My full tech stack is:

• GCP ML Vision.
• Exported Model to tflite format (from the same GCP console).
• XCode for iOS development
• iPhone 11 pro

I am trying to use a Custom Object detector using MLKit and one model trained in GCP AutoML Vision.
I created the model and exported as tflite file, but when trying to do objectDetector processImage:visionImage, I always get the error:
Error Domain=com.google.visionkit.pipeline.error Code=3 "Pipeline failed to fully start: CalculatorGraph::Run() failed in Run: Calculator::Open() for node "BoxClassifierCalculator" failed: #vk Unexpected number of dimensions for output index 0: got 3D, expected either 2D (BxN with B=1) or 4D (BxHxWxN with B=1, W=1, H=1)." UserInfo={com.google.visionkit.status=<MLKITvk_VNKStatusWrapper: 0x280841270>, NSLocalizedDescription=Pipeline failed to fully start: CalculatorGraph::Run() failed in Run: Calculator::Open() for node "BoxClassifierCalculator" failed: #vk Unexpected number of dimensions for output index 0: got 3D, expected either 2D (BxN with B=1) or 4D (BxHxWxN with B=1, W=1, H=1).}.
I have downloaded the mlkit examples from https://github.com/googlesamples/mlkitand there is something similar in the vision project, (to detect birds) when I try to replace my own tflite file, it breaks in the exact same way as in my own project.
I presume the tflite is created in a very different way as MLVision does.
Any insight? (Sorry if this is so obvious, but I'm pretty new to TensorFlow and MLVision) Thanks in advance

CodePudding user response：

The issue is exactly as what the error message says: got 3D, expected either 2D (BxN with B=1) or 4D (BxHxWxN with B=1, W=1, H=1). That means your model is not compatible with ML Kit, as its tensor has incorrect dimension. The model compatibility requirements are specified here.