Universe

SEGV2 Computer Vision Dataset

byRohiniTask:
Instance Segmentation
License:CC BY 4.0660 views21 downloads
See all 438 imagesSEGV2 floor sample showing floorSEGV2 floor sample showing floorSEGV2 floor sample showing floorSEGV2 floor sample showing floorSEGV2 floor sample showing floorSEGV2 floor sample showing floorSEGV2 floor sample showing floorSEGV2 floor sample showing floorSEGV2 floor sample showing floorSEGV2 floor sample showing floorSEGV2 floor sample showing floorSEGV2 floor sample showing floor

About SEGV2 Dataset

Here are a few use cases for this project:

  1. Assisting in Interior Design: SEGV2 can be used by architects and interior designers to identify different floor types in a floor plan, helping in the selection and placement of furniture and other elements according to the unique characteristics of each floor class.

  2. Augmented Reality Applications: SEGV2 can be used in AR applications for enhancing user experience by recognizing floor types, enabling users to visualize how different flooring options would look in their homes or office spaces before making purchase decisions.

  3. Home and Building Maintenance: The model can help facility managers and homeowners in identifying specific floors that require maintenance, repair, or inspection for structural integrity, making it easier to prioritize tasks and allocate resources efficiently.

  4. Robotics Navigation: Autonomous robots like vacuum cleaners and delivery systems can utilize SEGV2 for better navigation by identifying and understanding different floor types and their unique properties, allowing for improved adaptability and optimization of cleaning, navigation, or delivery strategies.

  5. Accessibility and Safety Planning: SEGV2 can aid city planners and architects in identifying different floor classes in public spaces, enabling the implementation of tailored accessibility and safety features, such as installing the right slip-resistant materials on a particular type of flooring or deploying specific warning signs for visually impaired people.

Use Free Floor Detection API

Powered by general detection model

Code
pip install inference-sdk
# 1. Import the library
from inference_sdk import InferenceHTTPClient

# 2. Connect to your workspace
client = InferenceHTTPClient(
  api_url="https://serverless.roboflow.com",
  api_key="API_KEY"
)

# 3. Run your workflow on an image
result = client.run_workflow(
  workspace_name="<YOUR_WORKSPACE>",
  workflow_id="<YOUR_WORKFLOW_ID>",
  images={
    "image": "YOUR_IMAGE.jpg"  # Path to your image file
  },
  parameters={
    "classes": "floor"
  },
  use_cache=True  # cache workflow definition for 15 minutes
)

# 4. Get your results
print(result)

Run on custom image

Drop an image here or click to upload

Detecting classes:
Or try a test image 

Cite This Project

LicenseCC BY 4.0

If you use this dataset in a research paper, please cite it using the following BibTeX:

@misc{ segv2_dataset,
  title = { SEGV2 Dataset },
  type = { Open Source Dataset },
  author = { Rohini },
  howpublished = { \url{ https://universe.roboflow.com/rohini/segv2 } },
  url = { https://universe.roboflow.com/rohini/segv2 },
  journal = { Roboflow Universe },
  publisher = { Roboflow },
  year = { 2023 },
  month = { mar },
  note = { visited on 2026-07-29 },
}

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