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- Examples
- =====================================
- Some examples are already available into documentation. You can find here some others and results of use of IPFML package.
- All examples below will use this picture.
- .. image:: _static/nature.jpg
- Metrics example
- --------------------
- Using **metrics** module you can convert image into Lab, XYZ, SVD...
- .. code:: python
-
- from PIL import Image
- from ipfml import metrics
- img_path = 'path/to/image_nature.jpg'
- img = Image.open(img_path)
-
- s = metrics.get_LAB_L(img)
- # convert result into PIL Image
- output = Image.fromarray(s)
- output.show()
- This is the generated output using only L chanel from Lab.
- .. image:: _static/nature_lab_l.png
- Processing example
- --------------------
- .. code:: python
-
- from PIL import Image
- from ipfml import processing
- img_path = 'path/to/image_nature.jpg'
- img = Image.open(img_path)
-
- low_bits_img = processing.rgb_to_grey_low_bits(img, 6)
-
- output = Image.fromarray(low_bits_img)
- output.show()
- Now we have picture information with only the 6 low bits values.
- .. image:: _static/nature_low_bits_6.png
- Noise filter example
- ---------------------
- .. code:: python
-
- from PIL import Image
- from ipfml.filters import noise as nf
- img_path = 'path/to/image_nature.jpg'
- img = Image.open(img_path)
- # set noise impact to 400
- # set same noise for each chanel
- noisy_image = nf.gaussian_noise(img, n=400, identical=True)
- output = Image.fromarray(noisy_image)
- output.show()
-
- Image result after applying gaussian noise on nature image.
- .. image:: _static/nature_gaussian_noise.png
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