_odConfig.CategoryFilePath = TestHelper.TFLitePath + "object_detector/od_label.txt";
_odConfig.MeanValue = 127.0;
_odConfig.StdValue = 127.0;
- _odConfig.ConfidenceThreshold = 0.6;
+ _odConfig.ConfidenceThreshold = 0.3;
_odConfig.Backend = InferenceBackendType.TFLite;
_odConfig.Device = InferenceTargetDevice.CPU;
_odConfig.DataType = InferenceDataType.Float32;
- _odConfig.TensorSize = new Size(224, 224);
+ _odConfig.TensorSize = new Size(300, 300);
_odConfig.TensorChannels = 3;
- _odConfig.InputNodeName = "input_2";
- _odConfig.OutputNodeName = new string[] { "dense_3/Softmax" };
+ _odConfig.InputNodeName = "normalized_input_image_tensor";
+ _odConfig.OutputNodeName = new string[]
+ {
+ "TFLite_Detection_PostProcess",
+ "TFLite_Detection_PostProcess:1",
+ "TFLite_Detection_PostProcess:2",
+ "TFLite_Detection_PostProcess:3"
+ };
+
_icConfig.WeightFilePath = TestHelper.TFLitePath + "image_classifier/ic_tflite_model.tflite";
_icConfig.CategoryFilePath = TestHelper.TFLitePath + "image_classifier/ic_label.txt";
_icConfig.MeanValue = 127.5;
_icConfig.StdValue = 127.5;
- _icConfig.ConfidenceThreshold = 0.3;
+ _icConfig.ConfidenceThreshold = 0.5;
_icConfig.Backend = InferenceBackendType.TFLite;
_icConfig.Device = InferenceTargetDevice.CPU;
_icConfig.DataType = InferenceDataType.Float32;
- _icConfig.TensorSize = new Size(300, 300);
+ _icConfig.TensorSize = new Size(224, 224);
_icConfig.TensorChannels = 3;
- _icConfig.InputNodeName = "normalized_input_image_tensor";
- _icConfig.OutputNodeName = new string[]
- {
- "TFLite_Detection_PostProcess",
- "TFLite_Detection_PostProcess:1",
- "TFLite_Detection_PostProcess:2",
- "TFLite_Detection_PostProcess:3"
- };
+ _icConfig.InputNodeName = "input_2";
+ _icConfig.OutputNodeName = new string[] { "dense_3/Softmax" };
}
}
}