How to run faster_rcnn_inception_v2 trained object detection tensorflow model on Jetson tx2?

Virat_Baahubali · October 25, 2020, 4:30pm

I have already configured Jetson Tx2 with tf_trtt_models and tensorflow successfully. I am able to import both tensorflow and tf_trt_models in python3 module on Jetson Tx2. I have faster_rcnn_inception_v2 trained object detection tensorflow model now I have couple of questions

tf_trtt_models repository converts models whose config files resembles to ssd_mobilenet_v1_coco and ssd_inception_v2_coco model’s config files. So is there any other way to convert faster_rcnn_inception_v2 model into tr_tf_model? or am I missing something?
what steps I need to follow in order to convert it into tf_trt_model? Can anyone please guide me through as it would really help me learn new concepts.

Please feel to reach out should you require more details thanks

Virat_Baahubali · October 25, 2020, 9:46pm

Running https://github.com/NVIDIA-AI-IOT/tf_trt_models/blob/master/examples/detection/detection.ipynb with faster_rcnn_inception_v2 it gives me following error

InvalidArgumentError: node BatchMultiClassNonMaxSuppression/map/while/MultiClassNonMaxSuppression/Slice (defined at /usr/local/lib/python3.6/dist-packages/tensorflow_core/python/framework/ops.py:1748) has inputs from different frames. The input node BatchMultiClassNonMaxSuppression/map/while/Reshape_1 (defined at /usr/local/lib/python3.6/dist-packages/tensorflow_core/python/framework/ops.py:1748) is in frame 'BatchMultiClassNonMaxSuppression/map/while/while_context'. The input node BatchMultiClassNonMaxSuppression/map/while/MultiClassNonMaxSuppression/Slice/begin (defined at /usr/local/lib/python3.6/dist-packages/tensorflow_core/python/framework/ops.py:1748) is in frame ''.

AastaLLL · October 26, 2020, 3:48am

Hi,

The error seems to be a TensorFlow issue:

May I know which TensorFlow version do you use?
Would you mind to try the conversion on the latest package we shared this month?

tensorflow-1.15.4+nv20.10-cp36-cp36m-linux_aarch64

Thanks.

Virat_Baahubali · October 26, 2020, 9:28am

Hi,

I am having jetpack 4.2 L4T 32.1.0 with tensorrt 5.0.6.3 and below is the tensorflow version installed
$ sudo pip3 install --extra-index-url https://developer.download.nvidia.com/compute/redist/jp/v42 tensorflow-gpu==1.13.1+nv19.3

AastaLLL · October 27, 2020, 3:16am

Hi,

Do you have any dependence on JetPack4.2?
If not, it’s recommended to upgrade your device to the latest first.

Thanks.

Virat_Baahubali · October 27, 2020, 3:34am

Hi,

Can you please explain what does dependence on jetpack 4.2 means? Thank you

AastaLLL · October 28, 2020, 3:58am

Hi,

If you don’t need to use JetPack4.2, it’s recommended to reflash your device with JetPack4.4.x first.

Thanks.

Virat_Baahubali · November 3, 2020, 3:42am

Hi,

Installed latest jetpack version and tensorflow 1.15.4 container 20.10 successfully on jetson TX2. I am still getting InvalidArgumentError: node BatchMultiClassNonMaxSuppression/map/while/MultiClassNonMaxSuppression/Slice (defined at /usr/local/lib/python3.6/dist-packages/tensorflow_core/python/framework/ops.py:1748) has inputs from different frames. The input node BatchMultiClassNonMaxSuppression/map/while/Reshape_1 (defined at /usr/local/lib/python3.6/dist-packages/tensorflow_core/python/framework/ops.py:1748) is in frame 'BatchMultiClassNonMaxSuppression/map/while/while_context'. The input node BatchMultiClassNonMaxSuppression/map/while/MultiClassNonMaxSuppression/Slice/begin (defined at /usr/local/lib/python3.6/dist-packages/tensorflow_core/python/framework/ops.py:1748) is in frame ''.
when I run faster_rcnn_inception_v2_coco in https://github.com/NVIDIA-AI-IOT/tf_trt_models/blob/master/examples/detection/detection.ipynb

Can anyone guide me through this it would really help continue my learning? This how I have reached this much far. is it even possible to convert faster_rcnn_inception_v2_coco model in tf_trt model
Thanks

AastaLLL · November 17, 2020, 8:02am

Hi,

Since the GitHub doesn’t be updated for a while, it is quite possible that it doesn’t support the newer operations.
May I know your target first? Do you want to enable the model with TF-TRT or standalone TenosrRT?

It’s more recommended to use standalone TensorRT due to performance.
And you can find an example for Faster-RCNN here:

Thanks.

Virat_Baahubali · November 17, 2020, 2:51pm

Hi,

I am trying to deploy my custom object detection faster_rcnn model trained with tensorflow on jetson tx2 platform. Since faster_rcnn model is not supported by tf-trt model but as you mentioned it has the workaround of using a convert-to-uff utility with trained custom object detection faster_rcnn model on tensorflow. I believe I should give it a try for this approach.

Can you please explain how tf-trt differs from convert-to-uff?
In order to use trained custom object detection faster_rcnn model would I just need frozen_graph.pb(Inference graph of trained model) ? as it mentions about .pb file in the attached guide on prerequisites section 3 point 2 so I am just assuming that would be frozen_graph of trained model.

Thanks