Cross platform CLI to run a pre-trained model exported from CustomVision.ai in the Tensorflow format for image classification using the TensorFlowSharp library.

To learn more about Microsoft Cognitive Custom Vision Service, please see here: https://azure.microsoft.com/en-gb/services/cognitive-services/custom-vision-service/

Depending on the CustomVision.ai model's Domain, you'll need to set the appropriate values within the code:

These are set in BGR eg:

// General (Compact) 
// Landmark (Compact)
var bgrValues = new TFTensor(new float[] { 104.0f, 117.0f, 123.0f });

// Retail (Compact)
var bgrValues = new TFTensor(0f);

• Open the solution
• Restore Nuget Packages
• Run & enjoy

In case you see the following error:

Unhandled Exception: System.DllNotFoundException: Unable to load DLL 'libtensorflow': The specified module could not be found.

Copy the libtensorflow.dll file from the relevant %userprofile%.nuget\packages\tensorflowsharp runtimes folder of your OS into the same folder as the compiled executable.

The sample TensorFlow model (exported from CustomVision.ai) is for mushroom classification

CustomVision-TensorFlow.exe -m Assets\model.pb -l Assets\labels.txt -t Assets\test.jpg

Running the above from the command line will display the following:

I tensorflow/core/platform/cpu_feature_guard.cc:137] Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX AVX2
C:\Github\CustomVision-TensorFlow-CSharp\Assets\test.jpg = Agaricus bisporus (92.7477061748505%)
Total time: 00:00:00.4987094

• Link to Custom Vision Service Documentation
• Link to Custom Vision with Android
• Link to TensorFlow documentation
• Link to TensorFlowSharp
• Link to TensorFlow example code using Python
• Link to TensorFlow example code using C++
• Link to TensorFlow example code using Java