Conversion of mobilenetV2 to tensorrt failing for model trained with Tensorflow Object Detection API

Autonomous Machines Jetson & Embedded Systems Jetson Nano
1

Hello, I have a Jetson Nano. I want to run object detection trained with tensorflow object detection API on the Nano. By default, the tensorflow frozen model runs with very huge latency (Mobilenet v2 ~ 134ms per image). I have tried running the mobilenet V2 model given by @dusty_nv by following the topic: [url]https://devtalk.nvidia.com/default/topic/1049802/jetson-nano/object-detection-with-mobilenet-ssd-slower-than-mentioned-speed/post/5327974[/url]. When I tried to convert my model, I encountered the following error:

ERROR: UFFParser: Parser error: BoxPredictor_0/Reshape: Reshape: -1 dimension specified more than 1 time

Jetson Nano
CUDA Version: 10.0
TensorRT version: 5.0.6.3
Distributor ID: Ubuntu
Description: Ubuntu 18.04.2 LTS
Release: 18.04
Codename: bionic

I have been stuck with conversion for a long time, any help is highly appreciated. Also will output plugin for FPN be provided soon?

2

Hi,

I have double checked the comment of Dusty and it can work correctly:
[url]https://devtalk.nvidia.com/default/topic/1049802/jetson-nano/object-detection-with-mobilenet-ssd-slower-than-mentioned-speed/post/5327974/#5327974[/url]

Please noticed that the steps is running with pure TensorRT rather than TF-TRT.
Thanks.

3

Hello,

Thank you for your reply. I have also been able to run the SSD mobilenet v2(~ 26ms per image) provided by him (Sorry for not mentioning this earlier). However I am having trouble converting my trained mobilenet with Tensorflow Object Detection API. I am not able to create trt engine after the model is converted to uff. I read in a separate thread that the recent protoc of the Tensorflow Object Detection API is causing some problems.

Could you please let me know how to overcome this?

4

Hi,

Is your there any new layer you used from the SSD mobilenet v2?
Would you mind to share the model or the difference with us?

Thanks.

5

Thank you for looking into this.

I will attach my pipeline.config file, a set of weights, the frozen tf model and the converted uff model.

[url]Avishek Mobilenet V2 - Google Drive

6

I have figured out this particular issue. During the conversion of the model to frozen graph, I mentioned the batch size to be -1. In the newer tensorflow object detection API, the box coder is built through “research/object_detection/predictors/box_head.py” file, which has the following line (Line 183)

box_encodings = tf.reshape(box_encodings, [batch_size, -1, 1, self._box_code_size])

Since I am providing batch size as -1, the reshape encounter two -1 dimensions. But after I mention non zero positive batch size, I am getting yet another error.

ERROR: Parameter check failed at: …/builder/Layers.h::setAxis::315, condition: axis>=0
ERROR: Concatenate/concat: all concat input tensors must have the same dimensions except on the concatenation axis

Could you please look into this.

7

Hi,

Please check this comment for some information:
[url]https://devtalk.nvidia.com/default/topic/1050465/jetson-nano/how-to-write-config-py-for-converting-ssd-mobilenetv2-to-uff-format/[/url]

Thanks.

8

Thank you so much. :-)

9

Hi @avishek.alex15

I am trying to optimise SSD Mobilenet v2 model trained on custom dataset.

Which commit of object detection API /models you are using to generate frozen graph ?

I am at commit e21dcdd03250900da35b267f34010efd738d93cf

I am getting error like when I try to optimise model:

[TensorRT] ERROR: UFFParser: Validator error: Cast: Unsupported operation _Cast

Please help.