Missing input quantization about tflitedetection

[CIPop]

I take this back: doing above will result in really bad detection.
(As reference, I was trying to port this model to WAMR, which internally does the quantization whenever this information is available: https://github.com/bytecodealliance/wasm-micro-runtime/blob/main/core/iwasm/libraries/wasi-nn/src/wasi_nn_tensorflowlite.cpp#L313)

[CIPop]

Re-opening based on the discussion/explanation from WAMR.

The pre-processing should be:

1. Obtain input - coincidentally, uint8_t `300x300x3, values [0..255]
2. Transform input to float 300x300x3, values [-1..1]
3. Based on the model input type (uint8_t), apply quantization parameters. This transforms the input back to uint8_t 300x300x3, values [0..255].

The important part is that, while the tensors in steps 1 and 3 have the same shape and type, the values are clearly different.