Data Management and Curation

STEP 1: Register or Import Data into Encord

You can either upload local data or register cloud data in Encord.

Registering your cloud data with Encord only references the files. Your data is not stored on Encord servers.

Create a Cloud Integration

Select your cloud provider.

AWS Integration

GCP Integration

Azure Integration

OTC Integration

Wasabi Integration

Oracle Integration

Direct Access Integration

Create a Folder

You must create a folder in Index to store your files.

Navigate to Files under the Index heading in the Encord platform.
Click the + New folder button to create a new folder. A dialog to create a new folder appears.

Give the folder a meaningful name and description.
Click Create to create the folder. The folder is listed in Files.

Create JSON or CSV for Registration

To register cloud storage files with Encord, you must create a JSON or CSV file specifying the files you want to register.

Find helpful scripts for creating JSON and CSV files for the data registration process here.

All types of data (videos, images, image groups, image sequences, and DICOM) from a private cloud are added to a Dataset in the same way, by using a JSON or CSV file. The file includes links to all images, image groups, videos and DICOM files in your cloud storage.

For a list of supported file formats for each data type, go here

Encord supports file names up to 300 characters in length for any file or video for upload.

For detailed information about the JSON file format used for import go here.

The information provided about each of the following data types is designed to get you up and running as quickly as possible without going too deeply into the why or how. Look at the template for each data type, then the examples, and adjust the examples to suit your needs.

If skip_duplicate_urls is set to true, all object URLs that exactly match existing images/videos in the dataset are skipped.

AWS JSON

Videos

BEST PRACTICE: If you want to use Index or Active with your video data, we STRONGLY RECOMMEND using key frames, custom metadata, and custom embeddings. When specifying key frames set the sampling_rate to 0. This imports only the first frame and any key frames you specify in the video. This can significantly speed up the import of your data into Active and Index and help you to focus on only data you identify as critical.

The following table provides some guidance for the examples provided after the table.

Title	Description
Template	Provides the proper JSON format to import videos into Encord. This template provides examples from the most basic to the most complex.
Data	Imports videos into Encord. Why would I do this? You ONLY want to add labels and classifications to your data. You DO NOT want to use Index or Active.
Key Frames	Imports videos with an Encord title and specifies key frames (frames of interest) for Active and Index. Why would I do this? You ONLY want to see frames that you deem critical in Active and Index. You want to significantly improve the time to import videos into Active and Index. `config` is optional when specifying key frames for Active and Index: Specifying a `sampling_rate` of `0` only imports the first frame and all key frames of your video into Active and Index. `"config": { "sampling_rate": "<samples-per-second>", "keyframe_mode": "frame" or "seconds", },` If `config` is not specified, the `sampling_rate` is 1 frame per second, and the `keyframe_mode` is `frame`.
Custom Metadata	Imports videos with an Encord title, specifies key frames (frames of interest), and custom metadata for Active and Index. Why would I do this? Importing custom metadata allows you to filter your data in Active and Index to make it easier to find the data you want to focus on. This speeds up creating Collections and by extension Datasets. Specifying key frames means you ONLY want to see frames that you deem critical in Active and Index AND you want to significantly improve the time to import videos into Active and Index. `config` is optional when specifying key frames for Active and Index: Specifying a `sampling_rate` of `0` only imports the first frame and all key frames of your video into Active and Index. `"config": { "sampling_rate": "<samples-per-second>", "keyframe_mode": "frame" or "seconds", },` If `config` is not specified, the `sampling_rate` is 1 frame per second, and the `keyframe_mode` is `frame`.
Embeddings	Imports videos with an Encord title, specifies key frames (frames of interest), custom metadata, and custom embeddings for Active and Index. This example includes the following custom metadata types: boolean, varchar, datetime, uuid, number. Why would I do this? Importing custom embeddings allows you to use scatter plots to examine your data AND allows you to use similarity search and natural language searches. Index supports embedding dimensions 1 to 4096, while Active supports embedding dimensions 1 to 2000. Importing custom metadata allows you to filter your data in Active and Index to make it easier to find the data you want to focus on. This speeds up creating Collections and by extension Datasets. Specifying key frames means you ONLY want to see frames that you deem critical in Active and Index AND you want to significantly improve the time to import videos into Active and Index. `config` is optional when specifying custom embeddings for Active and Index: Specifying a `sampling_rate` of `0` only imports the first frame and all key frames of your video into Active and Index. `"config": { "sampling_rate": "<samples-per-second>", "keyframe_mode": "frame" or "seconds", },` If `config` is not specified, the `sampling_rate` is 1 frame per second, and the `keyframe_mode` is `frame`. Refer to our documentation for more information about Index with Custom Metadata, Index with Custom Embeddings, Active with Custom Metadata and Active with Custom Embeddings.
Video Metadata	Imports videos with the videoMetadata flag. When the videoMetadata flag is present in the JSON file, we directly use the supplied metadata without performing any additional validation, and do not store the file on our servers. To guarantee accurate labels, it is crucial that the metadata you provide is accurate.

{
  "videos": [
    {
      "objectUrl": "cloud-path-to-your-video-1"
    },
    {
      "objectUrl": "cloud-path-to-your-video-2",
        "videoMetadata": {
          "fps": frames-per-second,
          "duration": duration-in-seconds,
          "width": frame-width,
          "height": frame-height,
          "file_size": file-size-in-bytes,
          "mime_type": "MIME-file-type-extension"
        }
      }
    {
      "objectUrl": "cloud-path-to-your-video-3",
      "title": "title-for-your-video-3",
      "clientMetadata": {"metadata-1": "value", "metadata-2": "value"}

    },
    {
      "objectUrl": "cloud-path-to-your-video-4",
      "title": "title-for-your-video-4",
      "clientMetadata": {
          "metadata-1": "value", "metadata-2": "value",
          "$encord": {
              "frames": ["<frame-number-1>","<frame-number-2>","<frame-number-3>"]
            }
        }
    },
    {
        "objectUrl": "cloud-path-to-your-video-5",
        "title": "title-for-your-video-5",
        "clientMetadata": {
            "metadata-1": "value", "metadata-2": "value",
            "$encord": {
                "frames": {
                    "<frame-number-or-seconds>": {
                        "<my-embedding>": [1.0, 2.0, 3.0]
                    },
                    "<frame-number-or-seconds>": {
                        "<my-embedding>": [1.0, 2.0, 3.0]
                    }
                }
             }
          }
    },
    {
      "objectUrl": "cloud-path-to-your-video-6",
        "title": "title-for-your-video-5",
        "clientMetadata": {
            "metadata-1": "value", "metadata-2": "value",
            "$encord": {
                "config": {
                    "sampling_rate": "<samples-per-second>",
                    "keyframe_mode": "frame" or "seconds",
                },
                "frames": {
                    "<frame-number-or-seconds>": {
                        "<my-embedding>": [1.0, 2.0, 3.0]
                    },
                    "<frame-number-or-seconds>": {
                        "<my-embedding>": [1.0, 2.0, 3.0]
                    }
                }
            }
        }
    }
  ],
  "skip_duplicate_urls": true
}

Audio Files

The following is an example JSON file for uploading two audio files to Encord.

Template: Imports audio files with an Encord title, and with custom metadata. Custom metadata only appears in the Encord UI in Active and Index as an option to filter your data.
Audio Metadata: Imports one audio file with the audiometadata flag. When the audiometadata flag is present in the JSON file, we directly use the supplied metadata without performing any additional validation, and do not store the file on our servers. To guarantee accurate labels, it is crucial that the metadata you provide is accurate.

{
  "audio": [
    {
      "objectUrl": "<object url_1>"
    },
    {
      "objectUrl": "<object url_2>",
      "title": "my-custom-audio-file-title.mp3",
      "clientMetadata": {"optional_key_1": "optional_metadata_value_1"}
    }
  ],
  "skip_duplicate_urls": true
}

PDFs

The following is an example JSON file for uploading PDFs to Encord.

Template: Imports PDFs with an Encord title, and with custom metadata. Custom metadata only appears in the Encord UI in Active and Index as an option to filter your data.
Data: Imports two PDFs with no title or custom metadata.
Custom Metadata: Imports two pdfs with a title and custom metadata.

{
  "pdfs": [
    {
      "objectUrl": "<object url_1>"
    },
    {
      "objectUrl": "<object url_2>",
      "title": "my-file.html",
      "clientMetadata": {"optional_key_1": "optional_metadata_value_1"}
    }
  ],
  "skip_duplicate_urls": true
}

Text Files

The following is an example JSON file for uploading text files to Encord.

Template: Imports text files with an Encord title, and with custom metadata. Custom metadata only appears in the Encord UI in Active and Index as an option to filter your data.
Data: Imports two text files with no title or custom metadata.
Custom Metadata: Imports two text files with a title and custom metadata.

{
  "text": [
    {
      "objectUrl": "<object url_1>"
    },
    {
      "objectUrl": "<object url_2>",
      "title": "my-file.html",
      "clientMetadata": {"optional_key_1": "optional_metadata_value_1"}
    }
  ],
  "skip_duplicate_urls": true
}

Single Images

For detailed information about the JSON file format used for import go here.

The JSON structure for single images parallels that of videos.

Template: Provides the proper JSON format to import images into Encord.

Examples:

Data Imports the images only.
Custom Metadata: Imports images with an Encord title for the images and with custom metadata for each image. Custom metadata only appears in Active and Index as an option to filter your data. This example includes the following custom metadata types: boolean, varchar, datetime, uuid, number.
Embeddings: Imports images with an Encord title, custom metadata, and custom embeddings for each image. This example includes the following custom metadata types: boolean, varchar, datetime, uuid, number.
Image Metadata: Imports images with image metadata. This improves the import speed for your images.

