This repository extends the YOLOv10 model with additional output layers: num_detections, detection_boxes, detection_scores, and detection_classes. It also includes optimizations for exporting models with dynamic size and dynamic batch size, ensuring that the ONNX models are optimized for TensorRT builds.
This repository provides a practical implementation of YOLOv10 within DeepStream, a powerful tool for video analytics. Users can seamlessly integrate the YOLOv10 model into their projects using DeepStream, leveraging its capabilities for efficient video processing and analysis.
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Repository 1: YOLOv10 with Enhanced Outputs and TensorRT Optimization
YOLOv10 Export ONNX
This repository extends the YOLOv10 model with additional output layers:
num_detections,detection_boxes,detection_scores, anddetection_classes. It also includes optimizations for exporting models with dynamic size and dynamic batch size, ensuring that the ONNX models are optimized for TensorRT builds.Repository 2: DeepStream Integration for YOLOv10
DeepStream YOLOv10
This repository provides a practical implementation of YOLOv10 within DeepStream, a powerful tool for video analytics. Users can seamlessly integrate the YOLOv10 model into their projects using DeepStream, leveraging its capabilities for efficient video processing and analysis.