April 2025
Intermediate to advanced
690 pages
19h 37m
Portuguese (Portugal, Brazil)
Content preview from Ciência de dados 3D com Python
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Capítulo 7. Criar aplicações analíticas 3D
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Nós, , procuramos constantemente formas de traduzir dados 3D brutos em informações acionáveis. Embora os métodos de análise tradicionais forneçam informações valiosas, muitas vezes não têm a flexibilidade e a interatividade necessárias para uma exploração aprofundada dos dados. As visualizações estáticas e a manipulação manual de dados prejudicam a tua capacidade de segmentar, rotular e extrair conhecimentos de conjuntos de dados 3D complexos de forma eficaz. Seria útil se dispusesses de ferramentas dinâmicas para visualizar e manipular caraterísticas em tempo real.
Imagina analisar uma nuvem de pontos de uma antiga fábrica, com o objetivo de isolar máquinas específicas e compreender o seu contexto espacial. Os métodos convencionais podem envolver uma tediosa segmentação manual ou a criação de scripts, limitando a nossa capacidade de explorar rapidamente diferentes combinações de caraterísticas e limiares. Precisamos de uma aplicação interactiva para visualizar caraterísticas como planaridade, linearidade e diferenças de elevação. Isto permitiria a definição de limiares que podem ser utilizados para estruturar o nosso conjunto de dados com base no feedback em tempo real .
O nosso objetivo neste capítulo é conceber um método de limiarização interativo que nos permita extrair seletivamente segmentos com base em limiares ...
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