# yolov3-tiny-onnx-TensorRT

**Repository Path**: zhiyuanzhao/yolov3-tiny-onnx-TensorRT

## Basic Information

- **Project Name**: yolov3-tiny-onnx-TensorRT
- **Description**: No description available
- **Primary Language**: Python
- **License**: Not specified
- **Default Branch**: master
- **Homepage**: None
- **GVP Project**: No

## Statistics

- **Stars**: 0
- **Forks**: 0
- **Created**: 2021-04-22
- **Last Updated**: 2021-04-22

## Categories & Tags

**Categories**: Uncategorized

**Tags**: None

## README

# 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.