将yolov-mitty模型转换为trt模型_convert your yolov3-tiny model to trt

# yolov3-tiny2onnx2trt Convert your yolov3-tiny model to trt model # device: nvidia jetson tx2 # jetpack version:jetpack4.2: ubuntu18.04 tensorrt5.0.6.3 cuda10.0 cudnn7.3.1 # others: python=2.7 numpy=1.16.1 onnx=1.4.1 (important) pycuda=2019.1.1 Pillow=6.1.0 wget=3.2 # custom settings data_processing.py: line14: LABEL_FILE_PATH = '/home/nvidia/yolov3-tiny2onnx2trt/coco_labels.txt' line19: CATEGORY_NUM = 80 yolov3_to_onnx.py: line778: img_size = 416 line784: cfg_file_path = '/home/nvidia/yolov3-tiny2onnx2trt/yolov3-tiny.cfg' line811: weights_file_path = '/home/nvidia/yolov3-tiny2onnx2trt/yolov3-tiny.weights' line826: output_file_path = 'yolov3-tiny.onnx' onnx_to_tensorrt.py: line39: input_size = 416 line40: batch_size = 1 line42~line46: onnx_file_path = 'yolov3-tiny.onnx' engine_file_path = 'yolov3-tiny.trt' input_file_list = '/home/nvidia/yolov3-tiny2onnx2trt/imagelist.txt' IMAGE_PATH = '/home/nvidia/yolov3-tiny2onnx2trt/images/' save_path = '/home/nvidia/yolov3-tiny2onnx2trt/' # notes (very important!): 0.The onnx version must be 1.4.1. If it is not, please run the commands: pip uninstall onnx pip install onnx==1.4.1 1.The cfg-file's last line must be a blank line. You should press Enter to add a blank line if there is no blank line at the end of the file. # steps: 0.Put your .weights file in the folder |-yolov3-tiny2onnx2trt |-yolov3-tiny.weights 1.Change your settings as "#custom settings" 2.Run commands: cd yolov3-tiny2onnx2trt python yolov3_to_onnx.py you will get a yolov3-tiny.onnx file 3.Run commands: python onnx_to_tensorrt.py: you will get a yolov3-tiny.trt file and some inferenced images.