1. OS Ubuntu 18.04

2. OS Architecture x86_64

3. Version of OpenVINO 2021.2.185 (the one from your dockerfile)

4. Version of TensorFlow e.g. v2.4.1 (the one from your dockerfile)

9. Download URL for .tflite : https://github.com/google/mediapipe/blob/master/mediapipe/modules/palm_detection/palm_detection.tflite

Hi Pinto ! First of all, I want to thank you for your last version of tflite2tensorflow. The dockerfile will surely make users life much easier !

I have installed and run the docker image of tflite2tensorflow to convert the Mediapipe palm detection model (see link above) into Openvino IR format. This model takes 128x128 images as input, whereas the previous model took 256x256 images.
When running the FP32 model on my cpu, I noticed that sometimes the palm bounding box seemed a bit off.
When comparing with the output from the original tflite model, we can see the bounding boxes are not the same:
Below is the output from the FP32 openvino model:

Below is the output from the tflite model:

Note that if I compare the outputs of the older 256x256 models, there are no differences between tflite and Openvino versions.

Do you have an idea of what could explain the different ouputs ?
Using Netron, I can see that the new tflite model now uses Prelu and ResizeBilinear that were not used in the older model. I don't see how Prelu could cause differences in the conversion process, but ResizeBilinear may be trickier (converted into Interpolate). Do you have any thoughts about that ?

Thanks for your help! I would like to use the new model, which is much faster than the previous version.

I can send you the code to reproduce the problem if you want.