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076222a11d0b896aa738d822cc23be3335b079d1c7d5b81880e43b843ab5d2a8 | Text | 15,855 | 266 | # Feature Extraction From Videos
This repository contains code and resources for extracting features from video files.
*Note:* This repository is a work in progress, with many aspects likely to undergo changes or updates.
---
The following features are currently implemented:
- Low-level visual features:
- [RGB-HSV... |
021fe9314277e42f1a36b80fe17ec8848dfa556dd2640118b9fc16a248992052 | Text | 15,888 | 202 | # <a name="top"></a>JuSpyce - a toolbox for flexible assessment of spatial associations between brain maps
[](https://zenodo.org/badge/latestdoi/506986337)
[](http://creative... |
26521e2592b9470e61943e74dea4a1b3d043ca0856c5631ff50eb05acb02182f | Text | 15,997 | 262 | # EMPRISE-analysis
**EMPRISE - EMergence of PRecISE numerosity representations in the human brain**
This code belongs to the [EMPRISE project](https://docs.google.com/document/d/1NplHdKIxAtiP9eXvE_wwQogRfu9pO_3gWW6BLUdUZak/edit) within the [Skeide Lab](https://www.skeidelab.com/) at the [Max Planck Institute for Huma... |
03c90967c3a62a4cb3f92f56c1cdabaa75160d15e0494e9c099f6ddd06916a57 | Text | 16,206 | 202 | # Leading Eigenvector Dynamics Analysis Toolbox - Matlab
This toolbox enables the neuroscience community to apply the Leading Eigenvector Dynamics Analysis (LEiDA) method to functional MRI data with the goal of understanding brain dynamics. Below you can find a set of instructions that will guide the application of th... |
94579c8adb2dcf23ae65a8238916e2ae1e54370835a18f76765cdd75cb289002 | Text | 16,218 | 211 | # ccfv3a-extended-atlas
# Overview
This repository contains the code developed for producing the CCFv3aBBP Nissl-based atlas, an extension of the Allen Institute's Common Coordinate Framework version 3 (CCFv3).
The project focuses on enhancing the anatomical correspondance between the Allen Reference Atlas (ARA) Nissl... |
e77c5bf0c9ed43ddf82f01cb5b4648d627313a623e278bf872b08742c19b1ab5 | Text | 16,310 | 277 | # MedicalPatchNet: A Patch-Based Self-Explainable AI Architecture for Chest X-ray Classification
[](https://python.org)
[](https://pytorch.org)
<!--TODO: Add [)
----
**NB:**
- Versions of Imagenette and Imagewoof with noisy labels are now available as CSV files that come ... |
4fd61fec9bd7204dcfe8045b87f2faeee6ca5f69eb28a97835c15aaa26b94f53 | Text | 16,538 | 323 | # Welcome to CLOOSE! <img src="Logo/Logo.png" width="500" title="CLOOSE" alt="CLOOSE" align="right" vspace = "100">
# 1. Overview
Pipeline for running BCI experiments and online analysis of 1 and 2 photon imaging data
Copyright (C) 2025 Massachusetts Institute of Technology
CLOOSE is currently under development and ... |
16b2dc38c5e25798e7efa08abf5e4b586acedd4bffe0a1513aca1cce5f14bced | Text | 16,553 | 326 |
# BrainLes-Preprocessing
[](https://pypi.org/project/brainles-preprocessing/)
[](https://pypi.python.org/pypi/brainles-preprocessing/)
[](https://github.com/argonne-lcf/ChemGraph/actions/workflows/tests.yml)
[](https://www.mathworks.com/products/matlab.html)
[](https://opensource.org/licenses/MIT)
A computational framework fo... |
f99f027ea7f3fda878b0472788e6283506dde021911fe73b3fc7abb3ca0ad854 | Text | 17,584 | 457 | # MReye-Seg
An open-access pipeline for MRI-based eye globe segmentation, landmark transformation, fiducial metric extraction, and globe shape (contour map) analysis.
