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- #!/usr/bin/env python3
-
- import cv2
- import sys
- import rospy
- import object_detector_python3 as od
- import detection_node_python3 as dn
- import deep_learning_model_options as do
-
- if __name__ == '__main__':
- print('cv2.__version__ =', cv2.__version__)
- print('Python version (must be > 3.0):', sys.version)
- assert(int(sys.version[0]) >= 3)
-
-
- models_directory = do.get_directory()
- print('Using the following directory for deep learning models:', models_directory)
- use_neural_compute_stick = do.use_neural_compute_stick()
- if use_neural_compute_stick:
- print('Attempt to use an Intel Neural Compute Stick 2.')
- else:
- print('Not attempting to use an Intel Neural Compute Stick 2.')
-
- use_tiny = True
- if use_tiny:
- confidence_threshold = 0.0
- else:
- confidence_threshold = 0.5
-
- detector = od.ObjectDetector(models_directory,
- use_tiny_yolo3=use_tiny,
- confidence_threshold=confidence_threshold,
- use_neural_compute_stick=use_neural_compute_stick)
- default_marker_name = 'object'
- node_name = 'DetectObjectsNode'
- topic_base_name = 'objects'
- fit_plane = False
- node = dn.DetectionNode(detector, default_marker_name, node_name, topic_base_name, fit_plane)
- node.main()
- try:
- rospy.spin()
- except KeyboardInterrupt:
- print('interrupt received, so shutting down')
-
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