Let the machines learn where obstacles are in your depth images.
Must have the pandas and numpy packages installed.
python algorithms.py arff_output_file.arff dataset_folder_with_csv_and_rgb_files
Example
python algorithms.py arff_output_file.arff datasets/train/
from algorithms import all_file_features_to_arff
file_list = ['file1.csv', 'file2.csv', 'file3.csv']
all_file_features_to_arff('arff_file_output.arff', file_list)
import pandas as pd
from algorithms import *
df = pd.read_csv('./tests/data/depth7.csv', header=None)
print 'Average Depth: ' + str(average_depth(df))
print 'Median Depth: ' + str(median_depth(df))
print 'Minimum Depth: ' + str(minimum_depth(df))
print 'Standard Deviation: ' + str(standard_deviation(df))
print 'closer than 5 meters: ' + str(points_closer_than_5(df))