TF-TRT error while trying to convert inception V2 model to TensorRT

leburi40 · December 3, 2020, 4:38am

Description

Getting error while trying to convert Inception V2 model to tensorRT model using TF-TRT library.

A clear and concise description of the bug or issue.
Unable to open table file faster_rcnn_inception_v2_coco_2018_01_28/model.ckpt.data-00000-of-00001: Data loss: not an sstable (bad magic number): perhaps your file is in a different file format and you need to use a different restore operator?

Environment

Ubuntu 16.04 (Tegra X2)

Model Link:
http://download.tensorflow.org/models/object_detection/faster_rcnn_inception_v2_coco_2018_01_28.tar.gz

AakankshaS · December 8, 2020, 7:44am

Hi @leburi40,
I am not able to access the link you have shared.
Can you please check.

Thanks!

leburi40 · December 8, 2020, 2:37pm

Hi @AakankshaS,

This is a model download link. I am able to directly download the model using this link. Please download the faster_rcnn_inception_v2_coco model from the below link.

github.com

tensorflow/models/blob/master/research/object_detection/g3doc/tf1_detection_zoo.md

# TensorFlow 1 Detection Model Zoo

[![TensorFlow 1.15](https://img.shields.io/badge/TensorFlow-1.15-FF6F00?logo=tensorflow)](https://github.com/tensorflow/tensorflow/releases/tag/v1.15.0)
[![Python 3.6](https://img.shields.io/badge/Python-3.6-3776AB)](https://www.python.org/downloads/release/python-360/)

We provide a collection of detection models pre-trained on the
[COCO dataset](http://cocodataset.org), the
[Kitti dataset](http://www.cvlibs.net/datasets/kitti/), the
[Open Images dataset](https://storage.googleapis.com/openimages/web/index.html),
the [AVA v2.1 dataset](https://research.google.com/ava/) the
[iNaturalist Species Detection Dataset](https://github.com/visipedia/inat_comp/blob/master/2017/README.md#bounding-boxes)
and the
[Snapshot Serengeti Dataset](http://lila.science/datasets/snapshot-serengeti).
These models can be useful for out-of-the-box inference if you are interested in
categories already in those datasets. They are also useful for initializing your
models when training on novel datasets.

In the table below, we list each such pre-trained model including:

*   a model name that corresponds to a config file that was used to train this

This file has been truncated. show original