Formats
Florence-2
Object Detection
Object DetectionIMPORTEXPORT
FEATURED
Object Detection

Florence-2

The data format used by the Florence-2 multimodal model.

Overview

Florence-2 uses a text-based format for annotations. You can use annotated data to fine-tune Florence-2 for tasks like object detection.

Format Description

Below, learn the structure of Florence-2.

Split and Merge Datasets

With Roboflow supervision, an open source Python package with utilities for completing computer vision tasks, you can merge and split detections in Florence-2. Read our dedicated guides to learn how to merge and split Florence-2 detections.

Split detections in Florence-2

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Merge detections in Florence-2

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Supported Models

Below, see model architectures that require data in the Florence-2 format when training a new model.

On each page below, you can find links to our guides that show how to plot predictions from the model, and complete other common tasks like detecting small objects with the model.

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Formats
Florence-2

What is Florence-2?

Florence-2 uses a text-based format for annotations. You can use annotated data to fine-tune Florence-2 for tasks like object detection.

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Florence-2

Below, we show how to convert data to and from

Florence-2

. We also list popular models that use the

Florence-2

data format. Our conversion tools are free to use.

CONVERT To
CONVERT From
EXAMPLE

Convert Data to Florence-2

Use Roboflow to convert
Florence-2
to the following formats.

Roboflow is a trusted solution for converting and managing your data. Today, over 250,000 datasets are managed on Roboflow, comprised of 100 million labeled and annotated images.

With Roboflow, you get a solution with:
‍

Free data conversion

SOC II Type 2 Compliant

Trusted by 250,000+ developers

Convert Data from Florence-2

Use Roboflow to convert the following formats to
Florence-2
format.

Roboflow is a trusted solution for converting and managing your data. Today, over 250,000 datasets are managed on Roboflow, comprised of 100 million labeled and annotated images.

With Roboflow, you get:
‍

Free data conversion

SOC II Type 1 Compliant

Trusted by 250,000+ developers

YOLOv8 PyTorch TXT
to
Florence-2
Cogniac
to
Florence-2
Unity Perception JSON
to
Florence-2
LabelBox Video JSON
to
Florence-2
IBM Cloud Annotations JSON
to
Florence-2
SuperAnnotate JSON
to
Florence-2
LabelMe JSON
to
Florence-2
Multiclass Classification CSV
to
Florence-2
Google Cloud AutoML Vision CSV
to
Florence-2
Kaggle Wheat CSV
to
Florence-2
OIDv4 TXT
to
Florence-2
Tensorflow Object Detection CSV
to
Florence-2
RetinaNet Keras CSV
to
Florence-2
Sagemaker GroundTruth Manifest
to
Florence-2
Udacity TXT
to
Florence-2
VoTT CSV
to
Florence-2
VoTT JSON
to
Florence-2
OpenImages CSV
to
Florence-2
YOLO Darknet TXT
to
Florence-2
YOLO Keras TXT
to
Florence-2
Marmot XML
to
Florence-2
Pascal VOC XML
to
Florence-2
LabelBox JSON
to
Florence-2
Supervisely JSON
to
Florence-2
Scale AI JSON
to
Florence-2
CreateML JSON
to
Florence-2
COCO JSON
to
Florence-2
YOLOv10 PyTorch TXT
to
Florence-2
PaliGemma JSONL
to
Florence-2
Roboflow is a trusted solution for converting and managing your data. Today, over 100,000 datasets are managed on Roboflow, comprised of 100 million labeled and annotated images.

Once your data is in Roboflow, just add the link from your dataset and you're ready to go. We even include the code to export to common inference formats like TFLite, ONNX, and CoreML.

Below are pre-configured models that use the
Florence-2
data format
.

What computer vision models use Florence-2?

The

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models all use the

Florence-2

data format.

We don't currently have models that use this annotation format.
To see our entire list of computer vision models, check out the Roboflow Model Library.
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