Search Libraries

PyNLPl, pronounced as 'pineapple', is a Python library for Natural Language Processing. It contains various modules useful for common, and less common, NLP tasks. PyNLPl can be used for basic tasks s…

The Insight Toolkit (ITK) is an open-source, cross-platform toolkit for N-dimensional scientific image processing, segmentation, and registration. Segmentation is the process of identifying and class…

Example: You can see some demo data using the modulees for SMS, filenamedatestamps, Twitter, RSS, imap, phonecalls, and git. The easiest way of installing Memacs is by using `pip`: This gets you the …

Invenio Framework is like a Swiss Army knife of battle-tested, safe and secure modules providing you with all the features you need to build a trusted digital repository.

In the era of Deep Learning, developing robust machine learning solutions to problems in biomedical imaging requires access to large amounts of annotated training data, objective comparisons of state…

Zenodo, a CERN service, is an open dependable home for the long-tail of science, enabling researchers to share and preserve any research outputs in any size, any format and from any science. Copyrigh…

An advanced web path brute-forcer Choose one of these installation options: dirsearch allows you to pause the scanning progress with CTRL+C, from here, you can save the progress (and continue later),…

Sacred is a tool to help you configure, organize, log and reproduce experiments. It is designed to do all the tedious overhead work that you need to do around your actual experiment in order to: Sacr…

Email is a challenge to visualize. The Newman tool and accompanying analytics contain a processing component, email analytics, visualization and discovery tools. Newman can quickly analyze and explor…

Install the API client: Then, to authenticate, either: The following example will setup the client and predict concepts on an image from a URL, using the general model The response is a JSON structur…

Tool for managing data-deduplication within extant compressed archive files, with a heavy focus on Manga/Comic-book archive files. It maintains a database of hashes for all files it scans, and actual…

A Python library with the following principles and goals: With Axelrod you: The library is tested on Python versions 3.8, 3.9, and 3.10. The simplest way to install is: To install from source: The fo…

Python Script for 'searching' and 'downloading' hundreds of Google images to the local hard disk! This program lets you download tons of images from Google. Please do not download or use any image th…

Run all: To update later on, just run that command again. Alternatively, to update while avoiding the confirmation prompt: To sync dev-setup to your local home directory without Git, run the followin…

Information about my cybersecurity experiences ... This repository is divided by the next sections: Bibliography

This is an open-source python package for the extraction of Radiomics features from medical imaging. With this package we aim to establish a reference standard for Radiomic Analysis, and provide a te…

This project can be used to build a searchable index of images that can scale to millions of images. It provides a RESTful API for querying the index to find similar images in less than a second. The…

See Also: repos which contains hundreds more scripts and programs for Cloud, Big Data, SQL, NoSQL, Web and Linux. Hari Sekhon Cloud & Big Data Contractor, United Kingdom List all programs: Run an…

Alexander Liu Very fast -- 4 to 10 times faster when processing big data. If the json data file is valid: If the json data file is invalid: No multi-threads And it works. And it works.

To be able to use this library, you need to enable Google Custom Search API, generate API key credentials and set a project: After setting up your Google developers account and project you should hav…

In addition to the built-in package documentation there are vignettes with more information on getting started and additional examples:

Once you're up and running, read these two (short) sections of the documentation to get a feel for what image-match is capable of:

Once you're up and running, read these two (short) sections of the documentation to get a feel for what image-match is capable of:

Once you're up and running, read these two (short) sections of the documentation to get a feel for what image-match is capable of:

Some of the formats require additional dependency packages, you can install these packages as follows: You can apply styles to specific cells by using style filters. Style filters will be written as …

Implementations are for learning purposes only. They may be less efficient than the implementations in the Python standard library. Use them at your discretion.