Hi @Manuel_Salas ,
Thank you for your response!
I went through the user manual, and it was really helpful. I was able to deploy the pre-trained MobileNet V1 model on the IMX95 using the NPU.
Here’s a summary of my results:
root@imx95-iwg61m:~/varshil/IMX95_Model_Deployment# python3 label_image.py \
-m mobilenet_v1_1.0_224_quant.tflite \
-l labels.txt \
-i test.jpg \
-e /usr/lib/libneutron_delegate.so
Loading external delegate from /usr/lib/libneutron_delegate.so with args: {}
INFO: NeutronDelegate delegate: 29 nodes delegated out of 31 nodes with 1 partitions.
INFO: Created TensorFlow Lite XNNPACK delegate for CPU.
1.000000: fox squirrel
0.000000: toilet tissue
0.000000: starfish
0.000000: zebra
0.000000: sorrel
time: 5.978ms
However, I’m currently stuck while trying to deploy my custom CNN model for Emotion Detection. I trained it on my local server and converted it to TFLite format, but I’m encountering some issues during deployment.
My main question is: What layers are necessary for my model to be compatible with the Neutron Delegate? The user manual mentions supported operators for the Ethos-U Delegate but not for the Neutron Delegate.
I would greatly appreciate your guidance on how to move past this blocker.
Thank you!
Best regards,
Varshil