Metadata-Version: 2.1
Name: imshowtools
Version: 0.3.1
Summary: imshowtools contains simplified imshow functions to show multiple images and with other options
Home-page: https://github.com/saravanabalagi/imshowtools
Author: Saravanabalagi Ramachandran
Author-email: saravanabalagi@hotmail.com
License: MIT
Description: # imshowtools
        
        ![](https://img.shields.io/pypi/v/imshowtools)
        ![](https://img.shields.io/pypi/wheel/imshowtools)
        ![](https://img.shields.io/pypi/l/imshowtools)
        
        This library lets you view images in Jupyter notebooks in a much simpler and intuitive way. Ships with a better 'imshow' function with Multi Images, Smart Wrap and BGR support!.
        
        ## Installation
        
        To install `imshowtools`, simply do
        
        ```py
        pip install imshowtools
        ```
        
        ## Usage
        
        Import `imshow` from `imshowtools` and use it like:
         
        ```py
        from imshowtools import imshow
        imshow(lenna)
        ```
        
        ![lenna](example/lenna_rgb.png)
        
        ## Advanced Usage
        
        #### Colorspaces
        
        OpenCV lover? `imshowtools` can also handle `cv2`'s BGR images
        
        ```py
        import cv2
        cv2image = cv2.imread('lenna.png')
        imshow(cv2image)
        ```
        ![lenna](example/lenna_bgr.png)
        
        ```py
        imshow(cv2image, mode='BGR')
        ```
        ![lenna](example/lenna_rgb.png)
        
        #### Show Multiple Images
        ```py
        imshow(image_1, image_2, image_3)
        ```
        
        #### Show Multiple Images from List
        
        ```py
        imshow(*[my_image_list])
        ```
        
        Example:
        
        ```py
        mnist = tf.keras.datasets.mnist
        
        (x_train, y_train), (x_test, y_test) = mnist.load_data()
        x_train, x_test = x_train / 255.0, x_test / 255.0
        [x_train.shape, y_train.shape], [x_test.shape, y_test.shape]
        imshow(*x_train[:25])
        ```
        
        ![mnist-25](example/mnist_25.png)
        
        Multiple images with colorspace:
        
        ```py
        imshow(*x_train[:100], cmap='gray')
        ```
        
        ![mnist-100](example/mnist_100.png)
        
        #### Single Row and Single Column
        
        ```py
        imshow(*x_train[:16], cmap='binary', rows=1)
        ```
        ![mnist-row](example/mnist_row.png)
        
        ```py
        imshow(*x_train[:4], cmap='binary', columns=1)
        ```
        ![mnist-column](example/mnist_column.png)
        
        #### Smart Wrapping / Custom Rows and Columns
        
        `imhow` chooses the optimal layout:
        
        * Have 6 images? You get 2x3
        * Have 12 images? You get 3x4
        * Have 20 images? You get 4x5
        
        You can also choose to manually control how many rows and columns you
        ```py
        imshow(*my_image_array, rows=3, columns=4)
        ```
        
        #### Namespaces
        If you do not want to use `imshow` directly in your app (maybe you have another function named imshow), you shall use it like
        
        ```py
        import imshowtools
        imshowtools.imshow(your_image)
        ```
        
        or if you like to use a custom namespace
        ```py
        import imshowtools as my_namespace
        my_namespace.imshow(your_image)
        ```
        
        ## Uninstall
        
        To uninstall `imshowtools`,
        
        ```py
        pip uninstall imshowtools
        ```
        
        ## Contributing
        
        Pull requests are very welcome.
        
        1. Fork the repo
        1. Create new branch with feature name as branch name
        1. Check if things work with a jupyter notebook
        1. Raise a pull request
        
        ## Licence
        
        Please see attached [Licence](LICENCE)
Platform: UNKNOWN
Classifier: Development Status :: 4 - Beta
Classifier: Topic :: Software Development :: Libraries
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Description-Content-Type: text/markdown
