Skip to content

Latest commit

 

History

History
47 lines (25 loc) · 1.32 KB

README.md

File metadata and controls

47 lines (25 loc) · 1.32 KB

Human-Pattern-Recognition

Real time recongition of humans through laser scans

#a)Convert R.O.S. bagfiles to suitable .mat files using 'bag2mat.py':

Enter desired destination with file ending in .mat

Command line use:

$rosrun <package_name> bag2mat.py <bag_file_path> <.mat_file_path> <laser_scan_rostopic> <scan_duration>

#b)Annotate with annotate.py (offline_train is no longer used):

Either provide command line arguments with the same order as below, or run the script without arguments and provide them when prompted

*Enter timewindow (int)

*Enter frames to set wall (int)

*Enter filename (string, no quotes)

trained data will be saved as : <input>.<trainingdata>

Command line use:

$python annotate.py <time_window> <wall_set_frames> <mat_file_to_use>

#c)create classifier with merge_train.py:

merge_train will create a classifier in the specified folder

$python merge_train <folder of annotated .mat files>

#d)Test on live data with hpr.py:

Publish laser scans on topic /scan, enable intensities, set min_angle, max_angle to -45,45 degrees
respectively (to be changed).

Command line use : $rosrun <package_name> hpr.py <.p file with annotated data for validation>

RECOMMENDATION:

Use same timewindow, and wall set time for each training set, and use the same values when
evaluating