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Further refinements
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@ -25,18 +25,16 @@ class OvDetector(DetectionApi):
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self.ov_model = self.ov_core.read_model(detector_config.model.path)
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self.ov_model = self.ov_core.read_model(detector_config.model.path)
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self.ov_model_type = detector_config.model.model_type
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self.ov_model_type = detector_config.model.model_type
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#self.num_classes = 80 # TODO
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self.h = detector_config.model.height
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self.h = detector_config.model.height # 416
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self.w = detector_config.model.width
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self.w = detector_config.model.width # 416
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if(self.ov_model_type == ModelTypeEnum.yolox):
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self.set_strides_grids()
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self.interpreter = self.ov_core.compile_model(
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self.interpreter = self.ov_core.compile_model(
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model=self.ov_model, device_name=detector_config.device
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model=self.ov_model, device_name=detector_config.device
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)
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)
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logger.info(f"Model Input Shape: {self.interpreter.input(0).shape}")
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logger.info(f"Model Input Shape: {self.interpreter.input(0).shape}")
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self.output_indexes = 0
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self.output_indexes = 0
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while True:
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while True:
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try:
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try:
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tensor_shape = self.interpreter.output(self.output_indexes).shape
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tensor_shape = self.interpreter.output(self.output_indexes).shape
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@ -46,9 +44,11 @@ class OvDetector(DetectionApi):
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except:
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except:
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logger.info(f"Model has {self.output_indexes} Output Tensors")
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logger.info(f"Model has {self.output_indexes} Output Tensors")
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break
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break
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if(self.ov_model_type == ModelTypeEnum.yolox):
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if(self.ov_model_type == ModelTypeEnum.yolox):
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self.num_classes = tensor_shape[2]-5
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self.num_classes = tensor_shape[2]-5
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logger.info(f"YOLOX model has {self.num_classes} classes")
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logger.info(f"YOLOX model has {self.num_classes} classes")
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self.set_strides_grids()
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def set_strides_grids(self):
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def set_strides_grids(self):
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grids = []
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grids = []
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