- Keterangan :
Kumpulan Data Atribut CelebFaces (CelebA) adalah kumpulan data atribut wajah berskala besar dengan lebih dari 200 ribu gambar selebriti, masing-masing dengan 40 anotasi atribut. Gambar dalam kumpulan data ini mencakup variasi pose yang besar dan latar belakang yang berantakan. CelebA memiliki keragaman yang besar, jumlah yang besar, dan anotasi yang kaya, termasuk - 10.177 jumlah identitas, - 202.599 jumlah gambar wajah, dan - 5 lokasi landmark, 40 anotasi atribut biner per gambar.
Kumpulan data dapat digunakan sebagai kumpulan pelatihan dan pengujian untuk tugas visi komputer berikut: pengenalan atribut wajah, deteksi wajah, dan lokalisasi landmark (atau bagian wajah).
Dokumentasi Tambahan : Jelajahi Makalah Dengan Kode
Kode sumber :
tfds.datasets.celeb_a.Builder
Versi :
-
2.0.1
: API terpisah baru ( https://tensorflow.org/datasets/splits ) -
2.1.0
(default): Fitur identitas ditambahkan.
-
Ukuran unduhan :
1.39 GiB
Ukuran kumpulan data :
1.63 GiB
Cache otomatis ( dokumentasi ): Tidak
Perpecahan :
Membelah | Contoh |
---|---|
'test' | 19.962 |
'train' | 162.770 |
'validation' | 19.867 |
- Struktur fitur :
FeaturesDict({
'attributes': FeaturesDict({
'5_o_Clock_Shadow': bool,
'Arched_Eyebrows': bool,
'Attractive': bool,
'Bags_Under_Eyes': bool,
'Bald': bool,
'Bangs': bool,
'Big_Lips': bool,
'Big_Nose': bool,
'Black_Hair': bool,
'Blond_Hair': bool,
'Blurry': bool,
'Brown_Hair': bool,
'Bushy_Eyebrows': bool,
'Chubby': bool,
'Double_Chin': bool,
'Eyeglasses': bool,
'Goatee': bool,
'Gray_Hair': bool,
'Heavy_Makeup': bool,
'High_Cheekbones': bool,
'Male': bool,
'Mouth_Slightly_Open': bool,
'Mustache': bool,
'Narrow_Eyes': bool,
'No_Beard': bool,
'Oval_Face': bool,
'Pale_Skin': bool,
'Pointy_Nose': bool,
'Receding_Hairline': bool,
'Rosy_Cheeks': bool,
'Sideburns': bool,
'Smiling': bool,
'Straight_Hair': bool,
'Wavy_Hair': bool,
'Wearing_Earrings': bool,
'Wearing_Hat': bool,
'Wearing_Lipstick': bool,
'Wearing_Necklace': bool,
'Wearing_Necktie': bool,
'Young': bool,
}),
'identity': FeaturesDict({
'Identity_No': int64,
}),
'image': Image(shape=(218, 178, 3), dtype=uint8),
'landmarks': FeaturesDict({
'lefteye_x': int64,
'lefteye_y': int64,
'leftmouth_x': int64,
'leftmouth_y': int64,
'nose_x': int64,
'nose_y': int64,
'righteye_x': int64,
'righteye_y': int64,
'rightmouth_x': int64,
'rightmouth_y': int64,
}),
})
- Dokumentasi fitur :
Fitur | Kelas | Membentuk | Tipe D | Keterangan |
---|---|---|---|---|
FiturDict | ||||
atribut | FiturDict | |||
atribut/5_o_Clock_Shadow | Tensor | bodoh | ||
atribut/Arched_Eyebrows | Tensor | bodoh | ||
atribut/Menarik | Tensor | bodoh | ||
atribut/Bags_Under_Eyes | Tensor | bodoh | ||
atribut/Botak | Tensor | bodoh | ||
atribut/poni | Tensor | bodoh | ||
atribut/Bibir_Besar | Tensor | bodoh | ||
