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Track objects in video
Florence-2 for Videos

Florence-2 for Videos

Generate annotated video with object detection

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What is Florence-2 for Videos ?

Florence-2 for Videos is a cutting-edge AI tool designed to track objects within video content. It leverages advanced computer vision technology to analyze video frames and generate annotated outputs. The tool is particularly useful for applications requiring object detection and tracking across multiple frames, making it ideal for surveillance, analytics, and content creation.

Features

• Advanced Object Tracking: Accurately tracks objects across video frames.
• Customizable Annotations: Generates annotated videos with detailed object labels.
• High Accuracy Detection: Utilizes state-of-the-art models for precise object recognition.
• Export Capabilities: Allows users to export annotated videos in multiple formats.
• Integration Support: Works seamlessly with popular video analysis tools.
• Real-Time Processing: Enables fast and efficient video processing for quick results.

How to use Florence-2 for Videos ?

  1. Install the Tool: Download and install Florence-2 for Videos from its official source.
  2. Upload Your Video: Import the video file you want to analyze.
  3. Select Settings: Choose detection settings, such as object classes and annotation styles.
  4. Apply the Model: Run the video through the AI model to detect and track objects.
  5. Review Results: Check the generated annotated video for accuracy.
  6. Export Output: Save the final annotated video in your preferred format.

Frequently Asked Questions

What video formats are supported?
Florence-2 for Videos supports MP4, AVI, MOV, and MPEG formats.

How accurate is the object detection?
Accuracy depends on factors like video resolution, lighting conditions, and object occlusion. Florence-2 for Videos delivers high accuracy under optimal conditions.

Can it track objects in real-time?
While Florence-2 for Videos is optimized for speed, real-time tracking depends on your system's processing power and the complexity of the video.

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