Metadata-Version: 2.4
Name: brisque
Version: 0.0.17
Summary: Image Quality
Home-page: https://github.com/rehanguha/brisque
Author: Rehan Guha
Author-email: rehanguha29@gmail.com
License: Apache-2.0
Keywords: quality,svm,image,maths
Classifier: Operating System :: OS Independent
Classifier: License :: OSI Approved :: MIT License
Classifier: Natural Language :: English
Classifier: Programming Language :: Python
Classifier: Topic :: Software Development :: Libraries :: Python Modules
Classifier: Topic :: Scientific/Engineering
Classifier: Intended Audience :: Developers
Requires-Python: >=2.7
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: numpy
Requires-Dist: scikit-image
Requires-Dist: scipy
Requires-Dist: opencv-python
Requires-Dist: libsvm-official
Requires-Dist: requests
Dynamic: author
Dynamic: author-email
Dynamic: classifier
Dynamic: description
Dynamic: description-content-type
Dynamic: home-page
Dynamic: keywords
Dynamic: license
Dynamic: license-file
Dynamic: requires-dist
Dynamic: requires-python
Dynamic: summary

# Blind/Referenceless Image Spatial Quality Evaluator (BRISQUE) 

[![DOI](https://zenodo.org/badge/DOI/10.5281/zenodo.11104461.svg)](https://doi.org/10.5281/zenodo.11104461)


BRISQUE is a no-reference image quality score.

A good place to know how BRISQUE works : [LearnOpenCV](https://learnopencv.com/image-quality-assessment-brisque/)


## Installation

```bash
pip install brisque
```

## Usage

1. Trying to perform Image Quality Assessment on **local images** 
```python
from brisque import BRISQUE

obj = BRISQUE(url=False)
obj.score("<Ndarray of the Image>")
```

2. Trying to perform Image Quality Assessment on **web images** 
```python
from brisque import BRISQUE

obj = BRISQUE(url=True)
obj.score("<URL for the Image>")
```

### Example

#### Local Image

- Input
```python
from brisque import BRISQUE
import numpy as np
from PIL import Image

img_path = "brisque/tests/sample-image.jpg"
img = Image.open(img_path)
ndarray = np.asarray(img)

obj = BRISQUE(url=False)
obj.score(img=ndarray)
```
- Output
```
34.84883848208594
```

#### URL

- Input
```python
from brisque import BRISQUE

URL = "https://www.mathworks.com/help/examples/images/win64/CalculateBRISQUEScoreUsingCustomFeatureModelExample_01.png"

obj = BRISQUE(url=True)
obj.score(URL)
```
- Output
```
71.73427549219988
```


