# Dataset Card for "hagrid50k"
This dataset is designed to train a ControlNet with human hands. It includes hand landmarks detected by MediaPipe(for more information refer to: https://developers.google.com/mediapipe/solutions/vision/hand_landmarker).
The source image data is from [HaGRID dataset](https://github.com/hukenovs/hagrid) and we use a modified version from Kaggle(https://www.kaggle.com/datasets/innominate817/hagrid-classification-512p) to build this dataset. We randomly select 50k data samples to build this dataset and the caption is generated using BLIP-2 model.



region:us
{"dataset_info": {"features": [{"name": "image", "dtype": "image"}, {"name": "conditioning_image", "dtype": "image"}, {"name": "text", "dtype": "string"}], "splits": [{"name": "train", "num_bytes": 11037324721.0, "num_examples": 50000}], "download_size": 11046953921, "dataset_size": 11037324721.0}}
TAGS
#region-us 

# Dataset Card for "hagrid50k"
This dataset is designed to train a ControlNet with human hands. It includes hand landmarks detected by MediaPipe(for more information refer to: URL
The source image data is from HaGRID dataset and we use a modified version from Kaggle(URL to build this dataset. We randomly select 50k data samples to build this dataset and the caption is generated using BLIP-2 model.



# Dataset Card for "hagrid50k"
This dataset is designed to train a ControlNet with human hands. It includes hand landmarks detected by MediaPipe(for more information refer to: URL
The source image data is from HaGRID dataset and we use a modified version from Kaggle(URL to build this dataset. We randomly select 50k data samples to build this dataset and the caption is generated using BLIP-2 model.
TAGS
#region-us 
 # Dataset Card for "hagrid50k"
This dataset is designed to train a ControlNet with human hands. It includes hand landmarks detected by MediaPipe(for more information refer to: URL
The source image data is from HaGRID dataset and we use a modified version from Kaggle(URL to build this dataset. We randomly select 50k data samples to build this dataset and the caption is generated using BLIP-2 model.