Metadata-Version: 2.1
Name: ThreadedFileLoader
Version: 1.0.0.8
Summary: UNKNOWN
Home-page: https://QuantumNovice.github.io/ThreadedFileLoader
Author: QuantumNovice
Author-email: portabl3lapy@gmail.com
License: MIT
Description: # Threaded File Loader
        
        <a href='https://github.com/QuantumNovice/ThreadedFileLoader'> Github: ThreadedFileLoader</a>
        
        Multithreaded Python package for faster file loading in machine learning.
        
        # Installation
        `pip install ThreadedFileLoader`
        
        # Usage:
        ## Loading Image Files:
        ```python
        from ThreadedFileLoader.ThreadedFileLoader import *
        
        instance = ThreadedImageLoader("path_to_/*.jpg")
        instance.start_loading()
        images = instance.loaded_objects
        print(len(images))
        print(images[0].shape)
        ```
        
        ## Loading Text Files:
        ```python
        from ThreadedFileLoader.ThreadedFileLoader import *
        
        instance = ThreadedTextLoader("path_to_/*.txt")
        instance.start_loading()
        images = instance.loaded_objects
        ```
        
        ## Loading Custom File Formats
        Threaded FileLoader can load different file types.
        This examples shows how the `ThreadedTextLoader` class
        overloads the `ThreadedFileLoader` class to load text files.
        
        ```python
        from ThreadedFileLoader.ThreadedFileLoader import *
        
        class ThreadedTextLoader(ThreadedFileLoader):
            def object_loader(self, path):
              with open(path) as afile:
                data = afile.readlines()
                return data
        
        instance = ThreadedTextLoader("path_to_/*.txt")
        instance.start_loading()
        texts = instance.loaded_objects
        ```
        
        # Machine Learning Example
        ## Loading Dataset
        
        
        ```Python
        import numpy as np
        
        from ThreadedFileLoader.ThreadedFileLoader import *
        from sklearn.cluster import KMeans
        
        
        instance = ThreadedImageLoader("path_to_dataset/*.jpg")
        instance.start_loading()
        images = instance.loaded_objects
        images = np.array(images)
        images = images.reshape(len(images), -1)
        
        kmeans = KMeans(n_clusters=10, random_state=0).fit(images)
        
        print(kmeans.labels_)
        
        ```
        
Platform: UNKNOWN
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.7
Requires-Python: >=3.6
Description-Content-Type: text/markdown
