tensorrt_yolo#

Purpose#

This package detects 2D bounding boxes for target objects e.g., cars, trucks, bicycles, and pedestrians on a image based on YOLO(You only look once) model.

Inner-workings / Algorithms#

Cite#

yolov3

Redmon, J., & Farhadi, A. (2018). Yolov3: An incremental improvement. arXiv preprint arXiv:1804.02767.

yolov4

Bochkovskiy, A., Wang, C. Y., & Liao, H. Y. M. (2020). Yolov4: Optimal speed and accuracy of object detection. arXiv preprint arXiv:2004.10934.

yolov5

Jocher, G., et al. (2021). ultralytics/yolov5: v6.0 - YOLOv5n 'Nano' models, Roboflow integration, TensorFlow export, OpenCV DNN support (v6.0). Zenodo. https://doi.org/10.5281/zenodo.5563715

Inputs / Outputs#

Input#

Name	Type	Description
`in/image`	`sensor_msgs/Image`	The input image

Output#

Name	Type	Description
`out/objects`	`tier4_perception_msgs/DetectedObjectsWithFeature`	The detected objects with 2D bounding boxes
`out/image`	`sensor_msgs/Image`	The image with 2D bounding boxes for visualization

Parameters#

Core Parameters#

Name	Type	Default Value	Description
`anchors`	double array	[10.0, 13.0, 16.0, 30.0, 33.0, 23.0, 30.0, 61.0, 62.0, 45.0, 59.0, 119.0, 116.0, 90.0, 156.0, 198.0, 373.0, 326.0]	The anchors to create bounding box candidates
`scale_x_y`	double array	[1.0, 1.0, 1.0]	The scale parameter to eliminate grid sensitivity
`score_thresh`	double	0.1	If the objectness score is less than this value, the object is ignored in yolo layer.
`iou_thresh`	double	0.45	The iou threshold for NMS method
`detections_per_im`	int	100	The maximum detection number for one frame
`use_darknet_layer`	bool	true	The flag to use yolo layer in darknet
`ignore_thresh`	double	0.5	If the output score is less than this value, ths object is ignored.

Node Parameters#

Name	Type	Default Value	Description
`onnx_file`	string	""	The onnx file name for yolo model
`engine_file`	string	""	The tensorrt engine file name for yolo model
`label_file`	string	""	The label file with label names for detected objects written on it
`calib_image_directory`	string	""	The directory name including calibration images for int8 inference
`calib_cache_file`	string	""	The calibration cache file for int8 inference
`mode`	string	"FP32"	The inference mode: "FP32", "FP16", "INT8"