{
  "images": [
    {
      "objectUrl": "file/path/to/images/file-name-01.file-extension"
    },
    {
      "objectUrl": "file/path/to/images/file-name-02.file-extension"
    },
    {
      "objectUrl": "file/path/to/images/file-name-03.file-extension",
      "title": "image-title.file-extension",
      "clientMetadata": {
        "metadata-1": "value", 
        "metadata-2": "value"
        }
    },
    {
      "objectUrl": "file/path/to/images/file-name-04.file-extension",
      "title": "image-title.file-extension",
      "clientMetadata": {
        "metadata-1": "value", 
        "metadata-2": "value", 
        "<my-embedding>": [1.0, 2.0, 3.0]
      }
     }
  ],
  "skip_duplicate_urls": true
}

Image groups

For detailed information about the JSON file format used for import go here.

Image groups are collections of images that are processed as one annotation task.
Images within image groups remain unaltered, meaning that images of different sizes and resolutions can form an image group without the loss of data.
Image groups do NOT require ‘write’ permissions to your cloud storage.
Custom metadata is defined per image group, not per image. See our documentation here to learn how to add clientMetadata to images in an image group.
If skip_duplicate_urls is set to true, all URLs exactly matching existing image groups in the dataset are skipped.

The position of each image within the sequence needs to be specified in the key (objectUrl_{position_number}).

Template: Provides the proper JSON format to import image groups into Encord.

Examples:

Data: Imports the image groups only.
Custom Metadata: Imports image groups with an Encord title for the image groups and with custom metadata for each image. Custom metadata only appears in Active and Index as an option to filter your data. This example includes the following custom metadata types: boolean, varchar, datetime, uuid, number.

{
  "image_groups": [
    {
      "title": "<title 1>",
      "createVideo": false,
      "objectUrl_0": "file/path/to/images/file-name-01.file-extension",
      "objectUrl_1": "file/path/to/images/file-name-02.file-extension",
      "objectUrl_2": "file/path/to/images/file-name-03.file-extension",
    },
    {
      "title": "<title 2>",
      "createVideo": false,
      "objectUrl_0": "file/path/to/images/file-name-01.file-extension",
      "objectUrl_1": "file/path/to/images/file-name-02.file-extension",
      "objectUrl_2": "file/path/to/images/file-name-03.file-extension",
      "clientMetadata": {"optional": "metadata"}
    }
  ],
  "skip_duplicate_urls": true
}

Image sequences

For detailed information about the JSON file format used for import go here.

Image sequences are collections of images that are processed as one annotation task and represented as a video.
Images within image sequences may be altered as images of varying sizes and resolutions are made to match that of the first image in the sequence.
Creating Image sequences from cloud storage requires ‘write’ permissions, as new files have to be created in order to be read as a video.
Each object in the image_groups array with the createVideo flag set to true represents a single image sequence.
Custom client metadata is defined per image sequence, not per image.
If skip_duplicate_urls is set to true, all URLs exactly matching existing image sequences in the dataset are skipped.

The only difference between adding image groups and image sequences using a JSON file is that image sequences require the createVideo flag to be set to true. Both use the key image_groups.

The position of each image within the sequence needs to be specified in the key (objectUrl_{position_number}).

Encord supports up to 32,767 entries (21:50 minutes) for a single image sequence. We recommend up to 10,000 to 15,000 entries for a single image sequence for best performance. If you need a longer sequence, we recommend using video instead of an image sequence.

Template: Provides the proper JSON format to import image groups into Encord.

** Examples:**

Data: Imports the images groups only.
Custom Metadata: Imports image groups and custom metadata. This example includes the following custom metadata types: boolean, varchar, datetime, uuid, number.

{
  "image_groups": [
    {
      "title": "<title 1>",
      "createVideo": true,
      "objectUrl_0": "<object url>"
    },
    {
      "title": "<title 2>",
      "createVideo": true,
      "objectUrl_0": "<object url>",
      "objectUrl_1": "<object url>",
      "objectUrl_2": "<object url>",
      "clientMetadata": {"optional": "metadata"}
    }
  ],
  "skip_duplicate_urls": true
}

DICOM

For detailed information about the JSON file format used for import go here.

Each dicom_series element can contain one or more DICOM series.
Each series requires a title and at least one object URL, as shown in the example below.
If skip_duplicate_urls is set to true, all object URLs exactly matching existing DICOM files in the dataset will be skipped.

Custom metadata is distinct from patient metadata, which is included in the .dcm file and does not have to be specific during the upload to Encord.

The following is an example JSON for uploading three DICOM series belonging to a study. Each title and object URL correspond to individual DICOM series.

The first series contains only a single object URL, as it is composed of a single file.
The second series contains 3 object URLs, as it is composed of three separate files.
The third series contains 2 object URLs, as it is composed of two separate files.

For each DICOM upload, an additional DicomSeries file is created. This file represents the series file-set. Only DicomSeries are displayed in the Encord application.

Template
{
  "dicom_series": [
    {
      "title": "Series-1",
      "objectUrl_0": "https://encord-integration.s3.eu-west-2.amazonaws.com/images/study1-series1-file.dcm"
    },
    {
      "title": "Series-2",
      "objectUrl_0": "https://encord-integration.s3.eu-west-2.amazonaws.com/images/study1-series2-file1.dcm",
      "objectUrl_1": "https://encord-integration.s3.eu-west-2.amazonaws.com/images/study1-series2-file2.dcm",
      "objectUrl_2": "https://encord-integration.s3.eu-west-2.amazonaws.com/images/study1-series2-file3.dcm",
    },
      {
      "title": "Series-3",
      "objectUrl_0": "https://encord-integration.s3.eu-west-2.amazonaws.com/images/study1-series3-file1.dcm",
      "objectUrl_1": "https://encord-integration.s3.eu-west-2.amazonaws.com/images/study1-series3-file2.dcm",
    }
  ],
  "skip_duplicate_urls": true
}

NIfTI

The following is an example JSON file for uploading two NIfTI files to Encord.

Template
{
    "nifti": [
      {
        "title": "<file-1>",
        "objectUrl": "https://my-bucket/.../nifti-file1.nii"
      },
      {
        "title": "<file-2>",
        "objectUrl": "https://my-bucket/.../nifti-file2.nii.gz"
      }
    ],
    "skip_duplicate_urls": true
  }

You can upload multiple file types using a single JSON file. The example below shows 1 image, 2 videos, 2 image sequences, and 1 image group.

Multiple file types

{
  "images": [
    {
      "objectUrl": "https://encord-integration.s3.eu-west-2.amazonaws.com/images/Image1.png"
    }
  ],
  "videos": [
    {
      "objectUrl": "https://encord-integration.s3.eu-west-2.amazonaws.com/videos/Cooking.mp4"
    },
    {
      "objectUrl": "https://encord-integration.s3.eu-west-2.amazonaws.com/videos/Oranges.mp4"
    }
  ],
  "image_groups": [
    {
      "title": "apple-samsung-light",
      "createVideo": true,
      "objectUrl_0": "https://encord-integration.s3.eu-west-2.amazonaws.com/images/1+(32).jpg",
      "objectUrl_1": "https://encord-integration.s3.eu-west-2.amazonaws.com/images/1+(33).jpg",
      "objectUrl_2": "https://encord-integration.s3.eu-west-2.amazonaws.com/images/1+(34).jpg",
      "objectUrl_3": "https://encord-integration.s3.eu-west-2.amazonaws.com/images/1+(35).jpg"
    },
    {
      "title": "apple-samsung-dark",
      "createVideo": true,
      "objectUrl_0": "https://encord-integration.s3.eu-west-2.amazonaws.com/images/2+(32).jpg",
      "objectUrl_1": "https://encord-integration.s3.eu-west-2.amazonaws.com/images/2+(33).jpg",
      "objectUrl_2": "https://encord-integration.s3.eu-west-2.amazonaws.com/images/2+(34).jpg",
      "objectUrl_3": "https://encord-integration.s3.eu-west-2.amazonaws.com/images/2+(35).jpg"
    }
  ],
  "image_groups": [
    {
      "title": "apple-ios-light",
      "createVideo": false,
      "objectUrl_0": "https://encord-integration.s3.eu-west-2.amazonaws.com/images/3+(32).jpg",
      "objectUrl_1": "https://encord-integration.s3.eu-west-2.amazonaws.com/images/3+(33).jpg"
    }
  ],
  "skip_duplicate_urls": true
}

GCP JSON

Videos

The following table provides some guidance for the examples provided after the table.

