> 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 Data Loading

> Load image data for curation using tar archives with distributed processing and GPU acceleration

Load image data for curation using NeMo Curator. The primary supported format is tar archives containing JPEG images, which enables efficient distributed processing of large-scale image datasets.

## How it Works

NeMo Curator's image data loading uses a pipeline-based approach optimized for large-scale, distributed curation workflows:

1. **File Partitioning**: `FilePartitioningStage` distributes `.tar` files across workers for parallel processing.

2. **High-Performance Reading**: `ImageReaderStage` uses NVIDIA DALI to accelerate image loading, decoding, and batching on GPU with CPU fallback.

3. **Tar Archive Format**: Processes sharded `.tar` archives containing JPEG images (other file types are ignored during loading).

4. **Batch Processing**: Images are processed in `ImageBatch` objects containing decoded images, metadata, and processing results.

The result is a stream of `ImageBatch` objects ready for embedding, classification, and filtering in downstream pipeline stages.

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## Options

#### [Tar Archive Pipeline](/curate-images/load-data/tar-archives)

Load and process JPEG images from tar archives using `FilePartitioningStage` and `ImageReaderStage` for scalable distributed curation.