基于TensorFlow的人脸属性操控网络，深度学习入门必学！

# Attribute classification model ## Quick Start Same attribute classification code as [AttGAN](https://github.com/LynnHo/AttGAN-Tensorflow). The model is trained on the training set (most images of official training and validation sets) of CelebA, and achieves 94.5% mean accuracy on the 13 attributes we use on the test set (official test set), please refer to the paper for the dataset configuration. To produce the same result (see [this file](https://github.com/csmliu/STGAN/files/3579879/quantitative.results.xlsx) given in [issue #18](https://github.com/csmliu/STGAN/issues/18#issuecomment-528414039)) as given in the paper, please use the following command to generate the manipulated images since I removed the `/ thres_int` in line 172 of test.py when merging `test.py`, `test_multi.py` and `test_slide.py` into one file before releasing the code. ```console python test.py --experiment_name 128 --test_int 2 cd att_classification python test.py --img_dir ../output/128/sample_testing ``` Note that the images used in the reconstruction image evulation and the user study are also generated by the above command. Also note that the tfrecord file is generated by [LynnHo/TfrecordCreator](https://github.com/LynnHo/TfrecordCreator-TfrecordLoarder).