Title	Description
JSON for videos	Provides the proper JSON format to import videos into Encord. This template provides examples from the most basic to the most complex.
Data	Imports videos into Encord. Why would I do this? You ONLY want to add labels and classifications to your data. You DO NOT want to use Index or Active.
Key Frames	Imports videos with an Encord title and specifies key frames (frames of interest) for Active and Index. Why would I do this? You ONLY want to see frames that you deem critical in Active and Index. You want to significantly improve the time to import videos into Active and Index. `config` is optional when specifying key frames for Active and Index: Specifying a `sampling_rate` of `0` only imports the first frame and all key frames of your video into Active and Index. `"config": { "sampling_rate": "<samples-per-second>", "keyframe_mode": "frame" or "seconds", },` If `config` is not specified, the `sampling_rate` is 1 frame per second, and the `keyframe_mode` is `frame`.
Custom Metadata	Imports videos with an Encord title, specifies key frames (frames of interest), and custom metadata for Active and Index. Why would I do this? Importing custom metadata allows you to filter your data in Active and Index to make it easier to find the data you want to focus on. This speeds up creating Collections and by extension Datasets. Specifying key frames means you ONLY want to see frames that you deem critical in Active and Index AND you want to significantly improve the time to import videos into Active and Index. `config` is optional when specifying key frames for Active and Index: Specifying a `sampling_rate` of `0` only imports the first frame and all key frames of your video into Active and Index. `"config": { "sampling_rate": "<samples-per-second>", "keyframe_mode": "frame" or "seconds", },` If `config` is not specified, the `sampling_rate` is 1 frame per second, and the `keyframe_mode` is `frame`.
Embeddings	Imports videos with an Encord title, specifies key frames (frames of interest), custom metadata, and custom embeddings for Active and Index. This example includes the following custom metadata types: boolean, varchar, datetime, uuid, number. Why would I do this? Importing custom embeddings allows you to use scatter plots to examine your data AND allows you to use similarity search and natural language searches. Active and Index support embedding dimensions 1 to 4096 for Index. 1 to 2000 for Active. Importing custom metadata allows you to filter your data in Active and Index to make it easier to find the data you want to focus on. This speeds up creating Collections and by extension Datasets. Specifying key frames means you ONLY want to see frames that you deem critical in Active and Index AND you want to significantly improve the time to import videos into Active and Index. `config` is optional when specifying custom embeddings for Active and Index: Specifying a `sampling_rate` of `0` only imports the first frame and all key frames of your video into Active and Index. `"config": { "sampling_rate": "<samples-per-second>", "keyframe_mode": "frame" or "seconds", },` If `config` is not specified, the `sampling_rate` is 1 frame per second, and the `keyframe_mode` is `frame`. Refer to our documentation for more information about Index with Custom Metadata, Index with Custom Embeddings, Active with Custom Metadata and Active with Custom Embeddings.
Video Metadata	Imports videos with the videoMetadata flag. When the videoMetadata flag is present in the JSON file, we directly use the supplied metadata without performing any additional validation, and do not store the file on our servers. To guarantee accurate labels, it is crucial that the metadata you provide is accurate.

{
  "videos": [
    {
      "objectUrl": "cloud-path-to-your-video-1"
    },
    {
      "objectUrl": "cloud-path-to-your-video-2",
        "videoMetadata": {
          "fps": frames-per-second,
          "duration": duration-in-seconds,
          "width": frame-width,
          "height": frame-height,
          "file_size": file-size-in-bytes,
          "mime_type": "MIME-file-type-extension"
        }
      }
    {
      "objectUrl": "cloud-path-to-your-video-3",
      "title": "title-for-your-video-3",
      "clientMetadata": {"metadata-1": "value", "metadata-2": "value"}

    },
    {
      "objectUrl": "cloud-path-to-your-video-4",
      "title": "title-for-your-video-4",
      "clientMetadata": {
          "metadata-1": "value", "metadata-2": "value",
          "$encord": {
              "frames": ["<frame-number-1>","<frame-number-2>","<frame-number-3>"]
            }
        }
    },
    {
        "objectUrl": "cloud-path-to-your-video-5",
        "title": "title-for-your-video-5",
        "clientMetadata": {
            "metadata-1": "value", "metadata-2": "value",
            "$encord": {
                "frames": {
                    "<frame-number-or-seconds>": {
                        "<my-embedding>": [1.0, 2.0, 3.0]
                    },
                    "<frame-number-or-seconds>": {
                        "<my-embedding>": [1.0, 2.0, 3.0]
                    }
                }
             }
          }
    },
    {
      "objectUrl": "cloud-path-to-your-video-6",
        "title": "title-for-your-video-5",
        "clientMetadata": {
            "metadata-1": "value", "metadata-2": "value",
            "$encord": {
                "config": {
                    "sampling_rate": "<samples-per-second>",
                    "keyframe_mode": "frame" or "seconds",
                },
                "frames": {
                    "<frame-number-or-seconds>": {
                        "<my-embedding>": [1.0, 2.0, 3.0]
                    },
                    "<frame-number-or-seconds>": {
                        "<my-embedding>": [1.0, 2.0, 3.0]
                    }
                }
            }
        }
    }
  ],
  "skip_duplicate_urls": true
}

Audio Files

The following is an example JSON file for uploading two audio files to Encord.

Example 1 imports audio files with an Encord title, and with custom metadata. Custom metadata only appears in the Encord UI in Active and Index as an option to filter your data.
Example 2 imports one audio file with the audiometadata flag. When the audiometadata flag is present in the JSON file, we directly use the supplied metadata without performing any additional validation, and do not store the file on our servers. To guarantee accurate labels, it is crucial that the metadata you provide is accurate.

{
  "audio": [
    {
      "objectUrl": "<object url_1>"
    },
    {
      "objectUrl": "<object url_2>",
      "title": "my-custom-audio-file-title.mp3",
      "clientMetadata": {"optional_key_1": "optional_metadata_value_1"}
    }
  ],
  "skip_duplicate_urls": true
}

PDFs

The following is an example JSON file for uploading PDFs to Encord.

Template: Imports PDFs with an Encord title, and with custom metadata. Custom metadata only appears in the Encord UI in Active and Index as an option to filter your data.
Data: Imports two PDFs with no title or custom metadata.
Custom Metadata: Imports two pdfs with a title and custom metadata.

{
  "pdfs": [
    {
      "objectUrl": "<object url_1>"
    },
    {
      "objectUrl": "<object url_2>",
      "title": "my-file.html",
      "clientMetadata": {"optional_key_1": "optional_metadata_value_1"}
    }
  ],
  "skip_duplicate_urls": true
}

Text Files

The following is an example JSON file for uploading text files to Encord.

Template: Imports text files with an Encord title, and with custom metadata. Custom metadata only appears in the Encord UI in Active and Index as an option to filter your data.
Data: Imports two text files with no title or custom metadata.
Custom Metadata: Imports two text files with a title and custom metadata.

{
  "text": [
    {
      "objectUrl": "<object url_1>"
    },
    {
      "objectUrl": "<object url_2>",
      "title": "my-file.html",
      "clientMetadata": {"optional_key_1": "optional_metadata_value_1"}
    }
  ],
  "skip_duplicate_urls": true
}

Single Images

For detailed information about the JSON file format used for import go here.

The JSON structure for single images parallels that of videos.

Template: Provides the proper JSON format to import images into Encord.

Examples:

Data Imports the images only.
Custom Metadata: Imports images with an Encord title for the images and with custom metadata for each image. Custom metadata only appears in Active and Index as an option to filter your data. This example includes the following custom metadata types: boolean, varchar, datetime, uuid, number.
Embeddings: Imports images with an Encord title, custom metadata, and custom embeddings for each image. This example includes the following custom metadata types: boolean, varchar, datetime, uuid, number.
Image Metadata: Imports images with image metadata. This improves the import speed for your images.

{
  "images": [
    {
      "objectUrl": "file/path/to/images/file-name-01.file-extension"
    },
    {
      "objectUrl": "file/path/to/images/file-name-02.file-extension"
    },
    {
      "objectUrl": "file/path/to/images/file-name-03.file-extension",
      "title": "image-title.file-extension",
      "clientMetadata": {
        "metadata-1": "value", 
        "metadata-2": "value"
        }
    },
    {
      "objectUrl": "file/path/to/images/file-name-04.file-extension",
      "title": "image-title.file-extension",
      "clientMetadata": {
        "metadata-1": "value", 
        "metadata-2": "value", 
        "<my-embedding>": [1.0, 2.0, 3.0]
      }
     }
  ],
  "skip_duplicate_urls": true
}

Image groups

For detailed information about the JSON file format used for import go here.

Image groups are collections of images that are processed as one annotation task.
Images within image groups remain unaltered, meaning that images of different sizes and resolutions can form an image group without the loss of data.
Image groups do NOT require ‘write’ permissions to your cloud storage.
Custom metadata is defined per image group, not per image. See our documentation here to learn how to add clientMetadata to images in an image group.
If skip_duplicate_urls is set to true, all URLs exactly matching existing image groups in the dataset are skipped.

The position of each image within the sequence needs to be specified in the key (objectUrl_{position_number}).

Template: Provides the proper JSON format to import image groups into Encord.

Examples:

Data: Imports the image groups only.
Custom Metadata: Imports image groups with an Encord title for the image groups and with custom metadata for each image. Custom metadata only appears in Active and Index as an option to filter your data. This example includes the following custom metadata types: boolean, varchar, datetime, uuid, number.

{
  "image_groups": [
    {
      "title": "<title 1>",
      "createVideo": false,
      "objectUrl_0": "file/path/to/images/file-name-01.file-extension",
      "objectUrl_1": "file/path/to/images/file-name-02.file-extension",
      "objectUrl_2": "file/path/to/images/file-name-03.file-extension",
    },
    {
      "title": "<title 2>",
      "createVideo": false,
      "objectUrl_0": "file/path/to/images/file-name-01.file-extension",
      "objectUrl_1": "file/path/to/images/file-name-02.file-extension",
      "objectUrl_2": "file/path/to/images/file-name-03.file-extension",
      "clientMetadata": {"optional": "metadata"}
    }
  ],
  "skip_duplicate_urls": true
}

Image sequences

For detailed information about the JSON file format used for import go here.

Image sequences are collections of images that are processed as one annotation task and represented as a video.
Images within image sequences may be altered as images of varying sizes and resolutions are made to match that of the first image in the sequence.
Creating Image sequences from cloud storage requires ‘write’ permissions, as new files have to be created in order to be read as a video.
Each object in the image_groups array with the createVideo flag set to true represents a single image sequence.
Custom client metadata is defined per image sequence, not per image.
If skip_duplicate_urls is set to true, all URLs exactly matching existing image sequences in the dataset are skipped.

The only difference between adding image groups and image sequences using a JSON file is that image sequences require the createVideo flag to be set to true. Both use the key image_groups.

The position of each image within the sequence needs to be specified in the key (objectUrl_{position_number}).

Template: Provides the proper JSON format to import image groups into Encord.

** Examples:**

Data: Imports the images groups only.
Custom Metadata: Imports image groups and custom metadata. This example includes the following custom metadata types: boolean, varchar, datetime, uuid, number.

