Universe

batch_1 Computer Vision Dataset

byanntotators group oneTask:
Object Detection
License:CC BY 4.032 views4 downloads
See all 805 imagesbatch_1 parkingSpots sample showing invalidSpot-yellowCurbbatch_1 parkingSpots samplebatch_1 parkingSpots samplebatch_1 parkingSpots sample showing fireHydrant, invalidSpot-redCurbbatch_1 parkingSpots samplebatch_1 parkingSpots samplebatch_1 parkingSpots sample showing invalidSpot-entrance, invalidSpot-redCurb, spot-1batch_1 parkingSpots sample showing spot-1batch_1 parkingSpots sample showing spot-2batch_1 parkingSpots sample showing invalidSpot-entrance, invalidSpot-yellowCurbbatch_1 parkingSpots samplebatch_1 parkingSpots sample showing invalidSpot-yellowCurb

About batch_1 Dataset

Here are a few use cases for this project:

  1. Parking Management Application: batch_1 model can be used in a parking management app to monitor and track available, occupied, and invalid parking spots in real-time, helping drivers find available parking spaces while avoiding illegal parking locations.

  2. Traffic and Parking Enforcement: Law enforcement agencies can integrate the batch_1 model into surveillance systems to identify vehicles parked in invalid spots or near fire hydrants, allowing them to enforce parking rules and issue fines more efficiently.

  3. Urban Planning and Development: City planners can use batch_1 to analyze parking usage and allocation, ensuring proper distribution of parking spots and identifying areas where modification or additional parking infrastructure is needed.

  4. Mobility-as-a-Service Provider: Companies offering ride-sharing, car-sharing, or autonomous transportation services can incorporate batch_1 model to guide their vehicles to available parking spaces, avoid parking in invalid spots, and optimize the use of parking resources.

  5. Accessibility and Inclusivity: batch_1 model can help identify and monitor designated accessible parking spots, ensuring that they are available and unobstructed for people with disabilities, ensuring a more inclusive urban environment.

Use Free FireHydrant, InvalidSpot-entrance and InvalidSpot-fireHydrant 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": "fireHydrant, invalidSpot-entrance, invalidSpot-fireHydrant, invalidSpot-redCurb, invalidSpot-whiteCurb"
  },
  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{ batch_1_dataset,
  title = { batch_1 Dataset },
  type = { Open Source Dataset },
  author = { anntotators group one },
  howpublished = { \url{ https://universe.roboflow.com/anntotators-group-one/batch_1 } },
  url = { https://universe.roboflow.com/anntotators-group-one/batch_1 },
  journal = { Roboflow Universe },
  publisher = { Roboflow },
  year = { 2022 },
  month = { jan },
  note = { visited on 2026-07-29 },
}

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