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Object Detection is a computer vision technology that identifies and labels objects within images or video streams. It is powered by advanced algorithms, such as YOLO (You Only Look Once) models, to detect, classify, and locate objects in real time. This technology is widely used in applications like surveillance, autonomous vehicles, and medical imaging analysis.
• Real-Time Processing: Detects objects in live video or images with minimal latency.
• High Accuracy: Utilizes state-of-the-art models to ensure precise object identification.
• Multiple Object Detection: Capable of detecting and labeling multiple objects in a single frame.
• Customizable Models: Allows users to train models for specific object detection tasks.
• Cross-Platform Compatibility: Can be integrated into various applications and environments.
What models are used for Object Detection?
The application primarily uses YOLO (You Only Look Once) models, known for their speed and accuracy.
What input formats are supported?
The tool supports JPG, PNG, and video formats for detection tasks.
Can the model detect custom objects?
Yes, with additional training, the model can be fine-tuned to detect specific or custom objects.