{
  "image_groups": [
    {
      "title": "<title 1>",
      "createVideo": true,
      "objectUrl_0": "<object url>"
    },
    {
      "title": "<title 2>",
      "createVideo": true,
      "objectUrl_0": "<object url>",
      "objectUrl_1": "<object url>",
      "objectUrl_2": "<object url>",
      "clientMetadata": {"optional": "metadata"}
    }
  ],
  "skip_duplicate_urls": true
}

DICOM

For detailed information about the JSON file format used for import go here.

Each dicom_series element can contain one or more DICOM series.
Each series requires a title and at least one object URL, as shown in the example below.
If skip_duplicate_urls is set to true, all object URLs exactly matching existing DICOM files in the dataset will be skipped.

Custom metadata is distinct from patient metadata, which is included in the .dcm file and does not have to be specific during the upload to Encord.

The following is an example JSON for uploading three DICOM series belonging to a study. Each title and object URL correspond to individual DICOM series.

The first series contains only a single object URL, as it is composed of a single file.
The second series contains 3 object URLs, as it is composed of three separate files.
The third series contains 2 object URLs, as it is composed of two separate files.

For each DICOM upload, an additional DicomSeries file is created. This file represents the series file-set. Only DicomSeries are displayed in the Encord application.

JSON for DICOM
{
  "dicom_series": [
    {
      "title": "Series-1",
      "objectUrl_0": "https://storage.cloud.google.com/encord-image-bucket/images/study1-series1-file.dcm"
    },
    {
      "title": "Series-2",
      "objectUrl_0": "https://storage.cloud.google.com/encord-image-bucket/images/study1-series2-file1.dcm",
      "objectUrl_1": "https://storage.cloud.google.com/encord-image-bucket/images/study1-series2-file2.dcm",
      "objectUrl_2": "https://storage.cloud.google.com/encord-image-bucket/images/study1-series2-file3.dcm",
    },
      {
      "title": "Series-3",
      "objectUrl_0": "https://storage.cloud.google.com/encord-image-bucket/images/study1-series3-file1.dcm",
      "objectUrl_1": "https://storage.cloud.google.com/encord-image-bucket/images/study1-series3-file2.dcm",
    }
  ],
  "skip_duplicate_urls": true
}

NIfTI

The following is an example JSON file for uploading two NIfTI files to Encord.

{
    "nifti": [
      {
        "title": "<file-1>",
        "objectUrl": "https://my-bucket/.../nifti-file1.nii"
      },
      {
        "title": "<file-2>",
        "objectUrl": "https://my-bucket/.../nifti-file2.nii.gz"
      }
    ],
    "skip_duplicate_urls": true
  }

You can upload multiple file types using a single JSON file. The example below shows 1 image, 2 videos, 2 image sequences, and 1 image group.

Multiple file types

{
  "images": [
    {
      "objectUrl": "https://storage.cloud.google.com/encord-image-bucket/images/Image1.png"
    }
  ],
  "videos": [
    {
      "objectUrl": "https://storage.cloud.google.com/encord-image-bucket/videos/Cooking.mp4"
    },
    {
      "objectUrl": "https://storage.cloud.google.com/encord-image-bucket/videos/Oranges.mp4"
    }
  ],
  "image_groups": [
    {
      "title": "apple-samsung-light",
      "createVideo": true,
      "objectUrl_0": "https://storage.cloud.google.com/encord-image-bucket/images/1+(32).jpg",
      "objectUrl_1": "https://encord-integration.s3.eu-west-2.amazonaws.com/images/1+(33).jpg",
      "objectUrl_2": "https://encord-integration.s3.eu-west-2.amazonaws.com/images/1+(34).jpg",
      "objectUrl_3": "https://encord-integration.s3.eu-west-2.amazonaws.com/images/1+(35).jpg"
    },
    {
      "title": "apple-samsung-dark",
      "createVideo": true,
      "objectUrl_0": "https://storage.cloud.google.com/encord-image-bucket/images/2+(32).jpg",
      "objectUrl_1": "https://storage.cloud.google.com/encord-image-bucket/images/2+(33).jpg",
      "objectUrl_2": "https://storage.cloud.google.com/encord-image-bucket/images/2+(34).jpg",
      "objectUrl_3": "https://storage.cloud.google.com/encord-image-bucket/images/2+(35).jpg"
    }
  ],
  "image_groups": [
    {
      "title": "apple-ios-light",
      "createVideo": false,
      "objectUrl_0": "https://storage.cloud.google.com/encord-image-bucket/images/3+(32).jpg",
      "objectUrl_1": "https://storage.cloud.google.com/encord-image-bucket/images/3+(33).jpg"
    }
  ],
  "skip_duplicate_urls": true
}

Azure JSON

Videos

The following table provides some guidance for the examples provided after the table.

Title	Description
Template	Provides the proper JSON format to import videos into Encord. This template provides examples from the most basic to the most complex.
Data	Imports videos into Encord. Why would I do this? You ONLY want to add labels and classifications to your data. You DO NOT want to use Index or Active.
Key Frames	Imports videos with an Encord title and specifies key frames (frames of interest) for Active and Index. Why would I do this? You ONLY want to see frames that you deem critical in Active and Index. You want to significantly improve the time to import videos into Active and Index. `config` is optional when specifying key frames for Active and Index: Specifying a `sampling_rate` of `0` only imports the first frame and all key frames of your video into Active and Index. `"config": { "sampling_rate": "<samples-per-second>", "keyframe_mode": "frame" or "seconds", },` If `config` is not specified, the `sampling_rate` is 1 frame per second, and the `keyframe_mode` is `frame`.
Custom Metadata	Imports videos with an Encord title, specifies key frames (frames of interest), and custom metadata for Active and Index. Why would I do this? Importing custom metadata allows you to filter your data in Active and Index to make it easier to find the data you want to focus on. This speeds up creating Collections and by extension Datasets. Specifying key frames means you ONLY want to see frames that you deem critical in Active and Index AND you want to significantly improve the time to import videos into Active and Index. `config` is optional when specifying key frames for Active and Index: Specifying a `sampling_rate` of `0` only imports the first frame and all key frames of your video into Active and Index. `"config": { "sampling_rate": "<samples-per-second>", "keyframe_mode": "frame" or "seconds", },` If `config` is not specified, the `sampling_rate` is 1 frame per second, and the `keyframe_mode` is `frame`.
Embeddings	Imports videos with an Encord title, specifies key frames (frames of interest), custom metadata, and custom embeddings for Active and Index. This example includes the following custom metadata types: boolean, varchar, datetime, uuid, number. Why would I do this? Importing custom embeddings allows you to use scatter plots to examine your data AND allows you to use similarity search and natural language searches. Index supports embedding dimensions 1 to 4096, while Active supports embedding dimensions 1 to 2000. Importing custom metadata allows you to filter your data in Active and Index to make it easier to find the data you want to focus on. This speeds up creating Collections and by extension Datasets. Specifying key frames means you ONLY want to see frames that you deem critical in Active and Index AND you want to significantly improve the time to import videos into Active and Index. `config` is optional when specifying custom embeddings for Active and Index: Specifying a `sampling_rate` of `0` only imports the first frame and all key frames of your video into Active and Index. `"config": { "sampling_rate": "<samples-per-second>", "keyframe_mode": "frame" or "seconds", },` If `config` is not specified, the `sampling_rate` is 1 frame per second, and the `keyframe_mode` is `frame`. Refer to our documentation for more information about Index with Custom Metadata, Index with Custom Embeddings, Active with Custom Metadata and Active with Custom Embeddings.
Video Metadata	Imports videos with the videoMetadata flag. When the videoMetadata flag is present in the JSON file, we directly use the supplied metadata without performing any additional validation, and do not store the file on our servers. To guarantee accurate labels, it is crucial that the metadata you provide is accurate.

{
  "videos": [
    {
      "objectUrl": "cloud-path-to-your-video-1"
    },
    {
      "objectUrl": "cloud-path-to-your-video-2",
        "videoMetadata": {
          "fps": frames-per-second,
          "duration": duration-in-seconds,
          "width": frame-width,
          "height": frame-height,
          "file_size": file-size-in-bytes,
          "mime_type": "MIME-file-type-extension"
        }
      }
    {
      "objectUrl": "cloud-path-to-your-video-3",
      "title": "title-for-your-video-3",
      "clientMetadata": {"metadata-1": "value", "metadata-2": "value"}

    },
    {
      "objectUrl": "cloud-path-to-your-video-4",
      "title": "title-for-your-video-4",
      "clientMetadata": {
          "metadata-1": "value", "metadata-2": "value",
          "$encord": {
              "frames": ["<frame-number-1>","<frame-number-2>","<frame-number-3>"]
            }
        }
    },
    {
        "objectUrl": "cloud-path-to-your-video-5",
        "title": "title-for-your-video-5",
        "clientMetadata": {
            "metadata-1": "value", "metadata-2": "value",
            "$encord": {
                "frames": {
                    "<frame-number-or-seconds>": {
                        "<my-embedding>": [1.0, 2.0, 3.0]
                    },
                    "<frame-number-or-seconds>": {
                        "<my-embedding>": [1.0, 2.0, 3.0]
                    }
                }
             }
          }
    },
    {
      "objectUrl": "cloud-path-to-your-video-6",
        "title": "title-for-your-video-5",
        "clientMetadata": {
            "metadata-1": "value", "metadata-2": "value",
            "$encord": {
                "config": {
                    "sampling_rate": "<samples-per-second>",
                    "keyframe_mode": "frame" or "seconds",
                },
                "frames": {
                    "<frame-number-or-seconds>": {
                        "<my-embedding>": [1.0, 2.0, 3.0]
                    },
                    "<frame-number-or-seconds>": {
                        "<my-embedding>": [1.0, 2.0, 3.0]
                    }
                }
            }
        }
    }
  ],
  "skip_duplicate_urls": true
}

Audio Files

The following is an example JSON file for uploading two audio files to Encord.

