Datasets description¶

data1.csv: A set of hand-drawn int 2D-points for 2 objects (“o1”, “o2”) with fixed width and length (i.e. bounding boxes are provided). Tried to cover all possible cardir and RCC states.
data2.csv: A set of 10K random integer 2D-points (random.randint(0, 50)) for 3 objects (“o1”, “o2”, “o3”) and random float width and length (random.randint(3, 6)) (i.e. bounding boxes are provided).
data3.csv: A set of 10K random integer 2D-points (random.randint(0, 50)) for 3 objects (“o1”, “o2”, “o3”), but no width and length are given (i.e. no bounding boxes are provided).
data4.csv: A set of 10K random float 2D-points (random.uniform(0, 50)) for 3 objects (“o1”, “o2”, “o3”) and random float width and length (random.randint(3, 6)) (i.e. bounding boxes are provided).
data2_first100.csv: First 100 instances of data2.
data3_first100.csv: First 100 instances of data3.
data4_first100.csv: First 100 instances of data4.

Running the tests¶

rosrun qsr_lib unittests_generate_ground_truth.py -i <world name> -o <output filename> <qsr>

E.g.

rosrun qsr_lib unittests_generate_ground_truth.py -i data1 -o qsr_lib/tests/data/data1_rcc4_defaults.txt rcc4

-i options: data1 | data2 | data3 | data4

Defaults. E.g.

rosrun qsr_lib unittests_generate_ground_truth.py -i data1 -o qsr_lib/tests/data/data1_rcc4_defaults.txt rcc4