Metadata-Version: 2.1
Name: caispp
Version: 0.2.4
Summary: High level ML library used in CAIS++ Curriculum
Home-page: https://github.com/zanedurante/caispp
Author: Zane Durante
Author-email: zanedurante@gmail.com
License: UNKNOWN
Description: # Caispp
        
        ## About
        This package allows for high level ML model creation.  It uses Keras with a Tensorflow backend, and was originally created to be used for the curriculum of USC's CAIS++ (Center for AI in Society, Student Branch).  
        
        ## Use Cases
        The package currently supports Image Classification.
        
        ## Installation
        To install run `pip install caispp`.  This package uses Tensorflow 2.0. 
        
        ## Example usage
        
        You can see a jupyter notebook with ouputs in the `examples/` directory.  The notebook runs the code below:
        
        ```
        from caispp import ImageDataset, ImageClassifier, Path
        
        path = Path('example_dataset/') # Path to dataset
        dataset = ImageDataset(path, show_distribution=True)
        
        classifier = ImageClassifier(dataset)
        classifier.train(epochs=10)
        
        classifier.show_history()
        
        classifier.test(show_distribution=True)
        ```
        ## Dataset directory structure
        ```
        ├── example_dataset         
        │   ├── test
        │   │   ├── class1      # Directory with images of class1
        │   │   ├── class2      # Directory with images of class2
        │   │   └── ...       
        │   ├── train
        │   │   ├── class1      # Directory with images of class1
        │   │   ├── class2      # Directory with images of class2
        │   │   └── ...         
        │   ├── valid           # Optional validation set    
        │   │   ├── class1
        │   │   ├── class2
        │   │   └── ... 
        └──  
        ```
        Each of the `test/`, `train/`, and `valid/` directories contain subdirectories for each class.  In those subdirectories, put the images files of that class.  
        
        ## Build the package
        
        To build the package run the `build.sh` script in the directory.  The output is stored in `dist/`.
        
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Description-Content-Type: text/markdown
