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			20 lines
		
	
	
		
			671 B
		
	
	
	
		
			Python
		
	
	
	
	
	
			
		
		
	
	
			20 lines
		
	
	
		
			671 B
		
	
	
	
		
			Python
		
	
	
	
	
	
| import statistics
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| import numpy as np
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| from edgetpu.detection.engine import DetectionEngine
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| 
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| # Path to frozen detection graph. This is the actual model that is used for the object detection.
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| PATH_TO_CKPT = '/frozen_inference_graph.pb'
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| 
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| # Load the edgetpu engine and labels
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| engine = DetectionEngine(PATH_TO_CKPT)
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| 
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| frame = np.zeros((300,300,3), np.uint8)
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| flattened_frame = np.expand_dims(frame, axis=0).flatten()
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| 
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| detection_times = []
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| 
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| for x in range(0, 1000):
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|     objects = engine.DetectWithInputTensor(flattened_frame, threshold=0.1, top_k=3)
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|     detection_times.append(engine.get_inference_time())
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| 
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| print("Average inference time: " + str(statistics.mean(detection_times))) | 
