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@ -212,7 +212,7 @@ You can get cfg-files by path: `darknet/cfg/`
* [YOLOv5](https://github.com/ultralytics/yolov5)
* **ONNX** on Jetson for YOLOv4: https://developer.nvidia.com/blog/announcing-onnx-runtime-for-jetson/
* **TensorRT** YOLOv4 on TensorRT+tkDNN: https://github.com/ceccocats/tkDNN
For YOLOv3 (-70% faster inference): [Yolo is natively supported in DeepStream 4.0](https://news.developer.nvidia.com/deepstream-sdk-4-now-available/) read [PDF](https://docs.nvidia.com/metropolis/deepstream/Custom_YOLO_Model_in_the_DeepStream_YOLO_App.pdf). [wang-xinyu/tensorrtx](https://github.com/wang-xinyu/tensorrtx) implemented yolov3-spp, yolov4, etc.
For YOLOv3 (-70% faster inference): [Yolo is natively supported in DeepStream 4.0](https://news.developer.nvidia.com/deepstream-sdk-4-now-available/) read [PDF](https://docs.nvidia.com/metropolis/deepstream/Custom_YOLO_Model_in_the_DeepStream_YOLO_App.pdf). [jkjung-avt/tensorrt_demos](https://github.com/jkjung-avt/tensorrt_demos) or [wang-xinyu/tensorrtx](https://github.com/wang-xinyu/tensorrtx) implemented yolov3-spp, yolov4, etc.
* **Deepstream 5.0 / TensorRT for YOLOv4** https://github.com/NVIDIA-AI-IOT/yolov4_deepstream or https://github.com/marcoslucianops/DeepStream-Yolo
* **Triton Inference Server / TensorRT** https://github.com/isarsoft/yolov4-triton-tensorrt
* **Xilinx Zynq Ultrascale+ Deep Learning Processor (DPU) ZCU102/ZCU104:** https://github.com/Xilinx/Vitis-In-Depth-Tutorial/tree/master/Machine_Learning/Design_Tutorials/07-yolov4-tutorial