My model doesn't work
From Emgu CV: OpenCV in .NET (C#, VB, C++ and more)
Why my model doesn't work
Try our demo project first
First, please try our demo project. Run it on your workstation or mobile device. In most of the case, our demo project should work as expected. If not, please send us the following information such that we can take a look:
- What is the full package name. e.g. libemgutflite-android-126.96.36.1998-cr or Emgu TF Lite v2.1 from Unity asset store.
- Platform information. e.g. Windows, Mac, Android or iOS.
- What is the CPU architecture. e.g. x86, x64, ARM or ARM64.
- For mobile device, let us know if it is a simulator or device.
- OS version. For Android, let us know the API level (e.g. Android 9) where the demo project is run.
Your demo works, I replaced with my model and it fails
- Not all model are created the same. TF / TF Lite model that use different training method are not drop and replaced. Even models that use the same training script can have different type of input tensor and output tensor. e.g. quantized model has different input tensor type than the none-quantized model, even the training code is the same.
- You need to make sure the TF / TF Lite model is working as expected. The best way to check is to load the model in python and test it against data, and make sure it produce the correct output. Or you can test it against Android device if you are using Android Studio.
- A few things to check:
- Input tensor dimension, input tensor data type
- Output tensor dimension. Output tensor data type. Output tensor data structure.
I checked all the parameters but the model doesn't work
- If you checked all the parameters but the model doesn't work. We can help. Usually it is due to mismatched input /output tensor parameters. It is a laborious process for us. Quite often requires 2 working day of our professional service time to port your model to Emgu TF / Emgu TF Lite. This is not a bug in Emgu TF / Emgu TF Lite (even thought in rare occasion it could be, and we will be happy to fix the bugs without any additional fees). If this is not due to bugs in the Emgu TF / Emgu TF Lite library, we will need to charge our hourly consultation fee times the hours we estimated to complete the task. There will be no fee if we failed to migrate your model to Emgu TF / Emgu TF Lite.
- We will require the following data from you:
- The TF / TF Lite model files.
- The test image / test data.
- The python code to load the TF / TF Lite model and apply it to the given data.
- The expected output for running the python code.
- We will draft a contract defining the deliverable, the time required to finish the task and the cost. The contracted needs to be signed.
- We will complete the task and deliver the code.