MultiClass Classification Computer Vision Project

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CgRLZxLNKI3O0etFRRsVII60UAf
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DQBPZRxyuwk4GKKqq7J0PNFAj
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DWPk7BnAGRSalDbRwxvbNlifmGapKAVOTQhManC81as5zby+ap5xT7BrdFl89A2Rxk1VYjzCU4XPAoBE0sjTzGRurHinMHjC7lINRROBIpYjg1c1C9Fz5a7QAg6igZFPdySQ+XkgYplrBLOjGNSQo5ppOTk9Kltrw2yyBQfmFAFdXZGBycj0p6uWk292PWoTukcnqT6UqM0cgJHINAFyeBrZ0DEENSFgwAJ4ps9yZyobt0p7QuIvM2nb64pAWbewS5tZXZ9pX7tZeCpq158sce1GwD1pkdvJPKsadW9aYiJNrSqG6FhmrGqW8ENwPs7EqR0zVWZXhlKOMEHmonc5B6mgB3BAJrSsjCLaQOAT71XexMdmlwX4btVdSQPagY7GGPoKKs2MSy3O2T7pFFBJ
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Defect
EIdfKXB7gUALeX7XEEcJHAqoEZvu5OOuO1IDz+NadjcxQW8isoLNQIhguXhXCHHrVdy0shPUmnOeTjpSRSGNw3BwaBiyxSQuBKhU06SZ3jCs2R6VLfXpvCuRytUSzYzg49aQF2GzkmhaRRwtVgzA4BwaliupIoWjViAajRGlkCqpLHsKYgRS8iqTyx61PfWZs3UbwwIzUBDRPgghgaSWRpDljmgBucjrV22t4HsneQ4ftUP2Ob7MLjb+7NQAkAgGgY7gZHocVLa484Z6Uy2iM0wizjPU0TRNBM0e7OD1FAFnUpISy+XjI64FUS3tQ3J69Kui1jbTzIWw+aAJbKeNLSSNlGT0NVQQp6cVXRypwelX7DynuVMo+WkAkMm11brjmlvbv7RNnHGKLooLpvKGFqu2MkkUANO4DJBxU6XjpCYlHymrUzRjTlAA31ncAigB8UTyvhFyTRVrT51imJ9qKAP
EaaBTu1GK0iAlHFIxxQpBFagGRSN1pTtoBFUgGmkJGKklYEDFQ5ya2QBjNN6VJwBTDzWiEHUUzoaceKTcCferQhNxzSY4NO7+1N7GqQDOlAy5pcZNNztNaIAYYNMbOacxLGkI496tAJtqN+nFPJ45pNuRVoQ1cYpH6Ujnb0pAcrzWgCA4pCaVulRk81okIYTzT84oKZFN6VdgBjTMU4U1jVpAITTCadnBphYVaQhCcUgbNL1pOlWkAGikyMUU7Af
FAhpAA6c1fgFsNOk8zmU9KjmsDHYrcF8knpVQEbcZpgKASOT0qeyZYrpGkwVHUVNp1nHcswdyABmqsqKkrKGyAeDSAfeyRvcO0YwpPQVACSR6VIqBnXP3c81a1C3gidDAcjHIoAluLxZbSKMLygoqpzswBRSEf
FAyTBUChpDtwKQyB1AoAyKAHJwoJqZZBtxVWRzjFSWsZlJyelAFiNlIORmmYG7pT1XAI7UiD5uaAJIdobkUS7RJuXpTWX5uDQOGA60gHLIFIyKKdMq7VOMUUAf
FFIR
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
NMJwaAxWmnk1ogY0HJpJMA8UpGKZjnmtUA1uKeApj56011wKiYnt0rRCAqBmmhh3qQYC81EcVogEfFIp2ijIFIx+WtEhIRjk008Um6kLZWtEgY5mygAqI0obAppPNaJEhmiiitESJRu4xRRQSFJRnikoFccDRSZooHc
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