**License:** MIT
**Author:** Ge Tang
---
## Table of Contents
1. [Overview](#overview)
2. [Prerequisites](#prerequisites)
3. [Data Preparation](#dat... |
a323c26422cd8943a1441b7b297eb998b9fe558f0bdc3eb411f3de44b177331b | Text | 17,904 | 522 | <div align="center">
# Source code for Geometric Transformers for Protein Interface Contact Prediction (ICLR 2022)
[](https://openreview.net/forum?id=CS4463zx6Hi) [](https://doi.org/10... |
96d6b5b49d1b94240d6e68caac705af90f9874bd36658227ddc7e2eca5a34c26 | Text | 17,919 | 256 | [](http://pepy.tech/project/opencv-python)
### Keep OpenCV Free
OpenCV is raising funds to keep the library free for everyone, and we need the support of the entire community to do it. [Donate to OpenCV on Github](https://github.com/sponsors/opencv) to show yo... |
92c982e111625e512df67000484ab57af9bc927656f7dfa9faa21fa3a9dce65d | Text | 18,002 | 133 | # Annotations for the [PI-CAI Challenge](https://pi-cai.grand-challenge.org/): Public Training and Development Dataset
---
### Updates
🚨 13 July 2026: We have released the [PI-RADS][PI-RADS] scores assigned during routine practice for each of the 1500 cases spanning the **Public Training and Development Dataset... |
10d54e4405c7ffd0a2e6a72de5285fcfedf8471fdb338cf0daf2e825ab6d52d0 | Text | 18,142 | 596 | # 1. Introduction
Spa3D is an algorithm that utilizes spatial pattern enhancement and graph convolutional neural network model to reconstruct 3D-based spatial structure from multiple spatially resolved transcriptomics (SRT) slides with 3D spatial coordinates.
Paper: 3D reconstruction of spatial transcriptomics w... |
bc3cfef5562deeffd2ecc5aadf2c46745ef08648df804597725dd5204ad4f478 | Text | 18,181 | 425 | ---
title: pyment-public
model_file: artifacts/sfcn-multi.onnx
license: cc-by-nc-4.0
pipeline_tag: image-classification
tags:
- neuroimaging
- multi-task
- structural t1 mri
- brain age
---
This repository contains pretrained predictive models for structural Magnetic Resonance Images from multiple publications.... |
fab3b8e5e715f628f84b93912b076629f4d3c49ac7ae0a327816fdb74565ff77 | Text | 18,315 | 299 | 
------------------------------------------------------
# Table of Contents
- [Introduction](#introduction)
- [System Requirements](#system-requirements)
- [Installation](#installation)
- [Notes](#notes)
- [Command Parameters](#command-parameters)
- [Examples](#examples)
- [Singl... |
6a0e70a566c1fe5dafd25cea62fe0bffc11cbbb3535ee5e327e1f977049d303f | Text | 18,997 | 265 | [](https://zenodo.org/badge/latestdoi/399400923)
## Introduction
Welcome to the project page of *VesselGraph* A Dataset and Benchmark for Graph Learning and Neuroscience. <br/>
Biological neural networks define human and... |
ad8cf512eead1106b38c8c2a87fb5f631f2133f5b9dab0d96f6522722b3e29e2 | Text | 19,182 | 444 | <div align="center">
[](https://arxiv.org/abs/2505.04672)
[![CC BY-NC-SA 4.0][cc-by-nc-sa-shield]][cc-by-nc-sa]
</div>
# Histo-Miner: Tissue Features Extraction Wi... |
d08aac96d28c060c1eee0cf585921415d1f591a4c2f88757b5005e3f2c821700 | Text | 19,214 | 447 |
<!-- Improved compatibility of back to top link: See: https://github.com/othneildrew/Best-README-Template/pull/73 -->
<a name="readme-top"></a>
<!--
*** Thanks for checking out the Best-README-Template. If you have a suggestion
*** that would make this better, please fork the repo and create a pull request
*** or simp... |
b722be07d65374ae898853c01089da3ff0cc32fe2caa0a7fa49a4b0a2b3f8704 | Text | 19,314 | 179 | # Memory consolidation in recurrent spiking neural networks
## Outline
This package serves to simulate recurrent spiking neural networks with calcium-based synaptic plasticity and synaptic tagging and capture.
