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Track objects in video
Car Counting

Car Counting

Detect and track cars in a video

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What is Car Counting ?

Car Counting is an advanced AI-powered tool designed to detect and track cars in video footage. It leverages cutting-edge computer vision technology to accurately count vehicles, track their movement, and provide detailed analytics. This solution is particularly useful for traffic monitoring, parking management, and urban planning applications.

Features

• Real-Time Detection: Identifies cars in live or recorded video streams with high accuracy. • Object Tracking: Follows vehicles across frames to avoid double-counting and monitor direction of travel. • Automated Counting: Provides precise counts of vehicles entering or exiting a specified area. • Direction Detection: Determines the movement direction of vehicles (e.g., entering or exiting). • Speed Measurement: Estimates vehicle speed based on consecutive frame analysis. • Data Export: Generates reports in customizable formats for further analysis. • Customizable Alerts: Triggers notifications when predefined thresholds are met.

How to use Car Counting ?

  1. Upload Video: Import your video footage into the Car Counting tool.
  2. Define Area of Interest: Specify the region in the video where you want to count cars.
  3. Configure Settings: Adjust parameters like detection sensitivity and counting rules.
  4. Run Analysis: Start the analysis process to detect and count vehicles.
  5. Review Results: View the counted data, visualized with overlays on the video.
  6. Export Data: Save the results in your preferred format for reporting or further processing.

Frequently Asked Questions

What video formats are supported by Car Counting?
Car Counting supports MP4, AVI, MOV, and MKV formats. For other formats, conversion may be required.

How accurate is Car Counting?
The accuracy of Car Counting exceeds 95% under ideal conditions, but may vary based on video quality, lighting, and object occlusions.

Can Car Counting work in low-light conditions?
Yes, Car Counting is optimized to perform well in low-light environments, though extreme darkness may reduce accuracy.

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