A large-scale face dataset for face parsing, recognition, generation and editing.

Related tags

Deep Learning generative-adversarial-network face-recognition celeba face-generation face-segmentation
Overview

CelebAMask-HQ

[Paper] [Demo]

image

CelebAMask-HQ is a large-scale face image dataset that has 30,000 high-resolution face images selected from the CelebA dataset by following CelebA-HQ. Each image has segmentation mask of facial attributes corresponding to CelebA.

The masks of CelebAMask-HQ were manually-annotated with the size of 512 x 512 and 19 classes including all facial components and accessories such as skin, nose, eyes, eyebrows, ears, mouth, lip, hair, hat, eyeglass, earring, necklace, neck, and cloth.

CelebAMask-HQ can be used to train and evaluate algorithms of face parsing, face recognition, and GANs for face generation and editing.

  • If you need the identity labels and the attribute labels of the images, please send request to the CelebA team.

  • Demo of interactive facial image manipulation

image

Sample Images

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Face Manipulation Model with CelebAMask-HQ

CelebAMask-HQ can be used on several research fields including: facial image manipulation, face parsing, face recognition, and face hallucination. We showcase an application on interactive facial image manipulation as bellow:

  • Samples of interactive facial image manipulation

image

CelebAMask-HQ Dataset Downloads

Related Works

  • CelebA dataset:
    Ziwei Liu, Ping Luo, Xiaogang Wang and Xiaoou Tang, "Deep Learning Face Attributes in the Wild", in IEEE International Conference on Computer Vision (ICCV), 2015
  • CelebA-HQ was collected from CelebA and further post-processed by the following paper :
    Karras et. al, "Progressive Growing of GANs for Improved Quality, Stability, and Variation", in Internation Conference on Reoresentation Learning (ICLR), 2018

Dataset Agreement

  • The CelebAMask-HQ dataset is available for non-commercial research purposes only.
  • You agree not to reproduce, duplicate, copy, sell, trade, resell or exploit for any commercial purposes, any portion of the images and any portion of derived data.
  • You agree not to further copy, publish or distribute any portion of the CelebAMask-HQ dataset. Except, for internal use at a single site within the same organization it is allowed to make copies of the dataset.

Related Projects using CelebAMask-HQ

License and Citation

The use of this software is RESTRICTED to non-commercial research and educational purposes.

@inproceedings{CelebAMask-HQ,
  title={MaskGAN: Towards Diverse and Interactive Facial Image Manipulation},
  author={Lee, Cheng-Han and Liu, Ziwei and Wu, Lingyun and Luo, Ping},
  booktitle={IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},
  year={2020}
}
Comments
  • How to process image without affecting background?

    How to process image without affecting background?

    Hi, first of all, thank you very much for sharing such nice project~! I am trying to use it on real-time webcam, however, process image will affect background? Is their a way to seperate backgound so that it wont get affect by editing facial parts?

    opened by swagzhang 7
  • Question about BN in the deconder

    Question about BN in the deconder

    Hi, it seems you didn't use ReLU and BN in the decoder side. Did you implement in this way purposely?

    In the defination of unetUp, self.conv = unetConv2(in_size, out_size, False), where False means is_batchnorm=False

    Thanks.

    opened by XiaoqiangZhou 6
  • Have trouble with g_mask.py

    Have trouble with g_mask.py

    I put CelebAMask-HQ-mask-anno under Datapreprocessing,and ran g_mask.py,but the pictures generated in CelebAMask-HQ-mask were black.Why?Shouldn't it be full labels?

    opened by yangyingni 6
  • where is the 'CelebAMask-HQ-label' folder ?

    where is the 'CelebAMask-HQ-label' folder ?

    wonderful work, but I didn't find the folder of 'CelebAMask-HQ-label', the 'g_color.py' need it. does it the 'CelebAMaskHQ-mask'(g_mask generated) = 'CelebAMask-HQ-label' ？ well, i just wanna confirm...

    Looking forward to your replay

    opened by dhhcj1 4
  • About testing model's performance

    About testing model's performance

    Hi, Could you please provide the testing code of calculating mAcc? I re-train a model based on your design but on a different dataset. I want to evaluate the performance. Thanks~

    opened by XiaoqiangZhou 4
  • Have trouble running this demo

    Have trouble running this demo

    I added all datasets into the file,the file was 3.11G after unzipped.I put HQ pictures under './Data_preprocessing/train_img',put label pictures under './Data_preprocessing/train_label'.But when i trained the network,it shows FileNotFoundError:[Error 2]No such file or directory: './Data_preprocessing/train_label\***.png',***always change,Can you tell me why?Thank you.

    opened by yangyingni 4
  • There may be some problems on the mask image below...

