mirror of
https://github.com/blakeblackshear/frigate.git
synced 2024-12-23 19:11:14 +01:00
47 lines
1.5 KiB
Python
47 lines
1.5 KiB
Python
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import logging
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import numpy as np
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from frigate.detectors.detection_api import DetectionApi
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import tflite_runtime.interpreter as tflite
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logger = logging.getLogger(__name__)
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class CpuTfl(DetectionApi):
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def __init__(self, det_device=None, model_config=None, num_threads=3):
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self.interpreter = tflite.Interpreter(
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model_path=model_config.path or "/cpu_model.tflite", num_threads=num_threads
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)
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self.interpreter.allocate_tensors()
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self.tensor_input_details = self.interpreter.get_input_details()
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self.tensor_output_details = self.interpreter.get_output_details()
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def detect_raw(self, tensor_input):
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self.interpreter.set_tensor(self.tensor_input_details[0]["index"], tensor_input)
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self.interpreter.invoke()
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boxes = self.interpreter.tensor(self.tensor_output_details[0]["index"])()[0]
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class_ids = self.interpreter.tensor(self.tensor_output_details[1]["index"])()[0]
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scores = self.interpreter.tensor(self.tensor_output_details[2]["index"])()[0]
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count = int(
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self.interpreter.tensor(self.tensor_output_details[3]["index"])()[0]
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)
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detections = np.zeros((20, 6), np.float32)
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for i in range(count):
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if scores[i] < 0.4 or i == 20:
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break
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detections[i] = [
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class_ids[i],
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float(scores[i]),
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boxes[i][0],
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boxes[i][1],
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boxes[i][2],
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boxes[i][3],
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]
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return detections
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