Search Results for "script-api.jar" - Page 5

A jQuery plugin for extracting dominant colors from images and applying it to its parent. Install via bower. Then simply include jQuery and the script in your page, and invoke it like so. Instead of using an <img> element nested inside of parent element, AB supports grabbing the dominant color of a background image of a standalone element, then applying the corresponding dominant color as the background color of said element. Enable this functionality by adding a data property, data-ab-css-background to the element. selector String (default: 'img[data-adaptive-background="1"]') a CSS selector which denotes which images to grab/process. ...

...If you would like to add features to the library, you will have to change the code in src/ and then compile the library into the build/ directory. The compilation script simply concatenates files in src/ and then minifies the result.

A Python script doing basic computer vision that takes control the webcam and with OpenCV processes the video stream to capture what is told to do.

Redundancy due to cut-paste operations in text creates bias in machine learning for NLP. This module takes a directory and produces a subset of the files in that directory (in a list) with an upper bound on similarity between two files.

DictionaryReader is a research project; the aim of which is to create software that can automatically import data from mixed-script dictionaries. (For example, a Tibetan-English dictionary.)

WikiPrep is a Perl script for preprocessing Wikipedia XML dumps.

Zerorule is a lite rule engine/expert system that implements the RETE algorithm which can improve the speed of forward-chained rule system. It is written entirly in the powerful python language. it supplies both a script interpreter and simple CLI.

A Perl script that renames files of a config-file specified type (ex: mp3) to a user specified naming scheme. The script tries to resolve parts of the file name to specific variables (ex: title). Will prompt for duplicates and keep a log.

...It achieves a WER of 11.3% (or 9.01% with LM) on Common Voice test data, demonstrating high accuracy for a single-language ASR model. Inference can be done using HuggingSound or via a custom PyTorch script using Hugging Face Transformers and Librosa. Training scripts and evaluation methods are open source and available on GitHub. It is released under the Apache 2.0 license and intended for ASR tasks in Brazilian Portuguese.