Image Metadata

Metadata lets you attach custom key-value pairs to images in your Roboflow workspace. Use metadata to store structured information alongside your images — such as capture conditions, device identifiers, quality scores, or any domain-specific attributes — and then search, filter, and organize your data around those attributes.

Overview

Each image can hold any number of metadata entries. An entry is a key (a name like camera_id) paired with a value (a string, number, or boolean).

Value type	Examples
String	location: "warehouse-3", shift: "night"
Number	temperature: 72.5, quality_score: 95
Boolean	reviewed: true, is_night: false

Use cases

• Capture context — record camera ID, GPS coordinates, weather, lighting conditions

• Quality tracking — attach confidence scores, review status, annotator IDs

• Data slicing — filter your dataset by any attribute to build targeted training sets

• External system linking — store identifiers that connect images back to your internal tools

Adding Metadata

You can add metadata to images through the web UI, the Python SDK, the REST API, or automatically via S3 Bucket Mirror.

Web Application

1

Open an image

Open any image in your project.

2

Enter key and value

In the metadata section, enter a key in the first input and a value in the second input.

3

Add

Press Enter to save or click on Add

Values are automatically parsed by type:

Value entered	Stored as
front	"front" (string)
95	95 (number)
3.14	3.14 (number)
true / false	true / false (boolean)

Annotation Tool's metadata editor

Python SDK

Pass a metadata dictionary when uploading an image:

import roboflow

rf = roboflow.Roboflow(api_key="YOUR_API_KEY")
project = rf.workspace("your-workspace").project("your-project")

project.upload(
    image_path="image.jpg",
    metadata={
        "camera_id": "cam001",
        "location": "warehouse-3",
        "temperature": 72.5,
        "is_night": False
    }
)

REST API

Add metadata during upload

Include a metadata field (JSON-stringified) in the multipart form data when uploading an image:

curl -X POST "https://api.roboflow.com/dataset/your-dataset/upload?api_key=YOUR_API_KEY" \
  -F "name=image.jpg" \
  -F "split=train" \
  -F "[email protected]" \
  -F 'metadata={"camera_id":"cam001","temperature":72.5}'

S3 Bucket Mirror

When using Bucket Mirror to sync images from an S3 bucket, you can attach metadata by placing a .json file alongside each image with the same base name:

my-bucket/
  images/
    photo_001.jpg
    photo_001.json      # metadata for photo_001.jpg
    photo_002.jpg
    photo_002.json      # metadata for photo_002.jpg

The JSON file contains your metadata as key-value pairs:

{
    "camera_id": "cam001",
    "location": "warehouse-3",
    "capture": { "temperature": 72.5, "humidity": 45 }
}

Nested objects are automatically flattened using dot notation. The example above produces:

Key	Value
camera_id	"cam001"
location	"warehouse-3"
capture.temperature	72.5
capture.humidity	45

Metadata file constraints

• Maximum file size: 256 KB

• Must be valid JSON

• null and undefined values are filtered out

Update strategies

Bucket Mirror supports different strategies for how synced metadata interacts with metadata you've set manually in the UI or via API:

Strategy	Behavior
mergeBucketWins (default)	Merges both sources. On key conflicts, the bucket value wins.
mergeUserWins	Merges both sources. On key conflicts, the user-set value wins.
overwrite	Bucket metadata completely replaces all existing metadata.
untilFirstChange	Syncs from bucket until a user manually edits metadata, then stops updating.
append	Only adds new keys from the bucket. Never overwrites existing keys.

Searching by Metadata

Metadata is indexed and searchable in the Asset Library. Use the search bar to filter images by metadata values:

metadata.camera_id:"cam001"
metadata.quality_score>80
metadata.reviewed:true

You can combine metadata filters with other search filters:

metadata.location:"warehouse-3" AND class:forklift

The Asset Library also provides autocomplete for metadata keys and values based on what exists in your workspace.

Key Naming Rules

Metadata keys must follow these rules:

Rule	Detail
Allowed characters	Letters (a-z, A-Z), numbers (0-9), underscores (_), dots (.)
First character	Must be a letter, number, or underscore
Forbidden characters	Forward slashes (/) are not allowed

Valid keys: camera_id, capture.temperature, _internal_ref, v2_score

Invalid keys: camera/id (contains /), .starts_with_dot (starts with .), has spaces (contains spaces)

Metadata vs. Tags

Both metadata and tags help you organize images, but they serve different purposes:

	Tags	Metadata
Structure	Simple labels	Key-value pairs
Values	No value, just a name	String, number, or boolean
Best for	Categorization, workflow status	Structured attributes, measurements
Example	reviewed, v2, needs-annotation	temperature: 72.5, camera_id: "cam001"

You can use both on the same image. For example, tag an image as reviewed and also store reviewer: "alice" and confidence: 0.95 as metadata.