Is it free to convert Unity Perception JSON to Segment Anything 2?
Yes! It is free to convert Unity Perception JSON data into the Segment Anything 2 format on the Roboflow platform.
Convert annotation formats
How to Convert Unity Perception JSON to Segment Anything 2
In this guide, we show you how to convert data between the Unity Synthetic Data and Segment Anything 2 formats for free. You can use your converted data to train models and other models that support the Segment Anything 2 format.
Unity Perception JSONtoSegment Anything 2
Unity Perception JSON
Unity Perception is a toolkit for generating datasets for computer vision by using 3D renders.
Below, learn the structure of Unity Perception JSON.
captures_000.jsonJSON
{
"version": "0.0.1",
"captures": [{
"id": "b49f1317-f3ce-42e3-8201-b85b0bd1574b",
"sequence_id": "96bf8ade-5d77-49a4-82e2-dc1ef567ab82",
"step": 0,
"timestamp": 10.0,
"sensor": {
"sensor_id": "edf45916-afec-9881-8d21-922241c54310",
"ego_id": "1ceb788a-8155-4860-99da-2b406536f198",
"modality": "camera",
"translation": [
0.0,
0.0,
0.0
],
"rotation": [
0.0,
0.0,
0.0,
1.0
],
"camera_intrinsic": [
[
0.999999762,
0.0,
0.0
],
[
0.0,
1.77777731,
0.0
],
[
0.2,
0.266666651,
-1.0006001
]
]
},
"ego": {
"ego_id": "1ceb788a-8155-4860-99da-2b406536f198",
"translation": [
-595.11,
1175.75,
487.64
],
"rotation": [
0.0778284,
0.9212198,
-0.246840149,
0.290459484
],
"velocity": null,
"acceleration": null
},
"filename": "RGB2327d665-d71f-4c4f-8c77-66df8fa29202/rgb_2.png",
"format": "PNG",
"annotations": [{
"id": "a6aef966-1fb3-4d59-91df-a44866e81038",
"annotation_definition": "f9f22e05-443f-4602-a422-ebe4ea9b55cb",
"values": [{
"label_id": 1,
"label_name": "person",
"instance_id": 2,
"x": 875.0,
"y": 303.0,
"width": 151.0,
"height": 122.0
},
{
"label_id": 1,
"label_name": "person",
"instance_id": 3,
"x": 1226.0,
"y": 382.0,
"width": 181.0,
"height": 130.0
},
{
"label_id": 1,
"label_name": "person",
"instance_id": 1,
"x": 660.0,
"y": 402.0,
"width": 148.0,
"height": 112.0
},
{
"label_id": 1,
"label_name": "person",
"instance_id": 5,
"x": 1003.0,
"y": 381.0,
"width": 148.0,
"height": 141.0
},
{
"label_id": 1,
"label_name": "person",
"instance_id": 42,
"x": 831.0,
"y": 389.0,
"width": 230.0,
"height": 225.0
}
]
}]
},
{
"id": "87182978-7b34-4157-85f2-9fa0b57af085",
"sequence_id": "96bf8ade-5d77-49a4-82e2-dc1ef567ab82",
"step": 1,
"timestamp": 20.0,
"sensor": {
"sensor_id": "edf45916-afec-9881-8d21-922241c54310",
"ego_id": "1ceb788a-8155-4860-99da-2b406536f198",
"modality": "camera",
"translation": [
0.0,
0.0,
0.0
],
"rotation": [
0.0,
0.0,
0.0,
1.0
],
"camera_intrinsic": [
[
0.999999762,
0.0,
0.0
],
[
0.0,
1.77777731,
0.0
],
[
0.2,
0.266666651,
-1.0006001
]
]
},
"ego": {
"ego_id": "1ceb788a-8155-4860-99da-2b406536f198",
"translation": [
-595.11,
1175.75,
487.64
],
"rotation": [
0.0778284,
0.9212198,
-0.246840149,
0.290459484
],
"velocity": null,
"acceleration": null
},
"filename": "RGB2327d665-d71f-4c4f-8c77-66df8fa29202/rgb_3.png",
"format": "PNG",
"annotations": [{
"id": "94bffb82-7753-4d79-8294-66e2976d7362",
"annotation_definition": "f9f22e05-443f-4602-a422-ebe4ea9b55cb",
"values": [{
"label_id": 1,
"label_name": "person",
"instance_id": 2,
"x": 875.0,
"y": 303.0,
"width": 151.0,
"height": 122.0
},
{
"label_id": 1,
"label_name": "person",
"instance_id": 3,
"x": 1226.0,
"y": 382.0,
"width": 181.0,
"height": 130.0
},
{
"label_id": 1,
"label_name": "person",
"instance_id": 1,
"x": 660.0,
"y": 402.0,
"width": 148.0,
"height": 112.0
},
{
"label_id": 1,
"label_name": "person",
"instance_id": 5,
"x": 1003.0,
"y": 381.0,
"width": 149.0,
"height": 142.0
},
{
"label_id": 1,
"label_name": "person",
"instance_id": 42,
"x": 831.0,
"y": 389.0,
"width": 230.0,
"height": 225.0
},
{
"label_id": 1,
"label_name": "person",
"instance_id": 4,
"x": 1317.0,
"y": 455.0,
"width": 201.0,
"height": 166.0
},
{
"label_id": 1,
"label_name": "person",
"instance_id": 33,
"x": 454.0,
"y": 462.0,
"width": 213.0,
"height": 216.0
},
{
"label_id": 1,
"label_name": "person",
"instance_id": 13,
"x": 899.0,
"y": 504.0,
"width": 308.0,
"height": 286.0
},
{
"label_id": 1,
"label_name": "person",
"instance_id": 16,
"x": 222.0,
"y": 501.0,
"width": 189.0,
"height": 290.0
},
{
"label_id": 4,
"label_name": "hard-hat",
"instance_id": 38,
"x": 295.0,
"y": 685.0,
"width": 113.0,
"height": 173.0
},
{
"label_id": 1,
"label_name": "person",
"instance_id": 10,
"x": 40.0,
"y": 630.0,
"width": 202.0,
"height": 252.0
},
{
"label_id": 12,
"label_name": "car",
"instance_id": 46,
"x": 827.0,
"y": 712.0,
"width": 257.0,
"height": 229.0
},
{
"label_id": 1,
"label_name": "person",
"instance_id": 26,
"x": 1402.0,
"y": 810.0,
"width": 254.0,
"height": 187.0
},
{
"label_id": 13,
"label_name": "bicycle",
"instance_id": 7,
"x": 667.0,
"y": 641.0,
"width": 298.0,
"height": 394.0
},
{
"label_id": 5,
"label_name": "door",
"instance_id": 31,
"x": 1143.0,
"y": 839.0,
"width": 652.0,
"height": 241.0
}
]
}]
}]
}Segment Anything 2
SAM-2 uses a custom dataset format for use in fine-tuning models. You can convert and export data to the SAM 2 format in Roboflow.
