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Image Curation Concepts

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This document covers the essential concepts for image data curation in NVIDIA NeMo Curator. These concepts assume basic familiarity with data science and machine learning principles.

Core Concept Areas

Image curation in NVIDIA NeMo Curator focuses on these key areas:

Data Loading

Core concepts for loading and managing image datasets

Data Processing

Concepts for embedding generation, classification, filtering, and deduplication

Data Export

Concepts for saving, exporting, and resharding curated image datasets

Infrastructure Components

The image curation concepts build on NVIDIA NeMo Curator’s core infrastructure components, which are shared across all modalities (text, image, video). These components include:

Memory Management

Optimize memory usage when processing large datasets partitioning batching monitoring

GPU Acceleration

Leverage NVIDIA GPUs for faster data processing cuda dali performance

Resumable Processing

Continue interrupted operations across large datasets checkpoints recovery batching