Skip to main content

Custom methodes for various data science, computer vision, and machine learning operations in python

Project description

JLpy Utils Package

Custom modules/classes/methods for various data science, computer vision, and machine learning operations in python


  • 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


$ pip install -upgrade JLpy_utils_package

After this, the package can be imported into jupyter notebook or python in general via the comman: import JLpy_utils_package as JLutils

Modules Overview

There are several modules in this package:


JLutils.summary_tables and JLutils.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.


The JLutils.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 JLutils.img.auto_crop.... and JLutils.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.



This module contains functions for interacting with kaggle. The simplest function is:


where competition is the competition name, such as "home-credit-default-risk"

Project details

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Files for JLpy-utils-package, version 2.0.5
Filename, size File type Python version Upload date Hashes
Filename, size JLpy_utils_package-2.0.5.tar.gz (30.4 kB) File type Source Python version None Upload date Hashes View
Filename, size JLpy_utils_package-2.0.5-py3-none-any.whl (61.7 kB) File type Wheel Python version py3 Upload date Hashes View

Supported by

AWS AWS Cloud computing Datadog Datadog Monitoring Facebook / Instagram Facebook / Instagram PSF Sponsor Fastly Fastly CDN Google Google Object Storage and Download Analytics Huawei Huawei PSF Sponsor Microsoft Microsoft PSF Sponsor NVIDIA NVIDIA PSF Sponsor Pingdom Pingdom Monitoring Salesforce Salesforce PSF Sponsor Sentry Sentry Error logging StatusPage StatusPage Status page