Le1kk / yolov3-tiny-onnx-TensorRT

convert your yolov3-tiny model to trt model

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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.

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convert your yolov3-tiny model to trt model


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