An open-source tool for creating image segmentation datasets from videos using SAM 2
Project description
ViVa-SAFELAND: Dataset Creation Tool
ViVa-SAFELAND is an open-source tool for creating semantic segmentation datasets by tracking objects of interest from videos. It leverages the SAM 2 (Segment Anything Model 2) and YOLO AI models to perform segmentation and object detection, guiding users through an 8-step process to generate complete datasets ready for model training.
This tool focuses on generating semantic segmentation datasets through object tracking, utilizing SAM 2 to enhance segmentation accuracy.
Key Features
- Video-to-Dataset Conversion: Transform videos into high-quality segmentation datasets with minimal manual effort.
- SAM 2 Integration: Utilize the latest Segment Anything Model 2 for accurate and interactive segmentation.
- 8-Step Guided Process: Step-by-step workflow ensuring comprehensive dataset creation from frame extraction to final composition.
- Interactive Refinement: Manually refine segmentations for precision and quality control.
- Object Tracking Integration: Utilize YOLO and DeepSort for tracking objects of interest across video frames.
- Batch Processing: Efficiently handle large videos through configurable batch processing.
- Customizable Classes: Define and assign custom object classes with unique colors.
- Safety-Focused: Designed for safe and reliable dataset generation without hardware risks.
Documentation
For detailed usage instructions, examples, and API documentation, please refer to the ViVa-DataCreator Documentation.
Citation
If you use ViVa-DataCreator in your research, please cite our work:
@software{soriano_garcia_viva_datacreator_2025,
author = {Miguel Soriano-García, Diego Mercado-Ravell, Israel Becerra and Julio De La Torre-Vanegas},
title = {ViVa-DataCreator: Dataset Creation Tool},
year = {2025},
url = {https://github.com/viva-safeland/viva_datacreator}
}
Project details
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
Built Distribution
Filter files by name, interpreter, ABI, and platform.
If you're not sure about the file name format, learn more about wheel file names.
Copy a direct link to the current filters
File details
Details for the file viva_datacreator-0.0.5.tar.gz.
File metadata
- Download URL: viva_datacreator-0.0.5.tar.gz
- Upload date:
- Size: 64.5 kB
- Tags: Source
- Uploaded using Trusted Publishing? Yes
- Uploaded via: twine/6.1.0 CPython/3.13.7
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
a402cee17235407ab52d6566592b4adea86b1af890a2a96daf143028f77233e9
|
|
| MD5 |
4c6e91d29bb96ff562d449f5975aaf87
|
|
| BLAKE2b-256 |
d819ca688f0b738507b25233759c2ca22d5abf5d73606880b6e6615f91f7a051
|
File details
Details for the file viva_datacreator-0.0.5-py3-none-any.whl.
File metadata
- Download URL: viva_datacreator-0.0.5-py3-none-any.whl
- Upload date:
- Size: 96.8 kB
- Tags: Python 3
- Uploaded using Trusted Publishing? Yes
- Uploaded via: twine/6.1.0 CPython/3.13.7
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
9097a50bf67a41e1c43554e8f0511757f6550768d5e3f7623605ca026f2e9f27
|
|
| MD5 |
a922a330f46339b217274b24ddb8419e
|
|
| BLAKE2b-256 |
b7fcdd2903b75a2e7f919379fe7c2258221eacde60c0e937b3d47e55f6c51b4e
|