The generic C++ program code and build scripts for specific simulations are located in the directory __simu... |
90b0547e64c9ce41efea0a5f4be5f1116427e98647330e75b3dedf90c3aa9c3f | Text | 19,403 | 477 | # Delocalization Score for MALDI-MSI
[](https://opensource.org/licenses/MIT)
[](https://www.python.org/downloads/)
[
## Introduction
**SEPIA** is a tool providing a graphical user interface to build data processing pipeline of quantitative susceptibility mapping (QSM) in Matlab.
Th... |
179fb06ff0b8239797e38d36072c64a5c2ef480714b505f4726e6c5712f885c5 | Text | 20,108 | 482 | # A deep learning framework for metabolite identification using enhanced MS/MS data and multidimensional molecular embeddings
A deep learning framework for metabolite identification using enhanced MS/MS data and multidimensional molecular embeddings is designed to process mass spectrometry data, perform predictions us... |
7e83be99617b2ebaeb0ab228daaa1af19959a216a44a6f219c1a7d2947c9caa2 | Text | 20,130 | 252 |
# Multi-Omics Factor Analysis v2 (MOFA+)
### Important notice: [MOFA v1](https://github.com/bioFAM/MOFA) is officially depreciated, please switch to [MOFA v2](https://github.com/bioFAM/MOFA2) even if you are not planning to use the novel functionalities.
## What is MOFA?
MOFA is a factor analysis model that provides... |
7be81b9f37c9b7cfcf17bd8ff31b7d0ae5d04b45d9b8730af6fe31d70219803e | Text | 20,573 | 486 |
<!-- README.md is generated from README.Rmd. Please edit that file -->
# MRlap <img src="inst/Figures/logo.png" align="right" height=180/>
<!---
# https://github.com/GuangchuangYu/hexSticker
library(hexSticker)
imgurl <- "inst/Figures/MRlap2.png"
sticker(imgurl,
package="", p_size=8, p_color="black",
... |
6c3569bf7afa33b9c069d9aa2d9eab3f6c7a8f437391a8ade414a298b06472bd | Text | 20,608 | 368 | # Learning to simulate realistic human diffuse reflectance spectra (mcmlnet)
[](https://www.python.org/downloads/)
[](https://opensource.org/licenses/MIT)
[:
## A machine learning-based method for predicting chromatin interactions from DNA sequences
### This document provides a brief intro of running models in ChINN for training and testing. Before launching any job, make sure you have properly downloaded the ChINN code and... |
a21c29eea090c26e2d7bd615a8d940cbaf8d4e4c83e03177b1da97e084d4b971 | Text | 20,784 | 252 | # High content in vitro survival assay of cortical neurons
Scripts file for the "High content in vitro survival assay of cortical neurons" paper on Bio-Protocol.
## Index
- [High content in vitro survival assay of cortical neurons](#high-content-in-vitro-survival-assay-of-cortical-neurons)
- [Index](#index)
- ... |
47f0dd7d7f960a8cf509b3388de91586cccec4fdd51e2ca7e56ef75d6630f65f | Text | 21,146 | 340 | # MRIsegmentation
[](https://zenodo.org/badge/latestdoi/457134654)
### Automatic MRI segmentation pipeline for consistent [FEM](https://en.wikipedia.org/wiki/Finite_element_method) and [BEM](https://en.wikipedia.org/wiki/Boundary_element_method) mesh creation from MRI scans... |
5488a9f29931fae6ca0218d8abe26fcb131d61af9a90572a45c40d4e0354ae29 | Text | 21,615 | 429 | [](https://github.com/lh3/minimap2/releases)
[](https://anaconda.org/bioconda/minimap2)... |
505fcc98f5b9a4b21260c192b79fe7ff6fe7cb339f1f7580dd2c69b8889c4d97 | Text | 22,132 | 476 | # Chinese Word Vectors 中文词向量
[中文](https://github.com/Embedding/Chinese-Word-Vectors/blob/master/README_zh.md)
This project provides 100+ Chinese Word Vectors (embeddings) trained with different **representations** (dense and sparse), **context features** (word, ngram, character, and more), and **corpora**. One can eas... |
d59649bba073c0a26f495e04e39e9f45c25e1e6551fc81ead29625d722123edf | Text | 22,634 | 573 | ..
