I used the Tensorflow2 API to fine-tune an object detection model (ssd_mobilenet_v2_fpnlite_640x640) and make it recognize a custom object.
The model works perfectly on my PC, I have the trained model in saved format, and I was wondering how to export it to the Jetson NANO.
I tried using the tf2onnx repository, but when I try to convert my model I’m getting the error:
ValueError: StridedSlice: attribute new_axis_mask not supported
so, I’m assuming there are some parts in the model not supported in onnx. Just out of curiosity, I also tried converting to onnx the original, pre-trained model (as downloaded form the TF model zoo, without me fine-tuning it) but it also returned some similar errors.
So, I was planning on copying my saved model to the Jetson NANO and following this guide to optimize it with TensorRT, but before proceeding I wanted to ask:
once (if) I successfully optimize the model with TensorRT, how can I run it on the Jetson NANO? Do I need the TensorFlow object detection API to run on the device for it? Or can I somehow run it with detectnet?
if I need the object detection API, is there a RELIABLE guide on how to install it on the NANO? I followed a bunch of guides, but can’t seem to make it work. After compiling the protopuf files, I’m running the command:
python -m pip install --use-feature=2020-resolver .
but the installation goes on forever, pip is going backwards through a bunch of versions of scipy without being able to solve the dependency.
- are there any alternatives that I’m missing?