# MIT 6.8300/6.8301 Advances in Computer Vision Final Project
This is a dataset card used for our final projet on control nets

Dataset is obtained from https://www.kaggle.com/datasets/kengoichiki/the-metropolitan-museum-of-art-ukiyoe-dataset

Here, we used BLIP for image captions (prompt), used CV2 canny edge detection algorithm for conditioning images (target)
region:us
{"dataset_info": {"features": [{"name": "source", "dtype": "image"}, {"name": "target", "dtype": "image"}, {"name": "prompt", "dtype": "string"}], "splits": [{"name": "train", "num_bytes": 1693358001.33, "num_examples": 4015}], "download_size": 1744645145, "dataset_size": 1693358001.33}}
TAGS
#region-us 

# MIT 6.8300/6.8301 Advances in Computer Vision Final Project
This is a dataset card used for our final projet on control nets

Dataset is obtained from URL

Here, we used BLIP for image captions (prompt), used CV2 canny edge detection algorithm for conditioning images (target)
# MIT 6.8300/6.8301 Advances in Computer Vision Final Project
This is a dataset card used for our final projet on control nets

Dataset is obtained from URL

Here, we used BLIP for image captions (prompt), used CV2 canny edge detection algorithm for conditioning images (target)
TAGS
#region-us 
 # MIT 6.8300/6.8301 Advances in Computer Vision Final Project
This is a dataset card used for our final projet on control nets

Dataset is obtained from URL

Here, we used BLIP for image captions (prompt), used CV2 canny edge detection algorithm for conditioning images (target)
passage: TAGS
#region-us 
# MIT 6.8300/6.8301 Advances in Computer Vision Final Project
This is a dataset card used for our final projet on control nets

Dataset is obtained from URL

Here, we used BLIP for image captions (prompt), used CV2 canny edge detection algorithm for conditioning images (target)