Below, learn the structure of Segment Anything 2.
JSON
{"image":{"image_id":3,"license":1,"file_name":"A2_jpg.rf.1aa89274b154e74a1f960fbb192c6bf2.jpg","height":416,"width":416,"date_captured":"2024-10-07T11:35:58+00:00"},"annotations":[{"id":3,"bbox":[92,153,193.077471,199.115617],"area":38444.7397669646,"segmentation":{"counts":"...","size":[416,416]}}]}Step 1: Create a free Roboflow public workspace
Roboflow is a universal conversion tool for computer vision annotation formats. The Public plan is the best way for those exploring personal projects, class assignments, and other experiments to try Roboflow. To convert your dataset, start by creating a free workspace on the Public plan.
Step 2: Upload your data into Roboflow
Once your account has been created, click Create New Project.
Upload your data to Roboflow by dragging and dropping your Unity Perception JSON images and annotations into the upload space.
Step 3: Generate Dataset Version
Next, click "Generate New Version" to generate a new version of your dataset:
You can then apply any preprocessing or augmentation steps to your dataset:
Step 4: Export Dataset Version
After generating, you will be prompted to Export your dataset. You can choose to receive your dataset as a .zip file or a curl download link. Choose Segment Anything 2 when asked in what format you want to export your data. You will see a dropdown with various options like this:
Congratulations, you have successfully converted your dataset from Unity Perception JSON format to Segment Anything 2 format!
Video Tutorial
Convert Computer Vision Annotation Formats Tutorial
Want to dive deeper into converting annotation formats with Roboflow? In the tutorial below, we explore how to convert your data in the Roboflow dashboard. We also discuss rejecting annotations and train-test-validation splits.
Frequently Asked Questions
Yes! It is free to convert Unity Perception JSON data into the Segment Anything 2 format on the Roboflow platform.
If you have between a few and a few thousand images, converting data between these formats will be quick. But, the time it takes to convert between data formats increases with the more images you have.
Convert Unity Perception JSON to other formats
- COCO JSON
- COCO Run-Length Encoding (RLE)
- CreateML JSON
- Florence-2
- Google Cloud AutoML Vision CSV
- meituan/yolov6
- Multiclass Classification CSV
- OpenAI CLIP Classification
- OpenAI GPT-4o Object Detection JSONL
- PaliGemma JSONL
- Pascal VOC XML
- RetinaNet Keras CSV
- Sagemaker GroundTruth Manifest
- Scaled-YOLOv4 TXT
- Tensorflow Object Detection CSV
- Tensorflow TFRecord
- YOLO Darknet TXT
- YOLO Keras TXT
- YOLOv10 PyTorch TXT
- YOLOv11 PyTorch TXT
- YOLOv4 PyTorch TXT
- YOLOv5 Oriented Bounding Boxes
- YOLOv5 PyTorch TXT
- YOLOv7 PyTorch TXT
- YOLOv8 Oriented Bounding Boxes
- YOLOv8 PyTorch TXT
- YOLOv9 PyTorch TXT
Convert other formats to Segment Anything 2
- How to Convert Cloud Annotations JSON to Segment Anything 2
- How to Convert COCO JSON to Segment Anything 2
- How to Convert COCO Run-Length Encoding RLE to Segment Anything 2
- How to Convert Cogniac to Segment Anything 2
- How to Convert PaliGemma JSONL to Segment Anything 2
- How to Convert Pascal VOC XML to Segment Anything 2
- How to Convert SuperAnnotate JSON to Segment Anything 2
- How to Convert YOLOv10 PyTorch TXT to Segment Anything 2
- How to Convert YOLOv11 PyTorch TXT to Segment Anything 2
- How to Convert YOLOv8 PyTorch TXT to Segment Anything 2
- How to Convert YOLOv8 PyTorch TXT to Segment Anything 2
- How to Convert YOLOv9 PyTorch TXT to Segment Anything 2