield entry_for_id(x)

ds = Dataset.from_generator(generate_entries)
ds.push_to_hub('pcuenq/face_synthetics')
```

Note that `image_seg`, the segmented images, appear to be black because each pixel contains a number between `0` to `18` corresponging to the different categories, see the [original README]() for details. We haven't created visualization code yet.

region:us
{"dataset_info": {"features": [{"name": "image", "dtype": "image"}, {"name": "image_seg", "dtype": "image"}, {"name": "landmarks", "dtype": "string"}], "splits": [{"name": "train", "num_bytes": 33730885609.0, "num_examples": 100000}], "download_size": 34096881533, "dataset_size": 33730885609.0}}
TAGS
#region-us 

# Dataset Card for 'face_synthetics'

This is a copy of Microsoft FaceSynthetics dataset, uploaded to Hugging Face Datasets for convenience.

Please, refer to the original license, which we replicate in this repo.

The dataset was uploaded using the following code, which assumes the original 'zip' file was uncompressed to '/data/microsoft_face_synthetics':



Note that 'image_seg', the segmented images, appear to be black because each pixel contains a number between '0' to '18' corresponging to the different categories, see the [original README]() for details. We haven't created visualization code yet.

# Dataset Card for 'face_synthetics'

This is a copy of Microsoft FaceSynthetics dataset, uploaded to Hugging Face Datasets for convenience.

Please, refer to the original license, which we replicate in this repo.

The dataset was uploaded using the following code, which assumes the original 'zip' file was uncompressed to '/data/microsoft_face_synthetics':



Note that 'image_seg', the segmented images, appear to be black because each pixel contains a number between '0' to '18' corresponging to the different categories, see the [original README]() for details. We haven't created visualization code yet.
TAGS
#region-us 
 # Dataset Card for 'face_synthetics'

This is a copy of Microsoft FaceSynthetics dataset, uploaded to Hugging Face Datasets for convenience.

Please, refer to the original license, which we replicate in this repo.

The dataset was uploaded using the following code, which assumes the original 'zip' file was uncompressed to '/data/microsoft_face_synthetics':



Note that 'image_seg', the segmented images, appear to be black because each pixel contains a number between '0' to '18' corresponging to the different categories, see the [original README]() for details. We haven't created visualization code yet.
passage: TAGS
#region-us 
# Dataset Card for 'face_synthetics'

This is a copy of Microsoft FaceSynthetics dataset, uploaded to Hugging Face Datasets for convenience.

Please, refer to the original license, which we replicate in this repo.

The dataset was uploaded using the following code, which assumes the original 'zip' file was uncompressed to '/data/microsoft_face_synthetics':



Note that 'image_seg', the segmented images, appear to be black because each pixel contains a number between '0' to '18' corresponging to the different categories, see the [original README]() for details. We haven't created visualization code yet.