class TestSpatialPrediction(unittest.TestCase):
def setUp(self):
rospy.loginfo("Initializing test for spatial predictions")
self.model = ImageLocationLearner()
self.model.load_models("/ros/catkin_ws/src/hrc_discrim_learning/model/spatial_regressors")
def test_prediction(self):
features = {
"location": [1, .2, .2],
"orientation": [0, 0, 0, 0],
"description" : "right"
}
obj_file = "/ros/catkin_ws/src/hrc_discrim_learning/train/objects.json"
with open(obj_file, 'r') as f:
obj_dict = json.load(f)
all_objs = [Object(x) for id, x in obj_dict.items()]
context = AdaptiveContext(all_objs)
for o in all_objs:
self.assertEqual(o.get_feature_class_value('description'),
self.model.predict(o, context))
def setUp(self):
print()
print("-----------Testing SGD selection--------------")
loc_model = ImageLocationLearner()
loc_model.load_models(
"/ros/catkin_ws/src/hrc_discrim_learning/model/spatial")
features_ordered = ['size_relative', 'color', 'material', 'location']
self.m = SGDPrimeSelector(features_ordered, loc_model, 0, 0)
def setUp(self):
print()
print("-----------Testing FullBrevity selection--------------")
loc_model = ImageLocationLearner()
loc_model.load_models(
"/ros/catkin_ws/src/hrc_discrim_learning/model/spatial")
rank = ['color', 'material', 'size_relative', 'location']
self.m = FullBrevSelector(rank, loc_model, 0, 0)
def setUp(self):
rospy.loginfo("Initializing test for spatial predictions")
self.model = ImageLocationLearner()
self.model.load_models("/ros/catkin_ws/src/hrc_discrim_learning/model/spatial_regressors")
# from hrc_discrim_learning.feature_learning import IncrementalLearner
from hrc_discrim_learning.sgd_learner import SGDPrimeSelector
from hrc_discrim_learning.spatial_learning import ImageLocationLearner
# if __name__ == "__main__":
# spatial_model_dest = rospy.get_param("hrc_discrim_learning/spatial_model")
# loc_model = ImageLocationLearner()
# loc_model.load_models(spatial_model_dest)
#
# feat_learner = IncrementalLearner(loc_model)
#
# all_learners = [feat_learner]
#
# t = TrainHarness('train_feature', '/train_input_provider', all_learners, 'feature')
# t.run_training()
if __name__ == "__main__":
spatial_model_dest = rospy.get_param("hrc_discrim_learning/spatial_model")
loc_model = ImageLocationLearner()
loc_model.load_models(spatial_model_dest)
rank = ['size_relative', 'color', 'material', 'location']
feat_learner = SGDPrimeSelector(rank, loc_model, 0, 0)
all_learners = [feat_learner]
t = TrainHarness('train_feature', '/train_input_provider', all_learners,
'feature')
t.run_training()
#!/usr/bin/env python
from hrc_discrim_learning.spatial_learning import ImageLocationLearner, ObjectLocationLearner
from hrc_discrim_learning.trainer_common import TrainHarness
import rospy
if __name__ == '__main__':
l1 = ImageLocationLearner()
# l2 = ObjectLocationLearner()
all_learners = [l1]
t = TrainHarness('train_spatial', '/train_input_provider', all_learners,
'spatial')
t.run_training()