This file is generated by setup.py
Image transformation, compression, and decompression codecs
===========================================================
Imagecodecs is a Python library that provides block-oriented, in-memory buffer
transformation, compression, and decompression functions for use in tifffile,
l... |
a80f3e391f32b7fb373881932415ab4ee7679df47da1e47d6883d9ae5e462a08 | Text | 24,106 | 413 | # <img src="img/permutools_logo.png">
[](https://github.com/mickcrosse/PERMUTOOLS/graphs/commit-activity)
[](https://uk.mathworks.com... |
7ede21c46c43b41504ee85eb292ddf327f36383131fd5a431dd91c844f750a4d | Text | 24,195 | 473 | # Lifespan BrainChart Project
* [Introduction](#introduction)
* [Datasets](#Datasets)
* [Lifespan curve estimates (and uncertainty)](#lifespan-curve-estimates--and-uncertainty-)
* [Scripts](#scripts)
+ [Example usage](#example-usage)
- [Obtaining population curves](#obtaining-population-curves)
... |
e28b9a41339b5a99fbdb0b8f6a9e97aeed343cf56137a89e07bff4772e54c8e3 | Text | 24,699 | 476 | # Cell Detection
[](https://pepy.tech/project/celldetection)
[](https://github.com/FZJ-INM1-BDA/celldetection/actions?query=workflow%3ATest)
[. Sensory sharpening and semantic prediction errors unify competing models of predictive processing in in human speech comprehensi... |
e0ecc86d39b8f7a394af4463575f8ccf151696c263fc30cda9731ad6b4bfe10c | Text | 25,124 | 300 | # Surface Morphometrics Pipeline
### Quantification of Membrane Surfaces Segmented from Cryo-ET or other volumetric imaging.
Author: __Benjamin Barad__/*<benjamin.barad@gmail.com>*, developed in close collabor... |
072e1153632bdd51a301f2a9fe7f507b5bcaee7c25b09b9b184683e1e06b95b6 | Text | 25,274 | 371 | <h1 align="center"> Ouroboros </h1>
<h3 align="center"> Directed Chemical Evolution via Navigating Molecular Encoding Space </h3>
<p align="center">
📃 <a href="https://doi.org/10.1002/advs.202513556" target="_blank">Paper</a> · 🤗 <a href="https://zhanglab.comp.nus.edu.sg/Ouroboros/" target="_blank">Model</a> · ... |
952cb0eb877a97f081e79a204ee3cf8c032dd6580995fec5fec5fb22e888cd5e | Text | 25,615 | 753 | Pipeline RNA-seq
===
This pipeline describes all the steps to perform transcriptomic analyses on RNA-seq libraries.
# Table of contents
- [Overview](#overview)
* [Read trimming](#read-trimming)
* [Read mapping](#read-mapping)
* [Assess strandeness of the library](#assess-strandeness-of-the-library)
+ [RSe... |
0d1edd32867ef0e72f7b794c1c15d62a08cce924e590b7410bd9c52bd1621958 | Text | 26,058 | 343 | # Kids First RNA-Seq Workflow V4
This is the Kids First RNA-Seq pipeline, which calculates gene and transcript isoform expression, detects fusions and splice junctions.
We have transitioned to this current version which upgrades several software components.
