Page Comparison

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1. Add some NN modules and Samples.

   1. Yolov8 Pose for human posture detection.

   2. Yolov8 OBB (oriented bounding box)， can detect the peripheral direction of objects.

   3. Yolov8 Segmentation. The detected targets can be identified using masks.

   4. Yolov8 Classification. Each target in the detected image can be classified based on confidence level.

   5. Pedestrian Tracking. Pedestrians can be tracked and assigned a fixed ID for each tracked pedestrian.

   6. Vehicle attributes. Can identify trucks, cars, buses, and their respective colors.

   7. License plate recognition. It can detect license plates and recognize their contents.

   8. Yolov10 Detection. Models for Object Detection.

   9. RTMDet. Real-time Models for Object Detection.

2. Parallel operations in multi-model applications can maximize the utilization of NPU and CPU, ultimately maximizing the processing frame rate of the application.

3. Implement official and customized partitions.

4. Arrangement of some folder structs such as tool and algo and so on.

5. The parameters of nnf_sample are designed in the standard Linux option (-, --) way.

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