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import './index.scss' ;
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import FaIcon from '@components/FaIcon' ;
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- import { Col , Modal , Row } from 'rsuite' ;
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+ import { Col , Modal , Row , Tooltip , Whisper } from 'rsuite' ;
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import Btn from '@src/Components/BTN/BTN' ;
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import { useEffect , useState } from 'react' ;
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import useWindow from '@src/Tools/Hooks/useWindow' ;
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+ import prize from '@assets/Images/projects/prize.png' ;
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import useDashboard from '@src/Tools/Hooks/useDashboard' ;
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import nava from '@assets/Images/projects/nava/nava.png' ;
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import dmeta from '@assets/Images/projects/dmeta/dmeta.png' ;
@@ -114,15 +115,25 @@ const Section3 = () => {
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alt = 'logo'
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/>
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</ div >
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+ < div className = 'grant-row' >
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+ { project ?. grant ?. map ( ( grant : any , i : any ) => (
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+ < Whisper
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+ trigger = 'hover'
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+ controlId = 'control-id-hover'
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+ key = { i }
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+ placement = 'top'
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+ speaker = { < Tooltip > { grant } </ Tooltip > } >
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+ < img src = { prize } alt = 'grant-prize' />
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+ </ Whisper >
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+ ) ) }
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+ </ div >
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< div className = 'second-row row' >
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{ project ?. coming_soon && (
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- < div >
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- < div className = 'second-cell cell' >
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- < div className = 'link' >
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- < FaIcon fa = 'l-hourglass-clock' className = 'text-primary w-7 mr-2' />
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- < span > Coming Soon</ span >
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- </ div >
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+ < div className = 'second-cell cell' >
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+ < div className = 'link' >
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+ < FaIcon fa = 'l-hourglass-clock' className = 'text-primary w-7 mr-2' />
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+ < span > Coming Soon</ span >
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</ div >
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</ div >
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) }
@@ -270,6 +281,7 @@ const projects = [
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github : 'https://github.com/sepandhaghighi/pycm' ,
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forkPage : 'https://github.com/sepandhaghighi/pycm/forks' ,
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starsPage : 'https://github.com/sepandhaghighi/pycm/stargazers' ,
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+ grant : [ 'PSF Development Grant 2022' , 'NLnet Grant 2022' , 'Trelis AI Grant 2024' ] ,
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description : `PyCM is a multi-class confusion matrix library written in Python that supports both input data vectors and direct matrix, and is a proper tool for post-classification model evaluation that supports most classes and overall statistics parameters. PyCM is the swiss-army knife of confusion matrices, targeted mainly at data scientists that need a broad array of metrics for predictive models and accurate evaluation of a large variety of classifiers.` ,
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} ,
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@@ -279,6 +291,7 @@ const projects = [
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dark_logo : pymiloDark ,
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light_logo : pymiloLight ,
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account : 'openscilab' ,
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+ grant : [ 'PSF Development Grant 2024' ] ,
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github : 'https://github.com/openscilab/pymilo' ,
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// webLink: 'https://github.com/openscilab/pymilo',
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forkPage : 'https://github.com/openscilab/pymilo/fork' ,
@@ -315,6 +328,7 @@ const projects = [
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dark_logo : samilaDark ,
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light_logo : samilaLight ,
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account : 'sepandhaghighi' ,
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+ grant : [ 'IPFS Grant 2022' ] ,
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github : 'https://github.com/sepandhaghighi/samila' ,
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webLink : 'https://www.samila.site' ,
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forkPage : 'https://github.com/sepandhaghighi/samila/forks' ,
@@ -327,6 +341,7 @@ const projects = [
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dark_logo : artDark ,
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light_logo : artLight ,
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account : 'sepandhaghighi' ,
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+ grant : [ 'PSF Development Grant 2024' ] ,
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github : 'https://github.com/sepandhaghighi/art' ,
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webLink : 'https://www.ascii-art.site' ,
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forkPage : 'https://github.com/sepandhaghighi/art/forks' ,
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