Our legacy workflow is still available as [v3.0.1](https://gi... |
76a682a66bce33737eec8adfee89ee52ef9fd26e9de8c39f88c75ad207c610f4 | Text | 26,796 | 408 | # rMATS turbo v4.4.0
[](https://github.com/Xinglab/rmats-turbo/releases/latest)
[](http... |
fe41fd2b0610db66c70e8acad880f30b28f475b95fdc69ce4fa3b6d5f6f5fa83 | Text | 26,911 | 406 | <br/>
<h1 align="center">ProtTrans</h1>
<br/>
<br/>
[ProtTrans](https://github.com/agemagician/ProtTrans/) is providing **state of the art pre-trained models for proteins**. ProtTrans was trained on **thousands of GPUs from Summit** and **hundreds of Google TPUs** using various **Transformer models**.
Have a look at... |
fcae0f7766ad6c0ec7f2d8c5a16096e88d9c1a3321acb4859d5edd4f150a91ef | Text | 28,120 | 303 | 
# NeMo 2.1 - Network Modification Tool
Predict brain network disruption from a lesion mask. Original concept described in [Kuceyeski 2013](https://pubmed.ncbi.nlm.nih.gov/23855491/).
**NEW!** Cloud interface for this tool can be used here: [https://kuceyeski... |
5a8887aaa2b85b971df72d9f25fe2cbb9bffa5518fab7f563dc787cdf156b8e2 | Text | 28,490 | 874 | [](https://www.mathworks.com/matlabcentral/fileexchange/59561-spider_plot)
[](https://matlab.mathworks.com/op... |
6ee09014c0882a0ceba3db0ff27d77ca5165df0843d86614003a036a555c0e06 | Text | 31,291 | 424 | [](https://doi.org/10.1093/nar/gkag145)
[](https://doi.org/10.5281/zenodo.15185168)
# Iterative Design of a NAND Hybrid Riboswitch by Deep Batch Bayesian Optimization
Thi... |
d6754b68da8fae70d2fb93b8100f41d55e2c0c262230c1017a053ad8154d85c1 | Text | 31,879 | 788 | jieba
========
“结巴”中文分词：做最好的 Python 中文分词组件
"Jieba" (Chinese for "to stutter") Chinese text segmentation: built to be the best Python Chinese word segmentation module.
- _Scroll down for English documentation._
特点
========
* 支持四种分词模式：
* 精确模式，试图将句子最精确地切开，适合文本分析；
* 全模式，把句子中所有的可以成词的词语都扫描出来, 速度非常快，但是不能解决歧义；
... |
a661cc0c5fee0f5904498577d695fb7a3e139d8f64a908b005022c5fba15278c | Text | 32,708 | 469 | # DTI Playground
DTI Playground is python based NIRAL pipeline software for diffusion MRI: preprocessing and quality control of
diffusion weighted images, fiber profile extraction and analysis, and atlas building. It ships a web UI
(DTIPlaygroundLab) and these command line tools:
| Tool | Purpose |
|---|---|
| [`dmri... |
cdd8ac84f44555750b8d61d04d46259ca9e2cb52b3d460b11a0323cad59e1a48 | Text | 32,898 | 875 | ..
This file is generated by setup.py
Read and write TIFF files
=========================
Tifffile is a comprehensive Python library to
(1) store NumPy arrays in TIFF (Tagged Image File Format) files, and
(2) read image and metadata from TIFF-like files used in bioimaging.
Image and metadata can be read from TIFF... |
5fe01b2fe422b0e7d16e770410dcaf03995f1b6e316f3c24e706e6a28cea791f | Text | 36,237 | 259 | # scATAC-benchmarking
Recent innovations in single-cell Assay for Transposase Accessible Chromatin using sequencing (scATAC-seq) enable profiling of the epigenetic landscape of thousands of individual cells. scATAC-seq data analysis presents unique methodological challenges. scATAC-seq experiments sample DNA, which, d... |
d485e86bb269b64c80ddd5b9e02d491d9aa8f1480f68c8a54ce3cd41420df4eb | Text | 36,734 | 259 | # TwiBot-22
This is the official repository of [TwiBot-22](https://twibot22.github.io/) @ NeurIPS 2022, Datasets and Benchmarks Track. This dataset is collected from the Twitter website before 2022.
