Metadata-Version: 2.1
Name: image-to-numpy
Version: 1.0.0
Summary: Load an image into a numpy array with proper Exif orientation handling
Home-page: https://github.com/ageitgey/image_to_numpy
Author: Adam Geitgey
Author-email: ageitgey@gmail.com
License: MIT
Description: # image_to_numpy
        
        Load an image file into a numpy array - while automatically rotating the image based on 
        Exif orientation. Prevents upside-down and sideways images! 
        
        ```
        import image_to_numpy
        
        img = image_to_numpy.load_image_file("my_file.jpg")
        ```
        
        The image is automatically rotated into the correct orientation if the image contains Exif orientation metadata.
        Otherwise, it is loaded normally.
        
        From there, you can pass the numpy array to any Python library that works with images
        in numpy array format, like face_recognition, Keras, etc.
        
        ## Installation
        
        You can install from [PyPI](https://pypi.org/project/image_to_numpy/):
        
            pip install image_to_numpy
        
        ## Usage
        
         ```python
        import image_to_numpy
        
        img = image_to_numpy.load_image_file("my_file.jpg")
        ```
        
        Your image is loaded - with the correct orientation! 
        
        By default, the image array is returned as a numpy array 
        with 3-channels of 8-bit RGB data.
        
        You can control the output format by passing in an optional `mode` parameter:
        
         ```python
        import image_to_numpy
        
        img = image_to_numpy.load_image_file("my_file.jpg", mode="RGB")
        
        # Supported modes:
        #  1 (1-bit pixels, black and white, stored with one pixel per byte)
        #  L (8-bit pixels, black and white)
        #  RGB (3x8-bit pixels, true color)
        #  RGBA (4x8-bit pixels, true color with transparency mask)
        #  CMYK (4x8-bit pixels, color separation)
        #  YCbCr (3x8-bit pixels, color video format)
        #  I (32-bit signed integer pixels)
        #  F (32-bit floating point pixels)
        ```
        
        
        If you have matplotlib installed, here's a quick way to show your image
        on the screen:
        
        ```python
        import matplotlib.pyplot as plt
        import image_to_numpy
        
        img = image_to_numpy.load_image_file("my_file.jpg")
        
        plt.imshow(img)
        plt.show()
        ```
        
        ## Thanks
        
        - EXIF test images used in the unittests created by Dave Perrett / @daveperrett
          - https://github.com/recurser/exif-orientation-examples
        
Platform: UNKNOWN
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 3
Description-Content-Type: text/markdown
