# Blind/Referenceless Image Spatial Quality Evaluator (BRISQUE)
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
```
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"description": "# Blind/Referenceless Image Spatial Quality Evaluator (BRISQUE) \n\nBRISQUE is a no-reference image quality score.\n\nA good place to know how BRISQUE works : [LearnOpenCV](https://learnopencv.com/image-quality-assessment-brisque/)\n\n\n## Installation\n\n```bash\npip install brisque\n```\n\n## Usage\n\n1. Trying to perform Image Quality Assessment on **local images** \n```python\nfrom brisque import BRISQUE\n\nobj = BRISQUE(url=False)\nobj.score(\"<Ndarray of the Image>\")\n```\n\n2. Trying to perform Image Quality Assessment on **web images** \n```python\nfrom brisque import BRISQUE\n\nobj = BRISQUE(url=True)\nobj.score(\"<URL for the Image>\")\n```\n\n### Example\n\n#### Local Image\n\n- Input\n```python\nfrom brisque import BRISQUE\nimport numpy as np\nfrom PIL import Image\n\nimg_path = \"brisque/tests/sample-image.jpg\"\nimg = Image.open(img_path)\nndarray = np.asarray(img)\n\nobj = BRISQUE(url=False)\nobj.score(img=ndarray)\n```\n- Output\n```\n34.84883848208594\n```\n\n#### URL\n\n- Input\n```python\nfrom brisque import BRISQUE\n\nURL = \"https://www.mathworks.com/help/examples/images/win64/CalculateBRISQUEScoreUsingCustomFeatureModelExample_01.png\"\n\nobj = BRISQUE(url=True)\nobj.score(URL)\n```\n- Output\n```\n71.73427549219988\n```\n\n\n",
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