Template: Imports audio files with an Encord title, and with custom metadata. Custom metadata only appears in the Encord UI in Active and Index as an option to filter your data.
Audio Metadata: Imports one audio file with the audiometadata flag. When the audiometadata flag is present in the JSON file, we directly use the supplied metadata without performing any additional validation, and do not store the file on our servers. To guarantee accurate labels, it is crucial that the metadata you provide is accurate.

{
  "audio": [
    {
      "objectUrl": "<object url_1>"
    },
    {
      "objectUrl": "<object url_2>",
      "title": "my-custom-audio-file-title.mp3",
      "clientMetadata": {"optional_key_1": "optional_metadata_value_1"}
    }
  ],
  "skip_duplicate_urls": true
}

PDFs

The following is an example JSON file for uploading PDFs to Encord.

Template: Imports PDFs with an Encord title, and with custom metadata. Custom metadata only appears in the Encord UI in Active and Index as an option to filter your data.
Data: Imports two PDFs with no title or custom metadata.
Custom Metadata: Imports two pdfs with a title and custom metadata.

{
  "pdfs": [
    {
      "objectUrl": "<object url_1>"
    },
    {
      "objectUrl": "<object url_2>",
      "title": "my-file.html",
      "clientMetadata": {"optional_key_1": "optional_metadata_value_1"}
    }
  ],
  "skip_duplicate_urls": true
}

Text Files

The following is an example JSON file for uploading text files to Encord.

Template: Imports text files with an Encord title, and with custom metadata. Custom metadata only appears in the Encord UI in Active and Index as an option to filter your data.
Data: Imports two text files with no title or custom metadata.
Custom Metadata: Imports two text files with a title and custom metadata.

{
  "text": [
    {
      "objectUrl": "<object url_1>"
    },
    {
      "objectUrl": "<object url_2>",
      "title": "my-file.html",
      "clientMetadata": {"optional_key_1": "optional_metadata_value_1"}
    }
  ],
  "skip_duplicate_urls": true
}

Single Images

For detailed information about the JSON file format used for import go here.

The JSON structure for single images parallels that of videos.

Template: Provides the proper JSON format to import images into Encord.

Examples:

Data Imports the images only.
Custom Metadata: Imports images with an Encord title for the images and with custom metadata for each image. Custom metadata only appears in Active and Index as an option to filter your data. This example includes the following custom metadata types: boolean, varchar, datetime, uuid, number.
Embeddings: Imports images with an Encord title, custom metadata, and custom embeddings for each image. This example includes the following custom metadata types: boolean, varchar, datetime, uuid, number.
Image Metadata: Imports images with image metadata. This improves the import speed for your images.

{
  "images": [
    {
      "objectUrl": "file/path/to/images/file-name-01.file-extension"
    },
    {
      "objectUrl": "file/path/to/images/file-name-02.file-extension"
    },
    {
      "objectUrl": "file/path/to/images/file-name-03.file-extension",
      "title": "image-title.file-extension",
      "clientMetadata": {
        "metadata-1": "value", 
        "metadata-2": "value"
        }
    },
    {
      "objectUrl": "file/path/to/images/file-name-04.file-extension",
      "title": "image-title.file-extension",
      "clientMetadata": {
        "metadata-1": "value", 
        "metadata-2": "value", 
        "<my-embedding>": [1.0, 2.0, 3.0]
      }
     }
  ],
  "skip_duplicate_urls": true
}

Image groups

For detailed information about the JSON file format used for import go here.

Image groups are collections of images that are processed as one annotation task.
Images within image groups remain unaltered, meaning that images of different sizes and resolutions can form an image group without the loss of data.
Image groups do NOT require ‘write’ permissions to your cloud storage.
Custom metadata is defined per image group, not per image. See our documentation here to learn how to add clientMetadata to images in an image group.
If skip_duplicate_urls is set to true, all URLs exactly matching existing image groups in the dataset are skipped.

The position of each image within the sequence needs to be specified in the key (objectUrl_{position_number}).

Template: Provides the proper JSON format to import image groups into Encord.

Examples:

Data: Imports the image groups only.
Custom Metadata: Imports image groups with an Encord title for the image groups and with custom metadata for each image. Custom metadata only appears in Active and Index as an option to filter your data. This example includes the following custom metadata types: boolean, varchar, datetime, uuid, number.

{
  "image_groups": [
    {
      "title": "<title 1>",
      "createVideo": false,
      "objectUrl_0": "file/path/to/images/file-name-01.file-extension",
      "objectUrl_1": "file/path/to/images/file-name-02.file-extension",
      "objectUrl_2": "file/path/to/images/file-name-03.file-extension"
    },
    {
      "title": "<title 2>",
      "createVideo": false,
      "objectUrl_0": "file/path/to/images/file-name-01.file-extension",
      "objectUrl_1": "file/path/to/images/file-name-02.file-extension",
      "objectUrl_2": "file/path/to/images/file-name-03.file-extension",
      "clientMetadata": {"optional": "metadata"}
    }
  ],
  "skip_duplicate_urls": true
}

Image sequences

For detailed information about the JSON file format used for import go here.

Image sequences are collections of images that are processed as one annotation task and represented as a video.
Images within image sequences may be altered as images of varying sizes and resolutions are made to match that of the first image in the sequence.
Creating Image sequences from cloud storage requires ‘write’ permissions, as new files have to be created in order to be read as a video.
Each object in the image_groups array with the createVideo flag set to true represents a single image sequence.
Custom client metadata is defined per image sequence, not per image.
If skip_duplicate_urls is set to true, all URLs exactly matching existing image sequences in the dataset are skipped.

The only difference between adding image groups and image sequences using a JSON file is that image sequences require the createVideo flag to be set to true. Both use the key image_groups.

The position of each image within the sequence needs to be specified in the key (objectUrl_{position_number}).

Template: Provides the proper JSON format to import image groups into Encord.

** Examples:**

Data: Imports the images groups only.
Custom Metadata: Imports image groups and custom metadata. This example includes the following custom metadata types: boolean, varchar, datetime, uuid, number.

{
  "image_groups": [
    {
      "title": "<title 1>",
      "createVideo": true,
      "objectUrl_0": "<object url>"
    },
    {
      "title": "<title 2>",
      "createVideo": true,
      "objectUrl_0": "<object url>",
      "objectUrl_1": "<object url>",
      "objectUrl_2": "<object url>",
      "clientMetadata": {"optional": "metadata"}
    }
  ],
  "skip_duplicate_urls": true
}

DICOM

For detailed information about the JSON file format used for import go here.

Each dicom_series element can contain one or more DICOM series.
Each series requires a title and at least one object URL, as shown in the example below.
If skip_duplicate_urls is set to true, all object URLs exactly matching existing DICOM files in the dataset will be skipped.

Custom metadata is distinct from patient metadata, which is included in the .dcm file and does not have to be specific during the upload to Encord.

The following is an example JSON for uploading three DICOM series belonging to a study. Each title and object URL correspond to individual DICOM series.

The first series contains only a single object URL, as it is composed of a single file.
The second series contains 3 object URLs, as it is composed of three separate files.
The third series contains 2 object URLs, as it is composed of two separate files.

For each DICOM upload, an additional DicomSeries file is created. This file represents the series file-set. Only DicomSeries are displayed in the Encord application.

Template
{
  "dicom_series": [
    {
      "title": "Series-1",
      "objectUrl_0": "https://myaccount.blob.core.windows.net/encordcontainer/study1-series1-file.dcm"
    },
    {
      "title": "Series-2",
      "objectUrl_0": "https://myaccount.blob.core.windows.net/encordcontainer/study1-series2-file1.dcm",
      "objectUrl_1": "https://myaccount.blob.core.windows.net/encordcontainer/study1-series2-file2.dcm",
      "objectUrl_2": "https://myaccount.blob.core.windows.net/encordcontainer/study1-series2-file3.dcm",
    },
      {
      "title": "Series-3",
      "objectUrl_0": "https://myaccount.blob.core.windows.net/encordcontainer/study1-series3-file1.dcm",
      "objectUrl_1": "https://myaccount.blob.core.windows.net/encordcontainer/study1-series3-file2.dcm",
    }
  ],
  "skip_duplicate_urls": true
}

NIfTI

The following is an example JSON file for uploading two NIfTI files to Encord.

Template
{
    "nifti": [
      {
        "title": "<file-1>",
        "objectUrl": "https://my-bucket/.../nifti-file1.nii"
      },
      {
        "title": "<file-2>",
        "objectUrl": "https://my-bucket/.../nifti-file2.nii.gz"
      }
    ],
    "skip_duplicate_urls": true
  }

You can upload multiple file types using a single JSON file. The example below shows 1 image, 2 videos, 2 image sequences, and 1 image group.

