# Dataset Card for "face_synthetics_spiga_captioned"

This is a copy of the [Microsoft FaceSynthetics dataset with SPIGA-calculated landmark annotations](https://huggingface.co/datasets/pcuenq/face_synthetics_spiga), and additional BLIP-generated captions. 
For a copy of the original FaceSynthetics dataset with no extra annotations, please refer to [pcuenq/face_synthetics](https://huggingface.co/datasets/pcuenq/face_synthetics).

Here is the code for parsing the dataset and generating the BLIP captions:
```py
from transformers import pipeline

dataset_name = "pcuenq/face_synthetics_spiga"
faces = load_dataset(dataset_name)
faces = faces["train"]

captioner = pipeline("image-to-text",model="Salesforce/blip-image-captioning-large", device=0)

def caption_image_data(example):
    image = example["image"]
    image_caption = captioner(image)[0]['generated_text']
    example['image_caption'] = image_caption
    return example

faces_proc = faces.map(caption_image_data)
faces_proc.push_to_hub(f"multimodalart/face_synthetics_spiga_captioned")
```

region:us
{"dataset_info": {"features": [{"name": "image", "dtype": "image"}, {"name": "image_seg", "dtype": "image"}, {"name": "landmarks", "dtype": "string"}, {"name": "spiga", "sequence": {"sequence": "float64"}}, {"name": "spiga_seg", "dtype": "image"}, {"name": "image_caption", "dtype": "string"}], "splits": [{"name": "train", "num_bytes": 31087489990.0, "num_examples": 100000}], "download_size": 31011261945, "dataset_size": 31087489990.0}}
TAGS
#region-us 

# Dataset Card for "face_synthetics_spiga_captioned"

This is a copy of the Microsoft FaceSynthetics dataset with SPIGA-calculated landmark annotations, and additional BLIP-generated captions. 
For a copy of the original FaceSynthetics dataset with no extra annotations, please refer to pcuenq/face_synthetics.

Here is the code for parsing the dataset and generating the BLIP captions:


# Dataset Card for "face_synthetics_spiga_captioned"

This is a copy of the Microsoft FaceSynthetics dataset with SPIGA-calculated landmark annotations, and additional BLIP-generated captions. 
For a copy of the original FaceSynthetics dataset with no extra annotations, please refer to pcuenq/face_synthetics.

Here is the code for parsing the dataset and generating the BLIP captions:
TAGS
#region-us 
 # Dataset Card for "face_synthetics_spiga_captioned"

This is a copy of the Microsoft FaceSynthetics dataset with SPIGA-calculated landmark annotations, and additional BLIP-generated captions. 
For a copy of the original FaceSynthetics dataset with no extra annotations, please refer to pcuenq/face_synthetics.

Here is the code for parsing the dataset and generating the BLIP captions:
passage: TAGS
#region-us 
# Dataset Card for "face_synthetics_spiga_captioned"

This is a copy of the Microsoft FaceSynthetics dataset with SPIGA-calculated landmark annotations, and additional BLIP-generated captions. 
For a copy of the original FaceSynthetics dataset with no extra annotations, please refer to pcuenq/face_synthetics.

Here is the code for parsing the dataset and generating the BLIP captions: