Neural Style Transfer using VGG19
Project description
NST_VGG19
Neural Style Transfer using VGG19.
Original paper link.
VGG19 weights from torchvision.
Installation
pip install nst_vgg19
Usage
nst photo.jpg --style style-image.png --output result.png
Usage in python
from nst_vgg19 import NST_VGG19
# images must be Numpy arrays. Use np.array(pil_image)
style_image = load_image('style.png')
content_image_1 = load_image('img1.jpg')
content_image_2 = load_image('img2.png')
nst = NST_VGG19(style_image)
result_1 = nst(content_image_1)
result_2 = nst(content_image_2)
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
nst_vgg19-0.3.1.tar.gz
(7.1 kB
view details)
Built Distribution
Filter files by name, interpreter, ABI, and platform.
If you're not sure about the file name format, learn more about wheel file names.
Copy a direct link to the current filters
File details
Details for the file nst_vgg19-0.3.1.tar.gz.
File metadata
- Download URL: nst_vgg19-0.3.1.tar.gz
- Upload date:
- Size: 7.1 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/6.1.0 CPython/3.12.3
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
946394e0b00a7443e576f7dc800e25dee0f2caab29ab3d7061fca098a4202d16
|
|
| MD5 |
cbc01e6b542b9c00e9c663eacd2c0e59
|
|
| BLAKE2b-256 |
20a69d9b351f490104ebd748f0f3d76505c3c9a82a0311f3590af4d121ba1175
|
File details
Details for the file nst_vgg19-0.3.1-py3-none-any.whl.
File metadata
- Download URL: nst_vgg19-0.3.1-py3-none-any.whl
- Upload date:
- Size: 7.4 kB
- Tags: Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/6.1.0 CPython/3.12.3
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
0dddded1a2a3f2e2ac57103c63d4733435971ab81e2f0485a816768ebe409fab
|
|
| MD5 |
f4c667f885ef171bea8cb7cd23c82929
|
|
| BLAKE2b-256 |
2c54411818870c9a9f6b6b4304d4b007201ad5e4f07fc98e61b9ff580e6da5c8
|
