Universe

Malam Computer Vision Dataset

by7 Class MalamTask:
Object Detection
License:CC BY 4.0130 views6 downloads
See all 5k imagesMalam vehicle sample showing car, truck_l, truck_sMalam vehicle sample showing truck_l, truck_sMalam vehicle sample showing truck_lMalam vehicle sample showing bus_l, car, truck_l, truck_xlMalam vehicle sample showing bus_l, car, truck_mMalam vehicle sample showing car, truck_xlMalam vehicle sample showing car, truck_xlMalam vehicle sample showing bus_l, car, truck_lMalam vehicle sample showing car, truck_l, truck_mMalam vehicle sample showing bus_l, car, truck_mMalam vehicle sample showing bus_l, car, truck_sMalam vehicle sample showing car, truck_l, truck_s

About Malam Dataset

Here are a few use cases for this project:

  1. Traffic Management: The Malam model can be used by traffic management authorities to automatically recognize the types of vehicles on roads, helping in real-time traffic analysis, such as identifying traffic congestion, planning route diversions, or even detecting unauthorized vehicular presence in restricted zones.

  2. Road Infrastructure Planning: Urban planners and civil engineers can use the Malam to analyze vehicle types commonly using certain routes. This data can inform road design upgrades by identifying the need for heavier-duty infrastructure for areas with frequent heavy trucks traffic.

  3. Intelligent Surveillance Systems: The Malam model can be integrated into surveillance systems to automatically identify and classify vehicles at night, allowing agencies to monitor vehicle movement, detect suspicious activities, or perform after-crime investigations.

  4. Night-time Vehicle Inspection at Borders: Customs or border protection agencies could use Malam to assist in monitoring and recording vehicle types crossing borders during night hours.

  5. Commercial Logistic Monitoring: Commercial transportation or logistic companies can use this model to automatically classify types of their vehicles on the roads during night hours for effective fleet management. It could also potentially detect unauthorized use or deviations from specified routes.

Use Free Car, Bus_l and Bus_s 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": "car, bus_l, bus_s, truck_l, truck_m"
  },
  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{ malam_dataset,
  title = { Malam Dataset },
  type = { Open Source Dataset },
  author = { 7 Class Malam },
  howpublished = { \url{ https://universe.roboflow.com/7-class-malam/malam } },
  url = { https://universe.roboflow.com/7-class-malam/malam },
  journal = { Roboflow Universe },
  publisher = { Roboflow },
  year = { 2024 },
  month = { aug },
  note = { visited on 2026-07-29 },
}

Similar Projects

See More