### Introduction
TwiBot-22 is the largest and most comprehensive Twitter bot detection benchmark to date. Specifical... |
b4aec016ead1a42c648d677e28f89bf3f063ea752918be7c76dd9c2f8e82c5a7 | Text | 37,043 | 1,180 | 
# FLYNC - FLY Non-Coding gene discovery & classification
## TL;DR (Quick Start)
**Platform**: Linux AMD64/x86_64 only (ARM64/Apple Silicon users: see Docker + Rosetta instructions)
Install (conda recommended):
```bash
conda create -n flync -c RFCDSantos flync
conda activate flync
```
Setup... |
d132d68c9a5c958a7df15b6b82cc5470596caf824e6215f734e022fa30ac6265 | Text | 38,062 | 1,007 | # ChemGraph
<details>
<summary><strong>Overview</strong></summary>
**ChemGraph** is an agentic framework that can automate molecular simulation workflows using large language models (LLMs). Built on top of `LangGraph` and `ASE`, ChemGraph allows users to perform complex computational chemistry tasks, from structure... |
0e01c0e5ca7f1868e0c91406a9a0a8a9ea1e21f766fbc3c5d79f3d68e7ef259e | Text | 38,434 | 302 | <div align="center">
<p>
<a href="https://www.ultralytics.com/yolo/yolo27?utm_source=github&utm_medium=social&utm_campaign=yolo27-launch-2026&utm_content=banner" target="_blank">
<img width="100%" src="https://raw.githubusercontent.com/ultralytics/assets/main/yolov8/banner-yolov8.png" alt="Ultralytics YOLO ... |
6ed648555824c90de79d5898103be855f300534c405dd326144e6104da493663 | Text | 54,670 | 627 | # OpenPedCan-analysis
[](https://zenodo.org/badge/latestdoi/358689512)
The Open Pediatric Cancer (OpenPedCan) project is an open analysis effort that harmonizes pediatric cancer data from multiple sources, performs downstream cancer analyses on these data and provides them... |
9f87937c05b082202ee4d2bfd4bd5dc243eca94494c2d804eda988498042a70b | Text | 98,405 | 2,276 | If you use this software, please cite our work.
``` r
citation("Tjazi")
```
##
## To cite Tjazi in publications use:
##
## Bastiaanssen TFS, Quinn TP, Loughman A (2022) Treating Bugs as
## Features: A compositional guide to the statistical analysis of the
## microbiome-gut-brain axis. ... |
3d3cbaaf394061039da1595c5e30b4c8775332fae772868c6694b2251c66f209 | TypeScript | 89 | 3 | import CommandExplainer from "./CommandExplainer.vue";
export default CommandExplainer;
|
888d54bbbddff9b9c7628fcd5a8985a6bc4a5b2d20ffe526035e602e1378999a | TypeScript | 97 | 5 | // Copyright (C) CVAT.ai Corporation
//
// SPDX-License-Identifier: MIT
declare module '*.svg';
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# Timestamp file for custom commands dependencies management for cfunc_linerec_swig_compilation.
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fcafe3ccd9e50e1fd5228fac61915eb38ebca1b019370b19c6eb1271c29d1506 | TypeScript | 136 | 2 | # CMAKE generated file: DO NOT EDIT!
# Timestamp file for custom commands dependencies management for cfunc_lprecfp16_swig_compilation.
|
11a59f3da5c26e511e1b449579d90d1c575b6dd8ca23666919280bbaf41f7fbb | TypeScript | 137 | 2 | # CMAKE generated file: DO NOT EDIT!
# Timestamp file for custom commands dependencies management for cfunc_fourierrec_swig_compilation.
|
71de24761781d0aef4f64f93708b8ce1bb0fc5fe039c5cf4092cb83aa9b2567c | TypeScript | 137 | 2 | # CMAKE generated file: DO NOT EDIT!
