flat-with-potentials Computer Vision Dataset

byhashwideTask:
Object Detection
License:CC BY 4.0115 views3 downloads

About flat-with-potentials Dataset

Here are a few use cases for this project:

  1. Real Estate Platform Enhancement: Integrate the "flat-with-potentials" model into a real estate listing platform to automatically categorize and tag property images based on room types, allowing for better searchability and user experience when browsing properties with specific room configurations.

  2. Interior Design Inspiration: Develop an app or a feature within existing interior design platforms that curates design ideas based on the room classes. Users could upload images of their homes, and the "flat-with-potentials" model would identify room classes to present targeted inspiration for designing their spaces.

  3. Home Renovation Assistance: Employ the computer vision model within a home renovation app to help homeowners identify potential remodeling projects by analyzing existing room layouts and available space, focusing on kitchen upgrades, expansions, and other modifications.

  4. Accessibility Evaluation: Utilize the "flat-with-potentials" computer vision model to assess room layouts in buildings and homes for compliance with accessibility standards. This can help architects, builders, and property managers make necessary modifications to create inclusive living environments.

  5. Virtual Reality (VR) and Augmented Reality (AR) Applications: Implement the computer vision model within VR/AR applications for architectural visualization, interior design mockups, and real estate tours. The model could automatically identify room classes for easy navigation, editing, and customization within the virtual environment.

Use Free Kitchen 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": "kitchen"
  },
  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{ flat-with-potentials_dataset,
  title = { flat-with-potentials Dataset },
  type = { Open Source Dataset },
  author = { hashwide },
  howpublished = { \url{ https://universe.roboflow.com/hashwide-9wmoa/flat-with-potentials } },
  url = { https://universe.roboflow.com/hashwide-9wmoa/flat-with-potentials },
  journal = { Roboflow Universe },
  publisher = { Roboflow },
  year = { 2023 },
  month = { mar },
  note = { visited on 2026-07-29 },
}

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