No Dataset? No Problem. How I Curated a Custom AI Dataset From Instagram & Pinterest to Build a Pose Suggester
The article discusses the author's journey in creating a custom AI dataset for a Pose Suggester application. Faced with the absence of a suitable dataset, the author sourced images from Instagram and Pinterest while ensuring diversity and clarity. The process involved automated labeling and data augmentation to enhance the dataset for effective machine learning training.
- ▪The author needed a dataset for an AI-powered Pose Suggester but found none available.
- ▪Images were sourced from Instagram and Pinterest, focusing on diverse body types and environments.
- ▪An automated labeling pipeline was created to efficiently extract joint coordinates from images.
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try { if(localStorage) { let currentUser = localStorage.getItem('current_user'); if (currentUser) { currentUser = JSON.parse(currentUser); if (currentUser.id === 3933227) { document.getElementById('article-show-container').classList.add('current-user-is-article-author'); } } } } catch (e) { console.error(e); } SHAIK TAUFEEQ AHMAD Posted on May 19 No Dataset? No Problem. How I Curated a Custom AI Dataset From Instagram & Pinterest to Build a Pose Suggester #ai #python #programming #architecture When you start a new Machine Learning project, you pray there’s a clean, ready-to-use dataset on Kaggle or Hugging Face.
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