> For clean Markdown of any page, append .md to the page URL.
> For a complete documentation index, see https://docs.nvidia.com/nemo/curator/llms.txt.
> For AI client integration (Claude Code, Cursor, etc.), connect to the MCP server at https://docs.nvidia.com/nemo/curator/_mcp/server.

# Image Curation Concepts

> Essential concepts for image data curation including loading, processing, and export with GPU acceleration

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](/about/concepts/image/data/loading)

Core concepts for loading and managing image datasets

#### [Data Processing](/about/concepts/image/data/processing)

Concepts for embedding generation, classification, filtering, and deduplication

#### [Data Export](/about/concepts/image/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](/reference/infra/memory-management)

Optimize memory usage when processing large datasets

#### [GPU Acceleration](/reference/infra/gpu-processing)

Leverage NVIDIA GPUs for faster data processing

#### [Resumable Processing](/reference/infra/resumable-processing)

Continue interrupted operations across large datasets