def run_test(id_test, test, id_estimator, estimator):
global W, H
logger.info(' id_test: %s' % id_test)
logger.info('id_estimator: %s' % id_estimator)
from led_detection.unit_tests import LEDDetectionUnitTest
assert isinstance(test, LEDDetectionUnitTest)
query = test.get_query()
print( query['images']['rgb'][0].shape)
H, W, _ = query['images']['rgb'][0].shape
print('shape is %s, %s'%(W, H))
result = estimator.detect_led(**query)
# We are testing whether the expected detections are a subset of
# the returned ones, we will accept duplicate detections of the
# same LED
match_count = [0]*len(test.expected)
for r in result.detections:
m = find_match(r, test.expected)
if(m != -1):
match_count[m]+=1
missedLEDs = [test.expected[i] for i in range(0, len(match_count)) if match_count[i]==0]
if(missedLEDs):
logger.error('missed LED detections (%s): \n %s' % (len(missedLEDs),missedLEDs))
return not 0 in match_count
if __name__ == '__main__':
wrap_main(main)
filename = os.path.join(root, dirname, filename)
alltests = load_tests(filename)
estimators = {'dummy': DummyLEDDetector()}
which_tests = expand_string(which_tests0, list(alltests))
which_estimators = expand_string(which_estimators0, list(estimators))
logger.info(' tests: %r |-> %s' % (which_tests0, which_tests))
logger.info('estimators: %r |-> %s' % (which_estimators0, which_estimators))
# which tests to execute
for id_test in which_tests:
for id_estimator in which_estimators:
test_results = run_test(id_test, alltests[id_test],
id_estimator, estimators[id_estimator])
def run_test(id_test, test, id_estimator, estimator):
logger.info(' id_test: %s' % id_test)
logger.info('id_estimator: %s' % id_estimator)
from led_detection.unit_tests import LEDDetectionUnitTest
assert isinstance(test, LEDDetectionUnitTest)
query = test.get_query()
result = estimator.detect_led(**query)
raise NotImplementedError('To finish: Compare result to expected result.')
if __name__ == '__main__':
wrap_main(main)