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IMDB-Clean: A Novel Benchmark for Age Estimation in the Wild

Scripts for creating the IMDB-Clean dataset for age estimation and gender classification.

If you use this repository in your research, we kindly rquest you to cite the following paper:

@article{lin2021fpage,
      title={FP-Age: Leveraging Face Parsing Attention for Facial Age Estimation in the Wild}, 
      author={Yiming Lin and Jie Shen and Yujiang Wang and Maja Pantic},
      year={2021},
      eprint={2106.11145},
      journal={arXiv},
      primaryClass={cs.CV}
}

Updates

2023-10: Added RetinFace Resnet50 face detector predicions for IMDB-Clean-1024 to csvs/imdb_1024_retinaface_predictions.csv, the number of predictions is smaller than the number of images because some faces are not detected. See visualisation for examples.

Introduction

We have cleaned the noisy IMDB-WIKI dataset using a constrained clustering method, resulting this new benchmark for in-the-wild age estimation. The annoations also allow this dataset to used for some other tasks, like gender classification and face recognition/verification. For more details please refer to our FPAge paper.

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How to use

Clone this repo, install the python requirements and run the script:

pip install -r ./requirements.txt
bash run_all.sh

This will download the original images from the IMDB-WIKI dataset. The file tree would become the following:

data
├── imdb
├── imdb-clean-1024
├── imdb-clean-1024-visualisation
csvs
├── imdb_test_new.csv
├── imdb_train_new.csv
├── imdb_valid_new.csv
├── imdb_test_new_1024.csv
├── imdb_train_new_1024.csv
└── imdb_valid_new_1024.csv

The cropped images are stored in imdb-clean-1024 and the annotations for the splits are in imdb_*_new_1024.csv which you can use to train age/gender estimation models.

Visualisation

Below are samples from imdb-clean-1024:

Community Contributions

Authors of MiVOLO have kindly provided extra face and body bounding box annotations here.

Disclaimer

We only provide new annotations under MIT licence. The images are from the IMDB-WIKI dataset. We do not own any of these images. Please refer to their website for the licence to use these images.