https://github.com/mazzzystar/make-celeba-hq
Supposed you've downloaded CelebA & CelebA-HQ dataset, and want to get HQ images from them.
https://github.com/mazzzystar/make-celeba-hq
celeba celeba-hq
Last synced: about 1 month ago
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Supposed you've downloaded CelebA & CelebA-HQ dataset, and want to get HQ images from them.
- Host: GitHub
- URL: https://github.com/mazzzystar/make-celeba-hq
- Owner: mazzzystar
- Created: 2019-05-25T08:43:56.000Z (about 6 years ago)
- Default Branch: master
- Last Pushed: 2019-08-21T02:09:20.000Z (almost 6 years ago)
- Last Synced: 2024-04-23T00:11:06.333Z (about 1 year ago)
- Topics: celeba, celeba-hq
- Language: Python
- Homepage:
- Size: 798 KB
- Stars: 20
- Watchers: 3
- Forks: 3
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
Awesome Lists containing this project
README
# make-CelebA-HQ
Python script to download and create the celebA-HQ dataset.
To get the celebA-HQ dataset, you need to
a) download the celebA dataset. [Google Drive](https://drive.google.com/drive/folders/0B7EVK8r0v71pWEZsZE9oNnFzTm8) or [Baidu Drive](https://pan.baidu.com/s/1eSNpdRG#list/path=%2F).
b) download celebA-HQ dataset. [Google Drive](https://drive.google.com/drive/folders/0B4qLcYyJmiz0TXY1NG02bzZVRGs)
c) do some processing to get the HQ images `make_HQ_images.py`.
# Usage
1.Clone the repository
```
git clone https://github.com/mazzzystar/make-CelebA-HQ.git
cd make-CelebA-HQ
```
2.Install necessary packages
* Install miniconda https://conda.io/miniconda.html
* Create a new environement
```
conda create -n celebaHQ python=3
source activate celebaHQ
```
* Install the packages
```
conda install jpeg tqdm requests pillow urllib3 numpy cryptography scipy
pip install opencv-python==3.4.0.12 cryptography==2.1.4
```
* Install 7zip (On Ubuntu)
```
sudo apt-get install p7zip-full
```
3.Download and Unzip CelebA & CelebA-HQ
Downloading CelebA: [Large-scale CelebFaces Attributes (CelebA) Dataset](http://mmlab.ie.cuhk.edu.hk/projects/CelebA.html)
Downloading CelebA-HQ. Google Drive: https://drive.google.com/drive/folders/0B4qLcYyJmiz0TXY1NG02bzZVRGs
```bash
# there are 14 file inside. (img_celeba.7z.001, ... img_celeba.7z.014)
cd CelebA/Img/img_celeba.7z
# merge .7z files into a single file.
cat img_celeba.7z.0** > img_celeba.7z
# unzip the .7z file
7z x img_celeba.7z
# move the unzipped folder 'img_celeba' under 'Img/' path
mv img_celeba ../
cd CelebA-HQ/
# unzip the zips of deltas00000.zip, deltas00001.zip, .. into one file
unzip '*.zip' -d combined
# move the "image_list.txt" to current github repo folder.
```
4.Make sure your datasets/landmark/scripts under current Github repo folder.
```
make-CelebA-HQ---CelebA
| |___Anno
| | |___list_landmarks_celeba.txt
| | |___...
| |
| |___Img
| |___ img_celeba/
|
|_CelebA-HQ
| |
| |_Combined/
|
|-make_HQ_images.py
|-image_list.txt
|_README.md
```
5.Run the scripts
```
python make_HQ_images.py ./
```
where `./` is the directory where you wish the data to be saved. this script will take a few hours to run depending on your internet connection and your CPU power. The final HQ images will be saved as `.npy` files in the `./celebA-HQ/combined/` folder.
6.Sample of loading image
```python
import numpy as np
from PIL import Image
img = np.load('imgHQ15858.npy')
img = img.reshape(3, 1024, 1024)
print(img.shape)
img = np.transpose(img, (1, 2, 0))
print(img.shape)
im = Image.fromarray(img)
im.show()
```
# Sources
This code is inspired by these files
* https://github.com/nperraud/download-celebA-HQ
# Note
The code above use `jpeg=8d` version of `md5` for checking hash value, however I could get the expected value for `jpeg=9b` version, so I simply ignore the md5 checking. Tell me if you think somewhere wrong.