# Downloading data

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If you have questions or feedback about the download tools provided by IDC, please reach out via our [forum](https://discourse.canceridc.dev/) - we are very interested in hearing your feedback and suggestions!
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IDC supports a variety of interfaces for fetching individual images, cohorts (groups of images), or portions of images, using desktop application, command-line interface, or programmatic API. These interfaces are covered in the subsequent pages. You should select the specific approach to accessing IDC data depending on your requirements.

* Download **directly from** [**IDC Portal**](https://learn.canceridc.dev/data/downloading-data/idc-portal): no prerequisites other than a Chrome web browser!
* [idc-index](https://learn.canceridc.dev/data/downloading-data/downloading-data#command-line-or-programmatic-download-idc-index-python-package) interface: **command-line and Python API interface** to download images corresponding to the specific patient/study/series, or a cohort defined by a manifest
* [3D Slicer](https://learn.canceridc.dev/data/downloading-data/downloading-data) interface: **desktop application** to download images corresponding to the specific patient/study/series, or a cohort defined by a manifest
* [s5cmd](https://learn.canceridc.dev/data/downloading-data/downloading-data-with-s5cmd): **command-line interface** to download images for a cohort defined by a manifest (unlike `idc-index`, does not organize downloaded images into folders corresponding to IDC data model hierarchy)
* [DICOMweb](https://learn.canceridc.dev/data/downloading-data/dicomweb-access) interface: **REST API interface** to access both metadata and pixel data at the granularity of image frames/tiles
* [Directly loading DICOM objects from Google Cloud or AWS in Python](https://learn.canceridc.dev/data/downloading-data/direct-loading): **Python API interface** to access both metadata and pixel data at the granularity of image frames/tiles