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- IPFML
- =====
- Image Processing For Machine Learning package.
- How to use ?
- ------------
- To use, simply do::
- >>> from PIL import Image
- >>> import ipfml as iml
- >>> img = Image.open('path/to/image.png')
- >>> s = iml.metrics.get_SVD_s(img)
- Modules
- -------
- This project contains modules.
- - **img_processing** : *PIL image processing part*
- - fig2data(fig): *Convert a Matplotlib figure to a 3D numpy array with RGB channels and return it*
- - fig2img(fig): *Convert a Matplotlib figure to a PIL Image in RGB format and return it*
- - **metrics** : *Metrics computation of PIL image*
- - get_SVD(image): *Transforms PIL Image into SVD*
- - get_SVD_s(image): *Transforms PIL Image into SVD and returns only 's' part*
- - get_SVD_U(image): *Transforms PIL Image into SVD and returns only 'U' part*
- - get_SVD_V(image): *Transforms PIL Image into SVD and returns only 'V' part*
- - **ts_model_helper** : *contains helpful function to save or display model information and performance of tensorflow model*
- - save(history, filename): *Function which saves data from neural network model*
- - show(history, filename): *Function which shows data from neural network model*
- All these modules will be enhanced during development of the project
- How to contribute
- -----------------
- This git project uses git-flow_ implementation. You are free to contribute to it.
- .. _git-flow : https://danielkummer.github.io/git-flow-cheatsheet/
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