{
  "images": [
    {
      "objectUrl": "https://myaccount.blob.core.windows.net/encordcontainer/Image1.png"
    }
  ],
  "videos": [
    {
      "objectUrl": "https://myaccount.blob.core.windows.net/encordcontainer/Cooking.mp4"
    },
    {
      "objectUrl": "https://myaccount.blob.core.windows.net/encordcontainer/Oranges.mp4"
    }
  ],
  "image_groups": [
    {
      "title": "apple-samsung-light",
      "createVideo": true,
      "objectUrl_0": "https://myaccount.blob.core.windows.net/encordcontainer/1-Samsung-S4-Light+Environment/1+(32).jpg",
      "objectUrl_1": "https://myaccount.blob.core.windows.net/encordcontainer/1-Samsung-S4-Light+Environment/1+(33).jpg",
      "objectUrl_2": "https://myaccount.blob.core.windows.net/encordcontainer/1-Samsung-S4-Light+Environment/1+(34).jpg",
      "objectUrl_3": "https://myaccount.blob.core.windows.net/encordcontainer/1-Samsung-S4-Light+Environment/1+(35).jpg"
    },
    {
      "title": "apple-samsung-dark",
      "createVideo": true,
      "objectUrl_0": "https://myaccount.blob.core.windows.net/encordcontainer/2-samsung-S4-Dark+Environment/2+(32).jpg",
      "objectUrl_1": "https://myaccount.blob.core.windows.net/encordcontainer/2-samsung-S4-Dark+Environment/2+(33).jpg",
      "objectUrl_2": "https://myaccount.blob.core.windows.net/encordcontainer/2-samsung-S4-Dark+Environment/2+(34).jpg",
      "objectUrl_3": "https://myaccount.blob.core.windows.net/encordcontainer/2-samsung-S4-Dark+Environment/2+(35).jpg"
    }
  ],
  "image_groups": [
    {
      "title": "apple-ios-light",
      "createVideo": false,
      "objectUrl_0": "https://myaccount.blob.core.windows.net/encordcontainer/3-IOS-4-Light+Environment/3+(32).jpg",
      "objectUrl_1": "https://myaccount.blob.core.windows.net/encordcontainer/3-IOS-4-Light+Environment/3+(33).jpg"
    }
  ],
  "skip_duplicate_urls": true
}

OTC JSON

Videos

The following table provides some guidance for the examples provided after the table.

Title	Description
Template	Provides the proper JSON format to import videos into Encord. This template provides examples from the most basic to the most complex.
Data	Imports videos into Encord. Why would I do this? You ONLY want to add labels and classifications to your data. You DO NOT want to use Index or Active.
Key Frames	Imports videos with an Encord title and specifies key frames (frames of interest) for Active and Index. Why would I do this? You ONLY want to see frames that you deem critical in Active and Index. You want to significantly improve the time to import videos into Active and Index. `config` is optional when specifying key frames for Active and Index: Specifying a `sampling_rate` of `0` only imports the first frame and all key frames of your video into Active and Index. `"config": { "sampling_rate": "<samples-per-second>", "keyframe_mode": "frame" or "seconds", },` If `config` is not specified, the `sampling_rate` is 1 frame per second, and the `keyframe_mode` is `frame`.
Custom Metadata	Imports videos with an Encord title, specifies key frames (frames of interest), and custom metadata for Active and Index. Why would I do this? Importing custom metadata allows you to filter your data in Active and Index to make it easier to find the data you want to focus on. This speeds up creating Collections and by extension Datasets. Specifying key frames means you ONLY want to see frames that you deem critical in Active and Index AND you want to significantly improve the time to import videos into Active and Index. `config` is optional when specifying key frames for Active and Index: Specifying a `sampling_rate` of `0` only imports the first frame and all key frames of your video into Active and Index. `"config": { "sampling_rate": "<samples-per-second>", "keyframe_mode": "frame" or "seconds", },` If `config` is not specified, the `sampling_rate` is 1 frame per second, and the `keyframe_mode` is `frame`.
Embeddings	Imports videos with an Encord title, specifies key frames (frames of interest), custom metadata, and custom embeddings for Active and Index. This example includes the following custom metadata types: boolean, varchar, datetime, uuid, number. Why would I do this? Importing custom embeddings allows you to use scatter plots to examine your data AND allows you to use similarity search and natural language searches. Index supports embedding dimensions 1 to 4096, while Active supports embedding dimensions 1 to 2000. Importing custom metadata allows you to filter your data in Active and Index to make it easier to find the data you want to focus on. This speeds up creating Collections and by extension Datasets. Specifying key frames means you ONLY want to see frames that you deem critical in Active and Index AND you want to significantly improve the time to import videos into Active and Index. `config` is optional when specifying custom embeddings for Active and Index: Specifying a `sampling_rate` of `0` only imports the first frame and all key frames of your video into Active and Index. `"config": { "sampling_rate": "<samples-per-second>", "keyframe_mode": "frame" or "seconds", },` If `config` is not specified, the `sampling_rate` is 1 frame per second, and the `keyframe_mode` is `frame`. Refer to our documentation for more information about Index with Custom Metadata, Index with Custom Embeddings, Active with Custom Metadata and Active with Custom Embeddings.
Video Metadata	Imports videos with the videoMetadata flag. When the videoMetadata flag is present in the JSON file, we directly use the supplied metadata without performing any additional validation, and do not store the file on our servers. To guarantee accurate labels, it is crucial that the metadata you provide is accurate.

{
  "videos": [
    {
      "objectUrl": "cloud-path-to-your-video-1"
    },
    {
      "objectUrl": "cloud-path-to-your-video-2",
        "videoMetadata": {
          "fps": frames-per-second,
          "duration": duration-in-seconds,
          "width": frame-width,
          "height": frame-height,
          "file_size": file-size-in-bytes,
          "mime_type": "MIME-file-type-extension"
        }
      }
    {
      "objectUrl": "cloud-path-to-your-video-3",
      "title": "title-for-your-video-3",
      "clientMetadata": {"metadata-1": "value", "metadata-2": "value"}

    },
    {
      "objectUrl": "cloud-path-to-your-video-4",
      "title": "title-for-your-video-4",
      "clientMetadata": {
          "metadata-1": "value", "metadata-2": "value",
          "$encord": {
              "frames": ["<frame-number-1>","<frame-number-2>","<frame-number-3>"]
            }
        }
    },
    {
        "objectUrl": "cloud-path-to-your-video-5",
        "title": "title-for-your-video-5",
        "clientMetadata": {
            "metadata-1": "value", "metadata-2": "value",
            "$encord": {
                "frames": {
                    "<frame-number-or-seconds>": {
                        "<my-embedding>": [1.0, 2.0, 3.0]
                    },
                    "<frame-number-or-seconds>": {
                        "<my-embedding>": [1.0, 2.0, 3.0]
                    }
                }
             }
          }
    },
    {
      "objectUrl": "cloud-path-to-your-video-6",
        "title": "title-for-your-video-5",
        "clientMetadata": {
            "metadata-1": "value", "metadata-2": "value",
            "$encord": {
                "config": {
                    "sampling_rate": "<samples-per-second>",
                    "keyframe_mode": "frame" or "seconds",
                },
                "frames": {
                    "<frame-number-or-seconds>": {
                        "<my-embedding>": [1.0, 2.0, 3.0]
                    },
                    "<frame-number-or-seconds>": {
                        "<my-embedding>": [1.0, 2.0, 3.0]
                    }
                }
            }
        }
    }
  ],
  "skip_duplicate_urls": true
}

Audio Files

The following is an example JSON file for uploading two audio files to Encord.

Template: Imports audio files with an Encord title, and with custom metadata. Custom metadata only appears in the Encord UI in Active and Index as an option to filter your data.
Audio Metadata: Imports one audio file with the audiometadata flag. When the audiometadata flag is present in the JSON file, we directly use the supplied metadata without performing any additional validation, and do not store the file on our servers. To guarantee accurate labels, it is crucial that the metadata you provide is accurate.

{
  "audio": [
    {
      "objectUrl": "<object url_1>"
    },
    {
      "objectUrl": "<object url_2>",
      "title": "my-custom-audio-file-title.mp3",
      "clientMetadata": {"optional_key_1": "optional_metadata_value_1"}
    }
  ],
  "skip_duplicate_urls": true
}

PDFs

The following is an example JSON file for uploading PDFs to Encord.

Template: Imports PDFs with an Encord title, and with custom metadata. Custom metadata only appears in the Encord UI in Active and Index as an option to filter your data.
Data: Imports two PDFs with no title or custom metadata.
Custom Metadata: Imports two pdfs with a title and custom metadata.

{
  "pdfs": [
    {
      "objectUrl": "<object url_1>"
    },
    {
      "objectUrl": "<object url_2>",
      "title": "my-file.html",
      "clientMetadata": {"optional_key_1": "optional_metadata_value_1"}
    }
  ],
  "skip_duplicate_urls": true
}

Text Files

The following is an example JSON file for uploading text files to Encord.

Template: Imports text files with an Encord title, and with custom metadata. Custom metadata only appears in the Encord UI in Active and Index as an option to filter your data.
Data: Imports two text files with no title or custom metadata.
Custom Metadata: Imports two text files with a title and custom metadata.

{
  "text": [
    {
      "objectUrl": "<object url_1>"
    },
    {
      "objectUrl": "<object url_2>",
      "title": "my-file.html",
      "clientMetadata": {"optional_key_1": "optional_metadata_value_1"}
    }
  ],
  "skip_duplicate_urls": true
}

Single Images

For detailed information about the JSON file format used for import go here.

The JSON structure for single images parallels that of videos.

Template: Provides the proper JSON format to import images into Encord.

Examples:

Data Imports the images only.
Custom Metadata: Imports images with an Encord title for the images and with custom metadata for each image. Custom metadata only appears in Active and Index as an option to filter your data. This example includes the following custom metadata types: boolean, varchar, datetime, uuid, number.
Embeddings: Imports images with an Encord title, custom metadata, and custom embeddings for each image. This example includes the following custom metadata types: boolean, varchar, datetime, uuid, number.
Image Metadata: Imports images with image metadata. This improves the import speed for your images.

{
  "images": [
    {
      "objectUrl": "file/path/to/images/file-name-01.file-extension"
    },
    {
      "objectUrl": "file/path/to/images/file-name-02.file-extension"
    },
    {
      "objectUrl": "file/path/to/images/file-name-03.file-extension",
      "title": "image-title.file-extension",
      "clientMetadata": {
        "metadata-1": "value", 
        "metadata-2": "value"
        }
    },
    {
      "objectUrl": "file/path/to/images/file-name-04.file-extension",
      "title": "image-title.file-extension",
      "clientMetadata": {
        "metadata-1": "value", 
        "metadata-2": "value", 
        "<my-embedding>": [1.0, 2.0, 3.0]
      }
     }
  ],
  "skip_duplicate_urls": true
}

Image groups

For detailed information about the JSON file format used for import go here.