# Timestamp file for custom commands dependencies management for cfunc_filterfp16_swig_compilation.
|
4c7e845095d0f193fc2d2ad9a2cbba284a8dc1706e9047ffc7fa1a48ab79f2fd | TypeScript | 138 | 2 | # CMAKE generated file: DO NOT EDIT!
# Timestamp file for custom commands dependencies management for CATERPillar_autogen_timestamp_deps.
|
c8c47e1bb57be30a6e13f76acdd4a95d427a48288d396bd0ce8a8d228d8688e6 | TypeScript | 138 | 2 | # CMAKE generated file: DO NOT EDIT!
# Timestamp file for custom commands dependencies management for cfunc_linerecfp16_swig_compilation.
|
86b60fec3d68121575b1dbb1d4414963239a1c30f0e0ffe0e4be585003d922ee | TypeScript | 141 | 2 | # CMAKE generated file: DO NOT EDIT!
# Timestamp file for custom commands dependencies management for cfunc_fourierrecfp16_swig_compilation.
|
480cfad27bb3ef430779b9c751de25d2f72da6aea9ded08739ea3a0446c14d65 | TypeScript | 149 | 8 | // Copyright (C) CVAT.ai Corporation
//
// SPDX-License-Identifier: MIT
export interface TimePeriod {
startDate: string;
endDate: string;
}
|
7056369b02b7addcc2a23b2eb1e61d4ed1669aa43ee7524cd7aa30affc82bd68 | TypeScript | 178 | 8 | // Copyright (C) 2020-2022 Intel Corporation
// Copyright (C) CVAT.ai Corporation
//
// SPDX-License-Identifier: MIT
import 'redux-thunk/extend-redux';
declare module '*.svg';
|
ed270bc8b0fb2672fb89390ddecc711596bdb7bd5257ec6571996bd7a4cac6ec | TypeScript | 183 | 6 | // Copyright (C) CVAT.ai Corporation
//
// SPDX-License-Identifier: MIT
export { fetchAndAssembleAudio } from './audio-data';
export type { AssembledAudioData } from './audio-data';
|
45b6f701785680f9cb4e64af018c325e69145eb6aa23be824e9a4b29753d8312 | TypeScript | 186 | 8 | import { defineConfig } from 'cypress'
export default defineConfig({
e2e: {
specPattern: 'cypress/e2e/**/*.{cy,spec}.{js,jsx,ts,tsx}',
baseUrl: 'http://localhost:4173'
}
})
|
0459cb99dabd8c238bef6a6b4b99af8e4d2175462eaca793853b7cb1e6aee996 | TypeScript | 191 | 8 | // https://docs.cypress.io/api/introduction/api.html
describe('My First Test', () => {
it('visits the app root url', () => {
cy.visit('/')
cy.contains('h1', 'You did it!')
