Dataset Card for HumanEdit

Paper (CVPR 2025 AI for Content Creation (AI4CC) Workshop)

Usage

from datasets import load_dataset
from PIL import Image

# Load the dataset
ds = load_dataset("BryanW/HumanEdit")

# Print the total number of samples and show the first sample
print(f"Total number of samples: {len(ds['train'])}")
print("First sample in the dataset:", ds['train'][0])

# Retrieve the first sample's data
data_dict = ds['train'][0]

# Save the input image (INPUT_IMG)
input_img = data_dict['INPUT_IMG']
input_img.save('input_image.jpg')
print("Saved input image as 'input_image.jpg'.")

# Save the mask image (MASK_IMG)
mask_img = data_dict['MASK_IMG']
mask_img.save('mask_image.png') # Note that the format of the mask image may need to be adjusted. Refer to https://github.com/viiika/HumanEdit/mask_convert.py for more details.
print("Saved mask image as 'mask_image.png'.")

# Save the output image (OUTPUT_IMG)
output_img = data_dict['OUTPUT_IMG']
output_img.save('output_image.jpg')
print("Saved output image as 'output_image.jpg'.")

License

Creative Commons License This work is licensed under a Creative Commons Attribution 4.0 International License.

Citation

If you find this work helpful, please consider citing:

@article{bai2024humanedit,
  title={HumanEdit: A High-Quality Human-Rewarded Dataset for Instruction-based Image Editing},
  author={Bai, Jinbin and Chow, Wei and Yang, Ling and Li, Xiangtai and Li, Juncheng and Zhang, Hanwang and Yan, Shuicheng},
  journal={arXiv preprint arXiv:2412.04280},
  year={2024}
}