Image groups are collections of images that are processed as one annotation task.
Images within image groups remain unaltered, meaning that images of different sizes and resolutions can form an image group without the loss of data.
Image groups do NOT require ‘write’ permissions to your cloud storage.
Custom metadata is defined per image group, not per image. See our documentation here to learn how to add clientMetadata to images in an image group.
If skip_duplicate_urls is set to true, all URLs exactly matching existing image groups in the dataset are skipped.

The position of each image within the sequence needs to be specified in the key (objectUrl_{position_number}).

Template: Provides the proper JSON format to import image groups into Encord.

Examples:

Data: Imports the image groups only.
Custom Metadata: Imports image groups with an Encord title for the image groups and with custom metadata for each image. Custom metadata only appears in Active and Index as an option to filter your data. This example includes the following custom metadata types: boolean, varchar, datetime, uuid, number.

{
  "image_groups": [
    {
      "title": "<title 1>",
      "createVideo": false,
      "objectUrl_0": "file/path/to/images/file-name-01.file-extension",
      "objectUrl_1": "file/path/to/images/file-name-02.file-extension",
      "objectUrl_2": "file/path/to/images/file-name-03.file-extension",
    },
    {
      "title": "<title 2>",
      "createVideo": false,
      "objectUrl_0": "file/path/to/images/file-name-01.file-extension",
      "objectUrl_1": "file/path/to/images/file-name-02.file-extension",
      "objectUrl_2": "file/path/to/images/file-name-03.file-extension",
      "clientMetadata": {"optional": "metadata"}
    }
  ],
  "skip_duplicate_urls": true
}

Image sequences

For detailed information about the JSON file format used for import go here.

Image sequences are collections of images that are processed as one annotation task and represented as a video.
Images within image sequences may be altered as images of varying sizes and resolutions are made to match that of the first image in the sequence.
Creating Image sequences from cloud storage requires ‘write’ permissions, as new files have to be created in order to be read as a video.
Each object in the image_groups array with the createVideo flag set to true represents a single image sequence.
Custom client metadata is defined per image sequence, not per image.
If skip_duplicate_urls is set to true, all URLs exactly matching existing image sequences in the dataset are skipped.

The only difference between adding image groups and image sequences using a JSON file is that image sequences require the createVideo flag to be set to true. Both use the key image_groups.

The position of each image within the sequence needs to be specified in the key (objectUrl_{position_number}).

Template: Provides the proper JSON format to import image groups into Encord.

** Examples:**

Data: Imports the images groups only.
Custom Metadata: Imports image groups and custom metadata. This example includes the following custom metadata types: boolean, varchar, datetime, uuid, number.

{
  "image_groups": [
    {
      "title": "<title 1>",
      "createVideo": true,
      "objectUrl_0": "<object url>"
    },
    {
      "title": "<title 2>",
      "createVideo": true,
      "objectUrl_0": "<object url>",
      "objectUrl_1": "<object url>",
      "objectUrl_2": "<object url>",
      "clientMetadata": {"optional": "metadata"}
    }
  ],
  "skip_duplicate_urls": true
}

DICOM

For detailed information about the JSON file format used for import go here.

Each dicom_series element can contain one or more DICOM series.
Each series requires a title and at least one object URL, as shown in the example below.
If skip_duplicate_urls is set to true, all object URLs exactly matching existing DICOM files in the dataset will be skipped.

Custom metadata is distinct from patient metadata, which is included in the .dcm file and does not have to be specific during the upload to Encord.

The following is an example JSON for uploading three DICOM series belonging to a study. Each title and object URL correspond to individual DICOM series.

The first series contains only a single object URL, as it is composed of a single file.
The second series contains 3 object URLs, as it is composed of three separate files.
The third series contains 2 object URLs, as it is composed of two separate files.

For each DICOM upload, an additional DicomSeries file is created. This file represents the series file-set. Only DicomSeries are displayed in the Encord application.

JSON for DICOM
{
  "dicom_series": [
    {
      "title": "Series-1",
      "objectUrl_0": "https://encord-bucket.obs.eu-de.otc.t-systems.com/images/study1-series1-file.dcm"
    },
    {
      "title": "Series-2",
      "objectUrl_0": "https://encord-bucket.obs.eu-de.otc.t-systems.com/images/study1-series2-file1.dcm",
      "objectUrl_1": "https://encord-bucket.obs.eu-de.otc.t-systems.com/images/study1-series2-file2.dcm",
      "objectUrl_2": "https://encord-bucket.obs.eu-de.otc.t-systems.com/images/study1-series2-file3.dcm",
    },
      {
      "title": "Series-3",
      "objectUrl_0": "https://encord-bucket.obs.eu-de.otc.t-systems.com/images/study1-series3-file1.dcm",
      "objectUrl_1": "https://encord-bucket.obs.eu-de.otc.t-systems.com/images/study1-series3-file2.dcm",
    }
  ],
  "skip_duplicate_urls": true
}

NIfTI

The following is an example JSON file for uploading two NIfTI files to Encord.

{
    "nifti": [
      {
        "title": "<file-1>",
        "objectUrl": "https://my-bucket/.../nifti-file1.nii"
      },
      {
        "title": "<file-2>",
        "objectUrl": "https://my-bucket/.../nifti-file2.nii.gz"
      }
    ],
    "skip_duplicate_urls": true
  }

You can upload multiple file types using a single JSON file. The example below shows 1 image, 2 videos, 2 image sequences, and 1 image group.

Multiple file types

{
  "images": [
    {
      "objectUrl": "https://encord-bucket.obs.eu-de.otc.t-systems.com/images/Image1.png"
    }
  ],
  "videos": [
    {
      "objectUrl": "https://encord-bucket.obs.eu-de.otc.t-systems.com/videos/Cooking.mp4"
    },
    {
      "objectUrl": "https://encord-bucket.obs.eu-de.otc.t-systems.com/videos/Oranges.mp4"
    }
  ],
  "image_groups": [
    {
      "title": "apple-samsung-light",
      "createVideo": true,
      "objectUrl_0": "https://encord-bucket.obs.eu-de.otc.t-systems.com/images/1+(32).jpg",
      "objectUrl_1": "https://encord-bucket.obs.eu-de.otc.t-systems.com/images/1+(33).jpg",
      "objectUrl_2": "https://encord-bucket.obs.eu-de.otc.t-systems.com/images/1+(34).jpg",
      "objectUrl_3": "https://encord-bucket.obs.eu-de.otc.t-systems.com/images/1+(35).jpg"
    },
    {
      "title": "apple-samsung-dark",
      "createVideo": true,
      "objectUrl_0": "https://encord-bucket.obs.eu-de.otc.t-systems.com/images/2+(32).jpg",
      "objectUrl_1": "https://encord-bucket.obs.eu-de.otc.t-systems.com/images/2+(33).jpg",
      "objectUrl_2": "https://encord-bucket.obs.eu-de.otc.t-systems.com/images/2+(34).jpg",
      "objectUrl_3": "https://encord-bucket.obs.eu-de.otc.t-systems.com/images/2+(35).jpg"
    }
  ],
  "image_groups": [
    {
      "title": "apple-ios-light",
      "createVideo": false,
      "objectUrl_0": "https://encord-bucket.obs.eu-de.otc.t-systems.com/images/3+(32).jpg",
      "objectUrl_1": "https://encord-bucket.obs.eu-de.otc.t-systems.com/images/3+(33).jpg"
    }
  ],
  "skip_duplicate_urls": true
}

Use a Multi-Region Access Point

When using a Multi-Region Access Point for your AWS S3 buckets the JSON file has to be slightly different from the examples provided. Instead of an object’s URL, objects are specified using the ARN of the Multi-Region Access Point followed by the object name. The example below shows how video files from a Multi-Region Access Point would be specified.

{
  "videos": [
    {
      "objectUrl": "Multi-Region-Access-Point-ARN + <object name_1>"
    },
    {
      "objectUrl": "Multi-Region-Access-Point-ARN + <object name_2>",
      "title": "my-custom-video-title.mp4",
      "clientMetadata": {"optional": "metadata"}
    }
  ],
  "skip_duplicate_urls": true
}

MRAP Example
{
  "videos": [
    {
      "objectUrl": "https://arn:aws:s3::123123123:accesspoint/frf28frarf9.mrap.s3-accesspoint.amazonaws.com/Videos/2022/video_1.mp4"
    },
    {
      "objectUrl": "https://arn:aws:s3::123123123:accesspoint/frf28frarf9.mrap.s3-accesspoint.amazonaws.com/Videos/2022/video_2.mp4",
      "title": "many-cute-cats.mp4",
      "clientMetadata": {"optional": "metadata"}
    }
  ],
  "skip_duplicate_urls": true
}

Create CSV File for Registration

In the CSV file format, the column headers specify which type of data is being uploaded. You can add and single file format at a time, or combine multiple data types in a single CSV file.

Details for each data format are given in the sections below.

Encord supports up to 10,000 entries for upload in the CSV file.

Object URLs can’t contain whitespace.
For backwards compatibility reasons, a single column CSV is supported. A file with the single ObjectUrl column is interpreted as a request for video upload. If your objects are of a different type (for example, images), this error displays: “Expected a video, got a file of type XXX”.

Videos

A CSV file containing videos should contain two columns with the following mandatory column headings:
‘ObjectURL’ and ‘Video title’. All headings are case-insensitive.

The ‘ObjectURL’ column containing the objectUrl. This field is mandatory for each file, as it specifies the full URL of the video resource.
The ‘Video title’ column containing the video_title. If left blank, the original file name is used.

In the example below files 1, 2 and 4 will be assigned the names in the title column, while file 3 will keep its original file name.

