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FilippoAleotti avatar FilippoAleotti commented on June 12, 2024

Hi,
Please, could you be more specific?

from mobilepydnet.

Suraj520 avatar Suraj520 commented on June 12, 2024

Hi @FilippoAleotti, Thanks for reverting back with a response

To be more precise:
I generated the frozen graph and .tflite from https://github.com/FilippoAleotti/mobilePydnet/tree/v2/single_inference and visualized it via Netron. The output was true div type: float32[1,384,640,1]

However, It is different from https://github.com/FilippoAleotti/mobilePydnet/blob/tflite/Android_tflite/app/src/main/assets/pydnet%2B%2B.tflite
which contains output at 3 scales as mentioned in Pydnet paper:

name: PSD/resize/ResizeBilinear : float32[1,448,640,1]
name: PSD/resize_1/ResizeBilinear : float32[1,448,640,1]
name: PSD/resize_2/ResizeBilinear : float32[1,448,640,1]

The difference in architectures from Master Branch to V2(Default) Branch, intrigued me to open the issue to request you for providing detailed documentation towards training the model as per the following reference
https://github.com/FilippoAleotti/mobilePydnet/tree/v2/single_inference

I felt like https://github.com/FilippoAleotti/mobilePydnet/tree/v2/single_inference 's README needs to be a bit more descriptive.
Kindly correct me, If I am missing something :)

from mobilepydnet.

FilippoAleotti avatar FilippoAleotti commented on June 12, 2024

This because I left in this frozen graph only the last prediction. If you need lower scale predictions, you can make you own frozen graph including also H/2 and H/4

from mobilepydnet.

Suraj520 avatar Suraj520 commented on June 12, 2024

Oh Okay, Thanks @FilippoAleotti !

from mobilepydnet.

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