BodyPix tflite model support

@Volcomix , your work is really impressive! Thank you so much for this work.

I saw this comment from @PINTO0309 in this issue https://github.com/Volcomix/virtual-background/issues/2#issuecomment-829730723

I don’t know if it will be useful for you, but I have converted and quantized it for various frameworks and committed it to my repository.

TFLite Float32/Float16/INT8, TFJS, TF-TRT, ONNX, CoreML, OpenVINO IR FP32/FP16, Myriad Inference Blob

https://github.com/PINTO0309/PINTO_model_zoo https://github.com/PINTO0309/PINTO_model_zoo/tree/main/109_Selfie_Segmentation

And I’m able to easily play with the different models. Thank you both for your hardwork.

I noticed @PINTO0309 also has bodypix tflite models here but they don’t seem to work with @Volcomix pipeline. Getting some logs I noticed the output image has the following:

console.log({
  inputHeight: this._tflite._getInputHeight(),
  inputWidth: this._tflite._getInputWidth(),
  inputChannelCount: this._tflite._getInputChannelCount(),
  outputHeight: this._tflite._getOutputHeight(),
  outputWidth: this._tflite._getOutputWidth(),
  outputChannelCount: this._tflite._getOutputChannelCount(),
});
// Outputs an image with 10x8 resolution, 17 channels

As you can see, the output seems wrong. Any advice on what to adjust? My intention is I want to run bodypix model in wasm hoping to gain more performance than the tfjs one. Is this something you can help with? Thank you in advance!