Filtered Laion Face
This repository provides the pipeline to construt the face augmneted dataset used in MasterWeaver. The dataset contains ~160k text-image pairs from the LAION-Face dataset. We have generated the corresponding captions using BLIP2 and created several attribute-augmented faces.
Steps to Construct the Dataset
1. Clone the Repository
git clone https://huggingface.co/datasets/csyxwei/Filtered-Laion-Face
cd Filtered-Laion-Face
2. Download images
We have provided links of filerted laion face images in filtered_laion_faces.parquet
. You can download the original image using img2dataset tool:
pip install img2dataset
img2dataset --url_list ./filtered_laion_faces.parquet --input_format "parquet" \
--url_col "URL" --caption_col "TEXT" --output_format files \
--output_folder ./filtered_laion_faces/images --processes_count 16 --thread_count 128 --resize_mode no \
--save_additional_columns '["NSFW","similarity","LICENSE","SAMPLE_ID"]'
The downloaded images will be saved in the ./filtered_laion_faces/images
directory.
3. Process Laion Face Images
Next, use dlib and a face parsing model to crop and align the downloaded images:
cd data_scripts
CUDA_VISIBLE_DEVICES=0 python process_images.py
4. Augment the Face Images
After processing, construct the augmented faces using DeltaEdit. Refer to its official repository for configuration details.
Then, run the following command::
cd ../delta_edit
CUDA_VISIBLE_DEVICES=0 python scripts/inference_laion.py \
--image_dir "../filtered_laion_faces/images_cropped_face" \
--save_dir "../filtered_laion_faces/images_cropped_face_aug/" \
--target ""
The final directory structure will be as follows:
filtered_laion_faces
ββ images
ββ images_cropped
ββ images_cropped_face
ββ images_cropped_face_mask
ββ images_cropped_face_aug
ββ captions
Acknowledgements
This dataset is built upon the Laion Face dataset with tools from FFHQ, face-parsing.PyTorch, and DeltaEdit. We thank the authors for sharing the datasets and code.