RENOVIA-TEST1 Computer Vision Dataset

byDataset HVACTask:
Object Detection
License:CC BY 4.045 views2 downloads

About RENOVIA-TEST1 Dataset

Here are a few use cases for this project:

  1. Construction and Renovation Planning: RENOVIA-TEST1 can be used by architects, engineers, and construction managers to quickly identify different building components within images of existing structures. They can use this information to plan targeted renovations or alterations, understanding the layout of the various elements within the space.

  2. Real Estate and Facility Management: Real estate agents and facility managers can use the RENOVIA-TEST1 model to create detailed summaries of the features and objects within properties. This will allow them to effectively market properties and create comprehensive facility inventories, ensuring accurate descriptions and valuable information is available for potential buyers or tenants.

  3. Energy Efficiency Audits: Energy auditors and consultants can use RENOVIA-TEST1 to identify essential building components, such as windows, doors, ventilation systems, and radiators, within images of residential or commercial spaces. By understanding the type and location of these components, they can better provide recommendations for energy efficiency improvements or retrofits.

  4. Interior Design and Space Planning: Interior designers and space planners can use RENOVIA-TEST1 to gain insights into the existing layout of building objects within an image of a room. They can then accurately determine the possibilities for rearranging or redesigning the space, ensuring a well-planned and aesthetically pleasing final design.

  5. Maintenance and Repair Management: Property owners, maintenance teams, and repair service providers can utilize RENOVIA-TEST1 to quickly identify building components in need of repair or maintenance. By locating specific objects like radiators, air conditioning units, or lighting fixtures, they can better diagnose and address repair issues, leading to a more efficient maintenance process.

Use Free Bouche d-aeration, Bouche d'aération and Climatiseur Type 1 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": "Bouche d-aeration, Bouche d'aération, Climatiseur Type 1, Dalle, Fenetre Type 1"
  },
  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{ renovia-test1_dataset,
  title = { RENOVIA-TEST1 Dataset },
  type = { Open Source Dataset },
  author = { Dataset HVAC },
  howpublished = { \url{ https://universe.roboflow.com/dataset-hvac/renovia-test1 } },
  url = { https://universe.roboflow.com/dataset-hvac/renovia-test1 },
  journal = { Roboflow Universe },
  publisher = { Roboflow },
  year = { 2022 },
  month = { sep },
  note = { visited on 2026-07-29 },
}

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