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# Contributors:
# Barbaros Cetiner
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# Last updated:
# 11-06-2024

"""
Example demonstrating use of street-level image detectors.

 Purpose: Testing 1) get_class method of Importer
                  2) set_directory and print_info methods of ImageSet objects
                  3) predict methods of NFloorDetector, ChimneyDetector, and
                     GarageDetector
"""

from brails.types.image_set import ImageSet
from brails import Importer

importer = Importer()
street_images = ImageSet()
street_images.set_directory("./images/street", True)

street_images.print_info()

# Test importer and one of the aerial imagery classifiers, RoofShapeClassifier:
print('Number of floors predictions using a detector model trained on a custom'
      ' dataset:')
my_class = importer.get_class('NFloorDetector')
my_classifier = my_class()
predictions = my_classifier.predict(street_images)
print(predictions)

print('Chimney detection using a detector model trained on a custom'
      ' dataset:')
my_class = importer.get_class('ChimneyDetector')
my_classifier = my_class()
predictions = my_classifier.predict(street_images)
print(predictions)

print('Garage detection using a detector model trained on a custom'
      ' dataset:')
my_class = importer.get_class('GarageDetector')
my_classifier = my_class()
predictions = my_classifier.predict(street_images)
print(predictions)