NOJ4phUgUmTTsIUE9KKAKKLAf
NOOBTAcmtEhjcc044obApm6rQhGpAcU44xTOM1ogFZielMAKnNOBxQTwfSqQhhbdTMZpR1pxGBVIBpOBUeMmn9aTpWiRJGMqaOppzc0yrSAGBqNiaexzTetaJDExxQeKCcUgOTVWELu5p2KYynOaN3GKdgFORRRnNFFgP
NQWJpCcVSQhTHxnNMxgUu89KNuRmtEgGgc01zilIxTR8x5qkMOopGx2pWGKZ35rRIQh5oyOlBphGTWiQAetJkA0A01mGc1SQmKxBFREnNOzzQQDWiQgDHFGSTTTkdKA2OtVYBQeaXdnimNzzSA4OaLASYoppORRTsB
NQfpSYxWiQAaMnNL2zSEcVdgFK5oyRwKAcUuD2q0gDJPWhxgE0pBWkyTVpAIpz2pSowfWkCk8ik7VokIQqAKVR60AcUhOBitEhDXPOBTQKeqA8mhlA6VYMaxGMY5qPFPNJVpALTTg0UDGasBvApCQaJMUwEVaAUrxS5460ZBFMNXFCENID1zQTikOa0QCMRnim85pe+RQzcVaQhCajIOc04800tgVaQhCdtA5zTcljS421dgDpSA5pM5NKRiqSAO1NJpTzSEVVgFWjI3U3OKAc07AOyM0U0miiwH
NSvxTSQKM5NUhMTdSk8UEAUwmrSAQtRSiiqsB
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
NTiuatCGN14py89aBTq0QhpFJkUpOTQQM1pEBpNJnJpSuTSY5rRCAHFITzTsUgGTzVxAbilNKQB0phNaIQh5opaTFaIAOaTpRk0jHirQgyTTCaUd6RmrRAJuOKbgE80vWjpVoBhBU8UnXrTiSaaRgZq0AMvy0wHA5pwJxSFcitUgGbc5ppABxTuRTOtWJh3pD1oIpKoQZFMIGeKVjTetWAnU0hpSKbVoBG6UgFBOaaxwK0QAzUwnFJnmlJxWiQCFuKKaTRVWEf
NTnJFFhoWmMabnmnHkU0MXd8tFRg80UwP
NUi1aAaBxQKUnnFNatUhATxRuODQOTR1rRAIKRhilzgUhbNWgDPGKMcUD1ozVgJmkAJpwFC8GtEIYwwaB1pD8xNGCBWkUA5uBUZPNLkk0YyM1qkAqjINMcYNG4ikzmrSAQZJpZDgcUh4pN2etWkIM8UfWl20w8GrQhDTc08ciozVoBT0qPB3c08EZxRJjtVoBCRiozRnJpSe1WkAzcAaR+elKRzmm+wrRAJggUdqGpMZGasBCtMJwcCnFqZz1FUhMTaSaR+KXcRTSSTWiRImeOaQkY60h60wk1okMeWpoagDOeaYeKpICQmiosminYD
NUkznj0oGWh8+DnHtUlvOLe4Eo521NpflGVzKuQB0xVS4CC5YRjCE9KAEvrgXU2+qrBlIJyPrUrFUPI71bv7qK4t4UVACB1xQBB9sm+yfZ937v0qvDDJLu8tC20ZOKaSQxANW9OvBamUMuSwoArxPJFKXRipHFPLNLLz95qYxDszepzSxsUuFPdaYia5tpbNlEi4JHB9aXzCwUE0X9zJcAFznFMUZCmkUWoLIzW7SCULzgAiioxOyRBQxAooEf
NVcPC4Eg6802SR3B9BSADHHsznmimRwSPEXHQUUAf
NWyAAKM4pc001QAabjBp44NDEVaAjLc0jDvSHrQzZrQkbuxRtyM0YytJ90mtEAjDGaahGeacRu71GwxVxAGI5xTD707qQKJEwARWiEAIIpj+gpuTT4x3NVYAztWosk0sjZOajDHvVpCH5pM00txTc5q7AO5FOzgdajySKXNVYB+N1NI2mkDYNH3jTsMcAD3pCAKbypozmiwC5zRkUEcUzpTsApzQTRnNMPJ4qkgHZBpOc00dacaqwh2aKj34NFFgP
NaIBQRionxmnt8pxQFDVaEyPIIpCBinuoWoj0q0IXgCmE8U7+Coya1SAXNJnvTc0E1QCls03NA4oPNMQcGikop2Ef
