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Uploading Local Data to Files

You can upload up to 250 local files at a time.
Any files you upload to Encord must be stored in folders. Click here to learn how to create a folder to store your files.
  1. Navigate to Files under the Index heading in the Encord platform.
  2. Click the +Upload files button
You can also right-click a folder to add data.
  1. Select a folder to upload your files to. You can click +New folder to create a new folder.
  2. Select the type of data you want to add.
  • A - Upload : Drag and drop local images, text, or video files. Click Upload to finish.
  • B - Batch images as : Create an image group or image sequence from local images. See our section on creating image groups and image sequences for more information. Click Upload and batch images to finish.
  • C - Audio Drag and drop local audio files. Click Upload to finish.
  • D - DICOM : Create a DICOM series from local DICOM files. Click Upload to finish.
To import DICOM files, Encord requires the files to have the following DICOM tags:Rows Columns StudyInstanceUID SeriesInstanceUID SOPInstanceUID PatientID The following DICOM tags are required to render DICOM images in 3D:ImagePositionPatient ImageOrientationPatient SliceThickness PixelSpacing
  • E - Import from private cloud : Add any data stored in your cloud storage. At least one data integration is required to register cloud data. Learn how to upload private cloud data here. Click Import to finish.

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Custom metadata

Custom metadata can only be added through the Encord SDK.
Custom metadata, also known as client metadata, is supplementary information you can add to all data imported into, or registered with Encord. It is provided in the form of a Python dictionary, as shown in examples. Client metadata serves several key functions: You can optionally add some custom metadata per data item in the clientMetadata field (examples show how this is done) of your JSON file.
We enforce a 10MB limit on the custom metadata for each data item. Internally, we store custom metadata as a PostgreSQL jsonb type. Read the relevant PostgreSQL documentation about the jsonb type and its behaviors. For example, jsonb type does not preserve key order or duplicate keys.

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Metadata schema

Metadata schemas, including custom embeddings, can only be imported through the Encord SDK.
Based on your Data Discoverability Strategy, you need to create a metadata schema. The schema provides a method of organization for your custom metadata. Encord supports:
  • Scalars: Methods for filtering.
  • Enums: Methods with options for filtering.
  • Embeddings: Method for embedding plot visualization, similarity search, and natural language search.
Metadata Schema keys support letters (a-z, A-Z), numbers (0-9), and the following blank spaces ( ), hyphens (-), underscores (_), and periods (.).

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Custom metadata

Custom metadata refers to any additional information you attach to files, allowing for better data curation and management based on your specific needs. It can include any details relevant to your workflow, helping you organize, filter, and retrieve data more efficiently. For example, for a video of a construction site, custom metadata could include fields like "site_location": "Algiers", "project_phase": "foundation", or "weather_conditions": "sunny". This enables more precise tracking and management of your data. Before importing any files with custom metadata to Encord, we recommend that you import a metadata schema. Encord uses metadata schemas to validate custom metadata uploaded to Encord and to instruct Index and Active how to display your metadata.
To handle your custom metadata schema across multiple teams within the same organization, we recommend using namespacing for metadata keys in the schema. This ensures that different teams can define and manage their own metadata schema without conflicts. For example, team A could use video.description, while team B could use audio.description. Another example could be TeamName.MetadataKey. This approach maintains clarity and avoids key collisions across departments.

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Metadata schema table

Metadata Schema keys support letters (a-z, A-Z), numbers (0-9), and blank spaces ( ), hyphens (-), underscores (_), and periods (.). Metadata schema keys are case sensitive.
Use add_scalar to add a scalar key to your metadata schema.
Scalar KeyDescriptionDisplay Benefits
booleanBinary data type with values “true” or “false”.Filtering by binary values
datetimeISO 8601 formatted date and time.Filtering by time and date
numberNumeric data type supporting float values.Filtering by numeric values
uuidUUIDv4 formatted unique identifier for a data unit.Filtering by customer specified unique identifier
varcharTextual data type. Formally string. string can be used as an alias for varchar, but we STRONGLY RECOMMEND that you use varchar.Filtering by string.
textText data with unlimited length (example: transcripts for audio). Formally long_string. long_string can be used as an alias for text, but we STRONGLY RECOMMEND that you use text.Storing and filtering large amounts of text.
Use add_enum and add_enum_options to add an enum and enum options to your metadata schema.
KeyDescriptionDisplay Benefits
enumEnumerated type with predefined set of values.Facilitates categorical filtering and data validation
Use add_embedding to add an embedding to your metadata schema.
KeyDescriptionDisplay Benefits
embedding1 to 4096 for Index. 1 to 2000 for Active.Filtering by embeddings, similarity search, 2D scatter plot visualization (Coming Soon)
Incorrectly specifying a data type in the schema can cause errors when filtering your data in Index or Active. If you encounter errors while filtering, verify your schema is correct. If your schema has errors, correct the errors, re-import the schema, and then re-sync your Active Project.

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Import your metadata schema to Encord


# Import dependencies
from encord import EncordUserClient
from encord.metadata_schema import MetadataSchema

SSH_PATH = "<file-path-to-ssh-private-key>"

# Authenticate with Encord using the path to your private key
user_client: EncordUserClient = EncordUserClient.create_with_ssh_private_key(
    ssh_private_key_path=SSH_PATH
)

# Create the schema
metadata_schema = user_client.metadata_schema()

# Add various metadata fields
metadata_schema.add_scalar("metadata_1", data_type="boolean")
metadata_schema.add_scalar("metadata_2", data_type="datetime")
metadata_schema.add_scalar("metadata_3", data_type="number")
metadata_schema.add_scalar("metadata_4", data_type="uuid")
metadata_schema.add_scalar("metadata_5", data_type="varchar")
metadata_schema.add_scalar("metadata_6", data_type="text")

# Add an enum field
metadata_schema.add_enum("my-enum", values=["enum-value-01", "enum-value-02", "enum-value-03"])

# Add embedding fields
metadata_schema.add_embedding('my-test-active-embedding', size=512)
metadata_schema.add_embedding('my-test-index-embedding', size=<values-from-1-to-4096>)

# Save the schema
metadata_schema.save()

# Print the schema for verification
print(metadata_schema)

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Verify your schema

After importing your schema to Encord we recommend that you verify that the import is successful. Run the following code to verify your metadata schema imported and that the schema is correct. 

# Import dependencies
from encord import EncordUserClient
from encord.metadata_schema import MetadataSchema

SSH_PATH = "<file-path-to-ssh-private-key>"

# Authenticate with Encord using the path to your private key
user_client: EncordUserClient = EncordUserClient.create_with_ssh_private_key(
    ssh_private_key_path=SSH_PATH
)

# Create the schema
metadata_schema = user_client.metadata_schema()

# Print the schema for verification
print(metadata_schema)