Here. 😃
https://github.com/NobuoTsukamoto/tflite-cv-example/tree/master/deeplab_edgetpu2#coral-dev-board-edgetpu-autosegedgetpu-xs-with-fusing-argmax

Hi,
amazing repo, I got my hands on an Edge TPU but I am struggling in finding an actually useful way to use it.
I am interested in doing only instance segmentation (so no classification whatsoever), and I was wondering if in your semantic segmentation approach based on DeepLabV3 you are limited to the same 20 classes listed here.

Thanks

Hi,
What frame rates are you experiencing with deeplabV3 using a webcam on a coral edge tpu?

Hello

First of all, great repo! I particularly want to thank you for your help in creating export_tfv2_lite_models.ipynb, I was able to convert my custom model with SSD MobileNet V2 FPNLite 640x640 to edge_tpu.tflite smoothly!

However, I am having difficulty understanding your repo to "run the model on a raspberry pi with coral"..

I have followed your guide from https://github.com/NobuoTsukamoto/edge_tpu/tree/master/detection/cpp

But I think I am running C++ instead of object_detection_capture_picamera.py?

I was wondering if you can provide me a guide on what I need to do in order to run your object_detection_capture_picamera.py script on my Raspberry Pi 4 2GB with Coral.

I have tried installing some of the dependencies myself but I still have no luck in running the script to see my model live on my Pi. I have cloned your entire repo but I don't think it is needed for what I want, maybe I am wrong?

Any help at all you can that you can share in order to run the correct repo/script on my Pi will be very appreciated.

Thank you again for your work!