NleRQBk9BUROQKRArShZOFzWhqkMUaxGJQuRzTAie9LWS24HAFFVCQcCigZ
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
No Defect
NtP5igcZGKAFljkt5DHJlZFNMeeSVgWJYjuaLq6N1N5rjDHrimkmKRQykZ6ZoAuXNlPawR3DMpRuoz0qv5zYxnI9KddX0ssAiYnaOgqKOCZ4DMkZMY6kUgL9laG9Rzv27apl5YpCueQcUlvctCW8tiN3UU5BJd3QjXG48nNMCWGTzriONzgMwBNW9St47C4URyFlI79qoSRNaymN+HU54NJI7ycs2fTJoAUz7hjoKKnudOkgt4py3DdcUUwP
Ntnl3Y29B60ATaaYUDmUA5HANFUFOO9FMVz
NxGIyMAHNURjHBzQBNa2j3W8pj5euTTY3ZGODz0pLe6a337R96mhy7lu7HNAE4csw55NWL21e3SNhIrBhyMdKpchyDkMD3qWaR3Ubm6UARO+VxU9nbwS28zSvtIHy002cptzMFyvtVVWIGM0wEduSKbEVEqbvuhhke1SwwfaZhEpAPqaZdW7Ws5jYqSB2oAvam9qxQQxhCPQ1nZzSk8Ank+9Xks4308XJJDHkAdBSaAdaXgt7SWPbkvRVIfd60UAf
NzQMk0jDaapALIo7U3otIc5yaU8itYgJnIplITiirQhUO000nJpCeaQHJq0iRMkGguTSt1qM8VdgFZTjNJuNBbK4qMtitYoB7DzOKjYFTgUbyKTdkmtEgDOTTWFKQRTD1xVpCE570oAx1oI4pucVVgAkjvTl45pgwetBPpVWAe2T0pgJU00MQaVjmmkA4yZ4puTSAAGgmnYTAtSDmkJFKDVAgNN6GnE00jmmMXoKaH+fBp1GB6U7AOJFFR0UrDP
O4Gmhdwo+7VAGMdKQNk04ENzil2dxTAAMdaT73TijaemaVQRVCYDpQBkUjZBoWqQClSO9SMSQMU1gMUKSRxVoBNpyM04DmnAc80mMmtBAxzz3pp6GlU4PPSlY4zxTEMyePSl60c4zSrjFWgG9MUHOacw5puMc1okIdggUbuKMk001rFALjNG7ApC2KAM1oIUc0uOM03OKXORiqQBinbcjFN296NxFaAB6YpBg8UcmgjHSrQCPx0poyTTiNxGaUjbVIAbGKiPJpxoGCOlaIQKRimvg9BR3oGA3NaJAMzg9Kk8zK4obaOlQnINVYQNyxNKrY7U4Yx701ulaJANbrTSxzS5pCRmrSGISTQRTCfmp24CrSEISRTRk0hOTRntVpCA8GmnrSk0xs1okMcRxTeg5NIScUFcp71aQC8Y60n0pnOKUU7AOApSabnApBzSsJjs07NMxSZxTsIUmikzRTsB
ODbTgLSAWz8sXOJfuDmm3oia6doeENQgbWYZzg0vVsdAe9MBq4PHetNrmL+zTbn72MfjUN7ZxQQxyRvycZFVwQWxQ9REaYUkHtVi0nENwr9qnsooJGk87sOKpyxqk5CfdzxQxkt7cefOXxVInpyasAZJz6U6+nilt41QAMnWkBCLp1hMQPyntVdAzOQBmgfPVm0lS2kZmGc00BFExjbcuQwpWdnclid1Dt5krNjAPSlAAoYErW08cIkZfkbvRUst600CxHgAYopAf
OHAFVZwizMsf3c8UK7IWGaFVmkA9TSAFGSCRRU1zCIGUBtwI7UUAf
OKaRmrQCY3UjLtozimk7sVogDqKCuKCuBTCatIAPWgYxRjNNPFaJAIwpABj3pcZ60jDaa0RIpGV461GTjrS5IPtQ2DVIQm4YqNjk0pIB4pdy45q0AwNimv8x4pxIJ4ptaIBjAg5oZyeKHbJxTGO2rSAXbxmo2wKfu4phGRmtEhAoXGaaW5pBxS5yeauwhVPHWmuOeKU4GabuzV2GN3YNSF8imkDFNp2GOzmgNikBwKaWJp2EOJzSZIpvzZobJHFOwDi1HOKYNwp+SadgAGlzTQtDDFFgFzRSYOKKLCP
OOlVYBxOKATioixzUqtxTsAhJophPNFKwH
