Metadata-Version: 1.1
Name: synthetic_datasets
Version: 0.1.9
Summary: synthetic datasets for benchmarking AI and machine learning
Home-page: https://github.com/synthetic-datasets/synthetic-datasets
Author: Dave MacDonald
Author-email: dave@torontoai.org
License: UNKNOWN
Description: 
        
        # Synthetic Datasets
        
        ## Installation
        
        ```
        pip install synthetic-datasets
        ```
        
        ## Datasets
        
        * NoiseCircle
        
        
        ### NoiseCircle
        
        A generator of square images, by default 64x64, with static noise and a circle
        with noisy pixels in the image at a random location and with a random size.
        
        Each result from the generator is a square numpy matrix of type float32
        
        Example use::
        
        ```python
            from synthetic_datasets import NoiseCircle
        
            nc = NoiseCircle(batch_size=32, dim=64)
            for samples, labels in nc:
        
                // samples  is a (32, 64, 64) numpy array of noise circle images
                // labels   is a dict with three keys, "X", "Y", and "R".
                //          These represent the X, Y, and RADIUS (in pixels) of the circle in the image.
                //          Each key holds a numpy array of shape (32,)
        ```
        
        
        
        ## Licence
        MIT
        
        
        ## More info
        - https://github.com/synthetic-datasets/synthetic-datasets
        - https://www.meetup.com/Toronto-AI/
        - http://torontoai.org/
        - A Toronto AI initiative
        
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