ObjectUrl	Video title
path/to/storage-location/frame1.mp4	Video 1
path/to/storage-location/frame2.mp4	Video 2
path/to/storage-location/frame3.mp4
path/to/storage-location/frame4.mp4	Video 3

A CSV file containing single images should contain two columns with the following mandatory headings:
‘ObjectURL’ and ‘Image title’. All headings are case-insensitive.

The ‘ObjectURL’ column containing the objectUrl. This field is mandatory for each file, as it specifies the full URL of the image resource.
The ‘Image title’ column containing the image_title. If left blank, the original file name is used.

In the example below files 1, 2 and 4 will be assigned the names in the title column, while file 3 will keep its original file name.

ObjectUrl	Image title
path/to/storage-location/frame1.jpg	Image 1
path/to/storage-location/frame2.jpg	Image 2
path/to/storage-location/frame3.jpg
path/to/storage-location/frame4.jpg	Image 3

Image groups

A CSV file containing image groups should contain three columns with the following mandatory headings:
‘ObjectURL’, ‘Image group title’, and ‘Create video’. All three headings are case-insensitive.

The ‘ObjectURL’ column containing the objectUrl. This field is mandatory for each file, as it specifies the full URL of the resource.
The ‘Image group title’ column containing the image_group_title. This field is mandatory, as it determines which image group a file will be assigned to.

In the example below the first two URLs are grouped together into ‘Group 1’, while the following two files are grouped together into ‘Group 2’.

ObjectUrl	Image group title	Create video
path/to/storage-location/frame1.jpg	Group 1	false
path/to/storage-location/frame2.jpg	Group 1	false
path/to/storage-location/frame3.jpg	Group 2	false
path/to/storage-location/frame4.jpg	Group 2	false

Image groups do not require ‘write’ permissions.

Image sequences

A CSV file containing image sequences should contain three columns with the following mandatory headings: ‘ObjectURL’, ‘Image group title’, and ‘Create video’. All three headings are case-insensitive.

The ‘ObjectURL’ column containing the objectUrl. This field is mandatory for each file, as it specifies the full URL of the resource.
The ‘Image group title’ column containing the image_group_title. This field is mandatory, as it determines which image sequence a file will be assigned to. The dimensions of the image sequence are determined by the first file in the sequence.
The ‘Create video’ column. This can be left blank, as the default value is ‘true’.

In the example below the first two URLs are grouped together into ‘Sequence 1’, while the second two files are grouped together into ‘Sequence 2’.

ObjectUrl	Image group title	Create video
path/to/storage-location/frame1.jpg	Sequence 1	true
path/to/storage-location/frame2.jpg	Sequence 1	true
path/to/storage-location/frame3.jpg	Sequence 2	true
path/to/storage-location/frame4.jpg	Sequence 2	true

Image groups and image sequences are only distinguished by the presence of the ‘Create video’ column.

Image sequences require ‘write’ permissions against your storage bucket to save the compressed video.

A CSV file containing DICOM files should contain two columns with the following mandatory headings: ‘ObjectURL’ and ‘Dicom title’. Both headings are case-insensitive.

The ‘ObjectURL’ column containing the objectUrl. This field is mandatory for each file, as it specifies the full URL of the resource.
The ‘Series title’ column containing the dicom_title. When two files are given the same title they are grouped into the same DICOM series. If left blank, the original file name is used.

In the example below the first two files are grouped into ‘dicom series 1’, the next two files are grouped into ‘dicom series 2’, while the final file will remain separated as ‘dicom series 3’.

ObjectUrl	Series title
path/to/storage-location/frame1.dcm	dicom series 1
path/to/storage-location/frame2.dcm	dicom series 1
path/to/storage-location/frame3.dcm	dicom series 2
path/to/storage-location/frame4.dcm	dicom series 2
path/to/storage-location/frame5.dcm	dicom series 3

Multiple file types

You can upload multiple file types with a single CSV file by using a new header each time there is a change of file type. Three headings will be required if image sequences are included.

Since the ‘Create video’ column defaults to true all files that are not image sequences must contain the value false

The example below shows a CSV file for the following:

Two image sequences composed of 2 files each.
One image group composed of 2 files.
One single image.
One video.

ObjectUrl	Image group title	Create video
path/to/storage-location/frame1.jpg	Sequence 1	true
path/to/storage-location/frame2.jpg	Sequence 1	true
path/to/storage-location/frame3.jpg	Sequence 2	true
path/to/storage-location/frame4.jpg	Sequence 2	true
path/to/storage-location/frame5.jpg	Group 1	false
path/to/storage-location/frame6.jpg	Group 1	false
ObjectUrl	Image title	Create video
path/to/storage-location/frame1.jpg	Image 1	false
ObjectUrl	Image title	Create video
full/storage/path/video.mp4	Video 1	false

Import or Register your data

STEP 2: Curate your Data

Curation of your data consists of sorting, filtering, using analytics, and embedding plots to create one or more Collections. Collections can then be made into a Dataset for use with your Annotate and Active Projects.

Filter and Sort Data

You can sort your data using a number of data unit metrics. The metrics available to sort your data depends on the data available in the Folder. You can sort your data in ascending and descending order.

Index has a number of criteria available to filter your data. You can only access filtering criteria that is available from the top-level Folder. For example, if you do not have any video or audio data in the top-level Folder or any sub-Folders, you cannot filter your data using those filtering criteria.

Adding key frames (for videos), custom metadata, and custom embeddings) to your data can all significantly improve the speed and effectiveness when filtering your data. We recommend importing customer metadata and custom embeddings with your data, but you can import custom metadata and embeddings after importing your data.

Criteria	Description
File Size	Filters files (video) based on their size in bytes.
Random Value	Filters files (video) based on a random value assigned as the file is added to Index.

Criteria	Description
Area	Filters videos based on the area of the frame.
Aspect Ratio	Filters videos based on the aspect ratio of the video.
Clip Duration	Filters videos based on the duration of the video by hundredths of seconds.
Frame per Second	Filters videos based on the frames per second of the video.
Height	Filters videos based on the height of the video frame.
No. of Video Frames	Filters videos based on the number of frames in the video.
Random Value	Filters videos based on a random value assigned as the file is added to Index.
Width	Filters videos based on the width of the video.

Criteria	Description
Area	Filters images/video frames based on the area of the frame.
Aspect Ratio	Filters images/video frames based on the aspect ratio of the video.
Frame Number	Filters images/video frames based on the height of the video frame.
Height	Filters images/video frames based on the height of the video frame.
Random Value	Filters images/video frames based on a random value assigned as the file is added to Index.
Width	Filters images/video frames based on the width of the video.

Criteria	Description
Bit Depth	Filters audio files based on the size of each sample (int) in bits.
Duration	Filters audio files based on the duration of the audio file by hundredths of seconds.
Number of Channels	Filters audio files based on number of audio channels in the audio file.
Random Value	Filters audio files based on a random value assigned as the file is added to Index.
Samples per Second	Filters audio files based on the number of samples per second.

Criteria	Description
Custom Metadata	Filters files by any custom metadata available on your data. For more information about custom metadata with Index, refer to our documentation
Custom Embeddings	Filters files by any custom embeddings available on your data. For more information about custom embeddings with Index, refer to our documentation
Key Frames	VIDEO ONLY Filters files by any key frames specified on frames in your video data. Specifying key frames on videos significantly speeds up importing videos in to Index. Index imports videos at 1 FPS by default.

Criteria

Description

Custom Metadata

Filters files by any custom metadata available on your data.

For more information about custom metadata with Index, refer to our documentation

Custom Embeddings

Filters files by any custom embeddings available on your data.

For more information about custom embeddings with Index, refer to our documentation

Key Frames

VIDEO ONLY

Filters files by any key frames specified on frames in your video data.

Specifying key frames on videos significantly speeds up importing videos in to Index.
Index imports videos at 1 FPS by default.

Criteria	Description
Collection	Filters files by the Collection the files belong to.
Data Title	Filters files their file name.
Data Type	Filters files their file type: Video, Audio, Image, Image Group, Image Sequence, DICOM Series
File ID	Filters files their unique file ID.
Folder	Filters files by the Folders that contain the files.
Integration	Filters files by the Integrations that contain the files.
Mime	Filters files the file’s Mime type.
Storage Location	Filters files by the storage location that contains the files.
Uploaded At	Filters files the time and date of their upload.

Use Custom Analytic Dashboards

You can create custom analytic dashboards using Distribution and Correlation charts. For more information on analytics dashboards, refer to our documentation.

Adding custom metadata to your data can significantly improve the insights you can gather from your data. We recommend importing customer metadata with your data, but you can import custom metadata after importing your data.

Custom Embeddings and Similarity Search

Adding custom embeddings to your data can significantly improve the insights you can gather from your data. We recommend importing customer embeddings with your data, but you can import custom embeddings after importing your data.

You must Upgrade the top-level Folder and select the custom embeddings to use embedding plot graphs and similarity search.

For information on upgrading your Folder and importing custom embeddings, refer to our documentation.

Custom Embeddings

Similarity Search

Create a Collection

Log in to the Encord platform. The landing page for the Encord platform appears.
Go to Index > Files. The All folders page appears with a list of all folders in Encord.
Click in to a Folder. The landing page for the Folder appears and the Explorer button is enabled.
Click the Explorer button. The Index Explorer page appears.
Search, sort, and filter your data until you have the subset of the data you need.
Select one or more of the images/frames/audio files in the Explorer workspace. A ribbon appears at the top of the Explorer workspace.

Selecting a video frame selects the entire video. Specific frames from a video cannot be selected.
Click Select all to select all the images in the subset.
Click Add to a Collection.
Click New Collection.
Specify a meaningful title and description for the Collection.

The title specified here is applied as a tag/label to every selected image.
Click Collections to verify the Collection appears in the Collections list.

STEP 3: Create a Dataset

Once you have a Collection, you can create a Dataset from your Collection.

Getting Started with Encord

Modalities

Custom Editor Layout

Agents

Benchmark QA Workflow