Super Resolution
Image Super-Resolution using Deep Convolutional Neural Networks.
Installing
Install and update using pip:
pip3 install super-resolution
Or
git checkout https://github.com/fengwang/super_resolution.git
cd super_resolution
python3 -m pip install -e .
Usage
Command line:
super_resolution INPUT_IMAGE_PATH OUTPUT_IMAGE_PATH_4X
Using Python API:
# uncomment the follow three lines if you have a Nvidia GPU but you do not want to enable it.
#import os
#os.environ["CUDA_DEVICE_ORDER"] = "PCI_BUS_ID"
#os.environ["CUDA_VISIBLE_DEVICES"]=''
from super_resolution import cartoon_upsampling_4x
large_image = cartoon_upsampling_4x( './a_tiny_input_image.png', './a_4x_larger_output_image.png' )
from super_resolution import cartoon_upsampling_8x
large_image = cartoon_upsampling_8x( './a_tiny_input_image.png', './a_8x_larger_output_image.png' )
Details
- The super resolution model is inherited from
Ledig C, Theis L, Huszár F, et al. Photo-realistic single image super-resolution using a generative adversarial network, Proceedings of the IEEE conference on computer vision and pattern recognition. 2017: 4681-4690. - The training images are downloaded from Konachan (NSFW).
License
- BSD
1 maintainer
Metadata
1 maintainer
Release files for super-resolution 0.2.4
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| super_resolution-0.2.4.tar.gz | 28.3 MB | Without provenance | Details |
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| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| super_resolution-0.2.4-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 28.3 MB
Release files / super_resolution-0.2.4.tar.gz
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| Size | 28.3 MB |
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Release files / super_resolution-0.2.4-py3-none-any.whl
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| Tags | Python 3 |
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