    There may be some problems on the mask image below...

    Type of Problem A: missing facial attribute B: mask area is too large C: useless label D: content does not match the label E: no content /////////////////////////////////

    CelebAMask-HQ-single/0 00481:
    00481_hair.png[A] 01499:
    01499_hair.png[B]

    CelebAMask-HQ-single/1 02260: 02260_hair.png[B] 02281: 02281_hair.png[B] 02905:
    02905_hat.png[C] 03137:
    03137_hat.png[C]

    CelebAMask-HQ-single/2 04790:
    04790_hair.png[E] 04790_l_brow.png[E] 04790_l_ear.png[E] 04790_l_eye.png[E] 04790_l_lip.png[E] 04790_mouth.png[E] 04790_neck.png[E] 04790_nose.png[E] 04790_r_brow.png[E] 04790_r_eye.png[E] 04790_u_lip.png[E] 04995:
    04995_skin.png[D] 04995_hair.png[A] 05130:
    05130_hair.png[B] 05591:
    05591_hair.png[B] 05608:
    05608_hair.png[B]

    CelebAMask-HQ-single/4 09150:
    09150_cloth.png[C] 09895:
    09895_hat.png[C]

    CelebAMask-HQ-single/5 10184:
    10184_hair.png[B]

    CelebAMask-HQ-single/6 13008:
    13008_hat.png[A]

    CelebAMask-HQ-single/7 15587:
    15587_hat.png[C]

    CelebAMask-HQ-single/8 17586:
    17586_hair.png[A]

    CelebAMask-HQ-single/9 18279:
    18279_skin.png[D] 18279_hair.png[A] 18322:
    18322_r_brow.png[D] 18322_hair.png[A]

    CelebAMask-HQ-single/10 20043:
    20043_hat.png[C]

    CelebAMask-HQ-single/11 23088:
    23088_hat.png[C] 23888:
    23888_hat.png[C]

    CelebAMask-HQ-single/13 26534:
    26534_hair.png[D]

    End

    opened by sobopark 4
  • demo QImage(): too many arguments

    demo QImage(): too many arguments

    File "demo.py", line 210, in edit qim = QImage(result.data, result.shape[1], result.shape[0], result.strides[0], QImage.Format_RGB888) TypeError: arguments did not match any overloaded call: QImage(): too many arguments QImage(QSize, QImage.Format): argument 1 has unexpected type 'memoryview' QImage(int, int, QImage.Format): argument 1 has unexpected type 'memoryview' QImage(bytes, int, int, QImage.Format): argument 1 has unexpected type 'memoryview' QImage(sip.voidptr, int, int, QImage.Format): argument 1 has unexpected type 'memoryview' QImage(bytes, int, int, int, QImage.Format): argument 1 has unexpected type 'memoryview' QImage(sip.voidptr, int, int, int, QImage.Format): argument 1 has unexpected type 'memoryview' QImage(List[str]): argument 1 has unexpected type 'memoryview' QImage(str, format: str = None): argument 1 has unexpected type 'memoryview' QImage(QImage): argument 1 has unexpected type 'memoryview' QImage(Any): too many arguments [1] 16810 abort (core dumped) python demo.py

    opened by diaodeyi 3
  • Stage 2 training

    Stage 2 training

    I know that Editing Behavior Simulated Training be divided into two stage.

    In stage 2, dense mapping network and alpha blending network is trained.

    Doesn't the discriminator learn? If you are learning discriminator, do you use different multi discriminators for the two generators(Ga = Dense mapping network, Gb = alpha blender)? In other wards, are there two discriminators?

    opened by ksoy0128 3
  • Demo problem

    Demo problem

    Hi，I try to run demo.py but find it has a problem about missing G model like followings:./checkpoints/label2face_512p/latest_net_G.pth not exists yet!Could you please share latest_net_G.pth? Looking forward to your reply!

    opened by flynnamy 3
  • how to split train/test

    how to split train/test

    how to split train/test

    I downloaded CelebAMask-HQ.zip data. After unzip file, I saw the folder data below, but I don't know how to split it to train/test. Could you help me how to split train/test? and which folder I will use. Thanks

    CelebA-HQ-img CelebAMask-HQ-mask-anno CelebA-HQ-to-CelebA-mapping.txt CelebAMask-HQ-attribute-anno.txt CelebAMask-HQ-pose-anno.txt README.txt

    opened by huynx8888 3
  • cannot import name 'make_folder' from 'utils'

    cannot import name 'make_folder' from 'utils'

    Hello, I am having some troubles by trying to import the make_folder function from make_folder. I have the utils library installed but don't find the make_folder function. Is it because I have to git bash all the files ? I just wanted to use the pre trained models.

    opened by emmar2 0
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