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add a benchmark script
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@ -102,5 +102,6 @@ RUN (apt-get autoremove -y; \
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WORKDIR /opt/frigate/
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ADD frigate frigate/
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COPY detect_objects.py .
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COPY benchmark.py .
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CMD ["python3", "-u", "detect_objects.py"]
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20
benchmark.py
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20
benchmark.py
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@ -0,0 +1,20 @@
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import statistics
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import numpy as np
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from edgetpu.detection.engine import DetectionEngine
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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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# Load the edgetpu engine and labels
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engine = DetectionEngine(PATH_TO_CKPT)
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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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detection_times = []
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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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print("Average inference time: " + str(statistics.mean(detection_times)))
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