# PyBRISQUE
An implementation of BRISQUE (Blind/Referenceless Image Spatial Quality
Evaluator) in Python from the paper: ["No-Reference Image Quality Assessment
in the Spatial Domain"](https://ieeexplore.ieee.org/document/6272356/).
## Installation
The package is in PyPI so you can install it simply by this command:
```pip install --process-dependency-links pybrisque```
## Usage
Initialize once:
```
brisq = BRISQUE()
```
and get the BRISQUE feature or score many times:
```
brisq.get_feature('/path')
brisq.get_score('/image_path')
```
## Limitations
This implementation is heavily adopted from the original Matlab
implementation in [here](https://github.com/dsoellinger/blind_image_quality_toolbox/tree/master/%2Bbrisque). There is one catch though, the bicubic interpolation when resizing image in
Matlab and OpenCV is a bit different as explained in [here](https://stackoverflow.com/questions/26823140/imresize-trying-to-understand-the-bicubic-interpolation). For now, it uses ```nearest``` interpolation
which gives the most similar output with the original implementation.
Comparing with Matlab original implementation on reference images of TID 2008:

And the absolute differences' stat is as follows:
```
{'min': 0.17222238726479588,
'max': 16.544924728934404,
'mean': 3.9994322498322754,
'std': 3.0715344507521416}
```
An implementation of BRISQUE (Blind/Referenceless Image Spatial Quality
Evaluator) in Python from the paper: ["No-Reference Image Quality Assessment
in the Spatial Domain"](https://ieeexplore.ieee.org/document/6272356/).
## Installation
The package is in PyPI so you can install it simply by this command:
```pip install --process-dependency-links pybrisque```
## Usage
Initialize once:
```
brisq = BRISQUE()
```
and get the BRISQUE feature or score many times:
```
brisq.get_feature('/path')
brisq.get_score('/image_path')
```
## Limitations
This implementation is heavily adopted from the original Matlab
implementation in [here](https://github.com/dsoellinger/blind_image_quality_toolbox/tree/master/%2Bbrisque). There is one catch though, the bicubic interpolation when resizing image in
Matlab and OpenCV is a bit different as explained in [here](https://stackoverflow.com/questions/26823140/imresize-trying-to-understand-the-bicubic-interpolation). For now, it uses ```nearest``` interpolation
which gives the most similar output with the original implementation.
Comparing with Matlab original implementation on reference images of TID 2008:

And the absolute differences' stat is as follows:
```
{'min': 0.17222238726479588,
'max': 16.544924728934404,
'mean': 3.9994322498322754,
'std': 3.0715344507521416}
```
Metadata
Release files for pybrisque 1.0
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| pybrisque-1.0.tar.gz | 136.4 kB | Details |
Release files / pybrisque-1.0.tar.gz
| Download URL | pybrisque-1.0.tar.gz |
|---|---|
| Size | 136.4 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
15878426e7d7576232cc4282c2de30194fff4af4a04162738d112054e81a4f8b
|
|
BLAKE2b-256 checksum How to use checksums |
0b382bafdc76e506df9e6ea6ca636e1fe291f2b40119c1c347f4a240d8ee3300
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/1.11.0 pkginfo/1.4.2 requests/2.19.1 setuptools/40.2.0 requests-toolbelt/0.8.0 tqdm/4.25.0 CPython/3.6.5
|