atribut/Hidung_Besar | Tensor | bodoh | ||
atribut/Hitam_Rambut | Tensor | bodoh | ||
atribut/Blond_Hair | Tensor | bodoh | ||
atribut/Buram | Tensor | bodoh | ||
atribut/Brown_Hair | Tensor | bodoh | ||
atribut/Bushy_Eyebrows | Tensor | bodoh | ||
atribut/Gemuk | Tensor | bodoh | ||
atribut/Double_Chin | Tensor | bodoh | ||
atribut/Kacamata | Tensor | bodoh | ||
atribut/Jenggot | Tensor | bodoh | ||
atribut/Gray_Hair | Tensor | bodoh | ||
atribut/Heavy_Makeup | Tensor | bodoh | ||
atribut/High_Cheekbones | Tensor | bodoh | ||
atribut/Laki-laki | Tensor | bodoh | ||
atribut/Mulut_Sedikit_Terbuka | Tensor | bodoh | ||
atribut/Kumis | Tensor | bodoh | ||
atribut/Narrow_Eyes | Tensor | bodoh | ||
atribut/No_Beard | Tensor | bodoh | ||
atribut/Oval_Wajah | Tensor | bodoh | ||
atribut/Pale_Skin | Tensor | bodoh | ||
atribut/Runcing_Hidung | Tensor | bodoh | ||
atribut/Receding_Hairline | Tensor | bodoh | ||
atribut/Rosy_Cheeks | Tensor | bodoh | ||
atribut/Cambang | Tensor | bodoh | ||
atribut/Tersenyum | Tensor | bodoh | ||
atribut/Rambut_Lurus | Tensor | bodoh | ||
atribut/Wavy_Hair | Tensor | bodoh | ||
atribut/Pakaian_Anting | Tensor | bodoh | ||
atribut/Memakai_Topi | Tensor | bodoh | ||
atribut/Memakai_Lipstik | Tensor | bodoh | ||
atribut/Memakai_Kalung | Tensor | bodoh | ||
atribut/Wearing_Dasi | Tensor | bodoh | ||
atribut/Muda | Tensor | bodoh | ||
identitas | FiturDict | |||
identitas/Identitas_No | Tensor | int64 | ||
gambar | Gambar | (218, 178, 3) | uint8 | |
landmark | FiturDict | |||
landmark/lefteye_x | Tensor | int64 | ||
landmark/mata kiri_y | Tensor | int64 | ||
landmark/leftmouth_x | Tensor | int64 | ||
landmark/leftmouth_y | Tensor | int64 | ||
landmark/hidung_x | Tensor | int64 | ||
landmark/hidung_y | Tensor | int64 | ||
landmark/mata kanan_x | Tensor | int64 | ||
landmark/mata kanan_y | Tensor | int64 | ||
landmark/rightmouth_x | Tensor | int64 | ||
landmark/rightmouth_y | Tensor | int64 |
Kunci yang diawasi (Lihat dokumen
as_supervised
):None
Gambar ( tfds.show_examples ):
- Contoh ( tfds.as_dataframe ):
- Kutipan :
@inproceedings{conf/iccv/LiuLWT15,
added-at = {2018-10-09T00:00:00.000+0200},
author = {Liu, Ziwei and Luo, Ping and Wang, Xiaogang and Tang, Xiaoou},
biburl = {https://www.bibsonomy.org/bibtex/250e4959be61db325d2f02c1d8cd7bfbb/dblp},
booktitle = {ICCV},
crossref = {conf/iccv/2015},
ee = {http://doi.ieeecomputersociety.org/10.1109/ICCV.2015.425},
interhash = {3f735aaa11957e73914bbe2ca9d5e702},
intrahash = {50e4959be61db325d2f02c1d8cd7bfbb},
isbn = {978-1-4673-8391-2},
keywords = {dblp},
pages = {3730-3738},
publisher = {IEEE Computer Society},
timestamp = {2018-10-11T11:43:28.000+0200},
title = {Deep Learning Face Attributes in the Wild.},
url = {http://dblp.uni-trier.de/db/conf/iccv/iccv2015.html#LiuLWT15},
year = 2015
}