![]() ![]() MaskHeight - The height of the mask to use. MaskWidth - The width of the mask to use. UseMask - Set to True or False to turn on and off □ □ The configuration settings are now located in the config.py file!ĬAPS_LOCK is the default for flipping the switch on the autoaim superpower! ⚙️ □ Check out the comments in the code for more insights. *Default settings are generally great for most scenarios. If you've followed these steps, you should be all set with TensorRT! ⚙️□ ⚙️ Configurable Settings TensorRT's power allows for larger models if desired! Note: You can pick a different YOLOv5 model size. yolov5s.pt -include engine -half -imgsz 320 320 -device 0 Patience is key it might look frozen, but it's just concentrating hard! Can take up to 20 mintues. Time to execute export.py with the following command. ![]() We recommend yolov5s.py or yolov5m.py HERE □. ![]() But if it doesn't work, then you will need to re-export it. C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v11.8\bin.C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v11.8\libnvvp.C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v11.8\lib.□ Just locate the correct file and replace the path with your new one. We're not looking for the 'lean' or 'dispatch' versions. □ If the following steps didn't work, don't stress out! □ The labeling of the files corresponds with the Python version you have installed on your machine. Pip install "C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v11.8\python\tensorrt-8.6.1-cp311-none-win_amd64.whl" If you do, good, then run the following command to install TensorRT in python. ![]() Once you have all the files copied over, you should have a folder at C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v11.8\python. zip TensorRT file and move all the folders/files to where the CUDA Toolkit is on your machine, usually at C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v11.8. zip CuDNN file and move all the folders/files to where the CUDA Toolkit is on your machine, usually at C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v11.8. Run the following pip install cupy-cuda11xĬlick to install CUDNN □. If you ever feel lost, you can always your questions in our Discord □. We forgot to mention adding environmental variable paths in the video. Watch the TensorRT section of the setup video □ before you begin.
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