OaaRWkUITFKabupa0QgxkA0EUo6UE1SQxmOaVutGaOprRCGUtKRTa1SAKWkoziqQDTTDmn0hxWqEA6U1hk5pSf50varGN3YqMtk4pzdaYPvVaJFIx0phYmnkg1Gx5rRIBeSKbnb0pd3FMzVJAIxJNGMCgtSbt1apANZqMcZpCpzSbu1WhDG4pMfLTmUmk7VaEiMr700AAdaeetNkBAwDVoBxxioyccUZwMHrSFc81aQCDk0Nimk4pM5rRIBc0UYFFVYD
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
OcdKaoxWiEIF280jN2p7HIpgjJ5rVCBV5zSZqTOBimbeM1ogEC5prcGlDY4pMbjWiATqaVlGOKRl200kjitEIaTg4oVQQTTmjJGc1HkgcVqhCMccUdqeib+tRP8pxWiARhiou9SdxmiQYPFaIQ0kAVGQTSscUHha1QDd+0Yph5BxSD5qXpWiQDB8pNMY5pzHJpmSDWqRIjAjFIWzSsSaYRirRQnWjdimhuKM5q0SxCcmmkc0Zw1G7mrQhKR0wKVqjaQmtkIQkZpKXjGabVpCuGaB1opveqJbHP96m0ZooELRSUUAf
OepoxxTBnvSM2DT5QH0U3gjNFFgP
OgB1g0Quw033QDRVYjaxX0NFAj
OhgG07c4+X1qxb3EluropHzinW9wsFtJGQCXGBkdqrIOvNIRLGrSNwMsT0FFLbyeTcIw7GigD
OinDAWtUrCYoPFJjPSkPenLnFaIQ0k9KTJIHNObOR603nitIgIBxQT1pRwppPerQhMc0lO65pM5rRAGM009RS4xRyatCGYJ607aMUu3ikPStUMjpVTNOC0u7aauwEbLtNNNOZ9zUNjFWhDOCvNRkYqSg8CtEJjFxg560ylPem1pEQGmueKRutHWtLANzSGlJpjGrQCOOM0zdTwy96uhLL7Lkf6z61XNYDOOTUbZDdalY4Y1GwzWiEITxTcUpHNHatUAzdtNMYkmlYmmAnNaITEPWjNHU0cVSQIXHvRTc0VVgP
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If you use this dataset in a research paper, please cite it using the following BibTeX:

                        @misc{
                            multiclass-classification-liqz8_dataset,
                            title = { MultiClass Classification Dataset },
                            type = { Open Source Dataset },
                            author = { Sagar },
                            howpublished = { \url{ https://universe.roboflow.com/sagar-xlg5z/multiclass-classification-liqz8 } },
                            url = { https://universe.roboflow.com/sagar-xlg5z/multiclass-classification-liqz8 },
                            journal = { Roboflow Universe },
                            publisher = { Roboflow },
                            year = { 2024 },
                            month = { apr },
                            note = { visited on 2024-11-30 },
                            }