})
})
|
361d3a06044b035a87fdc43bed0f3f2ed7801884a4277f7509abe4d9aed6edef | TypeScript | 192 | 6 | // Copyright (C) CVAT.ai Corporation
//
// SPDX-License-Identifier: MIT
export { default as ObjectState } from 'cvat-core/src/object-state';
export { ObjectType } from 'cvat-core/src/enums';
|
2e9cd2770e2304de6611e7ec14c5ad2017d61b8c4117a9d6256c6be99293d561 | TypeScript | 198 | 14 | // Copyright (C) CVAT.ai Corporation
//
// SPDX-License-Identifier: MIT
const dimensions = {
xs: 24,
sm: 24,
md: 24,
lg: 22,
xl: 20,
xxl: 16,
};
export default dimensions;
|
0b73a22434d4474beeec366ff2b6b7b152e7db25889145c1135b3eb7e5dcde46 | TypeScript | 206 | 8 | // Copyright (C) 2020-2022 Intel Corporation
// Copyright (C) CVAT.ai Corporation
//
// SPDX-License-Identifier: MIT
export function isDev(): boolean {
return process.env.NODE_ENV === 'development';
}
|
f75f28061ecd6ca1225b751fa060d5fe0f50e775bcbbf45d0f225e96d363ba72 | TypeScript | 244 | 9 | // Copyright (C) CVAT.ai Corporation
//
// SPDX-License-Identifier: MIT
export function handleDropdownKeyDown(event: React.KeyboardEvent): void {
if (['ArrowUp', 'ArrowDown'].includes(event.key)) {
event.stopPropagation();
}
}
|
f004e390ee2edbecd975eea36e55a46069144c194c6f37e0daa2ee8ac7b67723 | TypeScript | 247 | 7 | // Copyright (C) CVAT.ai Corporation
//
// SPDX-License-Identifier: MIT
export function anySearch<Type extends object>(obj: Type): boolean {
return Object.keys(obj).some((value: string) => value !== 'page' && (obj as any)[value] !== null);
}
|
30141420c358dce837848d32fa38c02281ae12e4f343a3e631dae84d5f571187 | TypeScript | 253 | 8 | // Copyright (C) CVAT.ai Corporation
//
// SPDX-License-Identifier: MIT
export function getTabFromHash(supportedTabs: string[]): string {
const tab = window.location.hash.slice(1);
return supportedTabs.includes(tab) ? tab : supportedTabs[0];
}
|
fdd4eaef5f9fe7c62dbd9c3e3e011f9065b2a6fb88a6f24ff3744112963a9d98 | TypeScript | 261 | 13 | import { createApp } from "vue";
import App from "./App.vue";
import router from "./router";
import ElementPlus from "element-plus";
import "element-plus/dist/index.css";
const app = createApp(App);
app.use(router);
app.use(ElementPlus);
app.mount("#app");
|
fa940d7523ee658cff8cc695ccbd34410c70eedf4d1f37e27757504a398aa55b | TypeScript | 280 | 7 | import { KeyMap } from './mousetrap-react';
export function subKeyMap(componentShortcuts: KeyMap, keyMap: KeyMap): KeyMap {
return Object.fromEntries(
Object.keys(componentShortcuts).filter((key) => !!keyMap[key]).map((key) => [key, keyMap[key]]),
) as KeyMap;
}
|
fd3e89498351357650a56636a1eae369d8121179c913caed1c33cf5056008a66 | TypeScript | 289 | 11 |
import { Routes } from '@angular/router';
import { ProjectPageComponent } from '@pages/projects/project-page.component';
/**
* Contains the routes for the components of the AppModule.
*/
export const routes: Routes = [
{ path: 'projects/:id', component: ProjectPageComponent }
];
|
b93d12a42d41f2178c6595018a287f74b02ca3bf6b5f06cfe7a82087aa4e9d4d | TypeScript | 330 | 11 | import { describe, it, expect } from 'vitest'
import { mount } from '@vue/test-utils'
import HelloWorld from '../HelloWorld.vue'
describe('HelloWorld', () => {
it('renders properly', () => {
const wrapper = mount(HelloWorld, { props: { msg: 'Hello Vitest' } })
expect(wrapper.text()).toContain('Hello Vitest'... |
c3435837b325d8392fe51ab4b46047b4522d4652b2d7489031d401086865b1a7 | TypeScript | 351 | 10 | // Copyright (C) CVAT.ai Corporation
//
// SPDX-License-Identifier: MIT
import type { CombinedState } from 'reducers';
export default function getHiddenZLayers(state: CombinedState): Set<number> {
const frame = state.annotation.player.frame.number;
return state.annotation.annotations.zLayer.hiddenByFrame.get(... |
e08783d71870b59dbac4834e7a391b362a8c0710a0382b67ff3c44743c0873e6 | TypeScript | 360 | 15 |
/**
* Represents the interface for the event that is triggered when the value of an input element changes.
*/
export interface HTMLInputEvent extends Event {
// #region Fields
/**
* Contains the target of the event, which is the input element that triggered the event.
*/
target: HTMLInputElem... |
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