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Yolov5g is an object detection model designed to find and label objects in images efficiently. It is a variant of the YOLOv5 family, optimized for performance and accuracy in real-world applications. Yolov5g is widely used for tasks like surveillance, autonomous systems, and image analysis due to its speed and reliability.
• Real-time detection: Process images in milliseconds for quick object identification.
• Multiple object detection: Detect and label multiple objects in a single image.
• High accuracy and speed balance: Optimized for both accuracy and performance, making it suitable for resource-constrained environments.
• Customizable: Choose from different model sizes (small, medium, or larger) based on your specific needs.
• Versatile input support: Works with images and video streams.
• Flowchart-friendly: Easy integration into workflows for automated image processing.
• Cross-platform compatibility: Runs seamlessly on Windows, macOS, and Linux systems.
pip install -r requirements.txt.python detect.py --source [image/path] for images or python detect.py --source [video/path] for video streams.python train.py.What is the difference between Yolov5g and Yolov5?
Yolov5g is an optimized version of Yolov5, offering improved performance and better balance between accuracy and speed.
How do I install Yolov5g?
Clone the repository and install the dependencies using the provided requirements.txt file. Ensure you have Python and PyTorch installed.
Can I use Yolov5g for real-time video analysis?
Yes, Yolov5g supports real-time video analysis. Use the --source parameter with a video file or camera input for live detection.