Metadata-Version: 2.1
Name: JLpyUtils
Version: 0.1.2
Summary: Custom methodes for various data science, computer vision, and machine learning operations in python
Home-page: https://github.com/jlnerd/JLpyUtils.git
Author: John T. Leonard
Author-email: jtleona01@gmail.com
License: UNKNOWN
Description: # JLpyUtils
        Custom modules/classes/methods for various data science, computer vision, and machine learning operations in python
        
        ## Dependancies
        * General libraries distributed with Anaconda (pandas, numpy, sklearn, scipy, matplotlib, etc.)
        * image/video analysis:
            * cv2 (pip install opencv-python)
        * ML_models sub-package dependancies:
            * tensorflow or tensorflow-gpu
            * dill
            
        ## Installing & Importing
        In CLI:
        ```
        $ pip install -upgrade JLpyUtils
        ```
        After this, the package can be imported into jupyter notebook or python in general via the comman:
        ```import JLpyUtils```
        
        ## Modules Overview
        There are several modules in this package:
        ```
        JLpyUtils.summary_tables
        JLpyUtils.plot
        JLpyUtils.img
        JLpyUtils.video
        JLpyUtils.ML_models
        ```
        
        ```JLpyUtils.summary_tables``` and ```JLpyUtils.plot``` probably aren't that useful for most people, so we won't go into detail on them here, but feel free to check them out if you're curious.
        
        ### JLpyUtils.img
        The ```JLpyUtils.img``` module contains a number of functions related to image analysis, most of which wrap SciKit image functions in some way. The most interesting functions/classes are the ```JLpyUtils.img.auto_crop....``` and ```JLpyUtils.img.decompose_video_to_img()```. 
        
        The ```auto_crop``` class allows you to automatically crop an image using countours via the ```use_countours``` method, which essentially wraps the function ```skimage.measure.find_contours``` function. Alternatively, the ```use_edges``` method provides cropping based on the ```skimage.feature.canny``` function. Generally, I find the ```use_edges``` runs faster and gives more intuitive autocropping results.
        
        The ```decompose_video_to_img()``` is fairly self explanatory and basically uses cv2 to pull out and save all the frames from a video.
        
        ### JLpyUtils.video
        ...
        
        ### JLpyUtils.kaggle
        This module contains functions for interacting with kaggle. The simplest function is:
        ```
        JLpyUtils.kaggle.competition_download_files(competition)
        ```
        where ```competition``` is the competition name, such as  "home-credit-default-risk"
        
        
        
        
Platform: UNKNOWN
Description-Content-Type: text/markdown
