Help us understand the problem. What is going on with this article?

Jetson NanoでTensorRTのメモ

リポジトリのclone

$ git clone https://github.com/tensorflow/models

Protocol Bufferをインストール

cd ./models/research
wget -O protobuf.zip https://github.com/protocolbuffers/protobuf/releases/download/v3.7.0/protoc-3.7.0-linux-aarch_64.zip
unzip protobuf.zip
./bin/protoc object_detection/protos/*.proto --python_out=.

テスト

export PYTHONPATH=$PYTHONPATH:`pwd`:`pwd`/slim
python3 object_detection/builders/model_builder_test.py

モデルのダウンロード

cd
git clone https://github.com/karaage0703/object_detection_tools
~/object_detection_tools/models
./get_ssd_mobilenet_v1_coco_model.sh

TensorRT

cd
git clone https://github.com/NVIDIA-AI-IOT/tf_trt_models
cd tf_trt_models

convert

cp ../object_detection_tools/scripts/convert_rt_model.py .
python3 convert_rt_model.py -c='../models/research/object_detection/samples/configs/ssd_mobilenet_v1_coco.config' -m='../object_detection_tools/models/ssd_mobilenet_v1_coco_2018_01_28/model.ckpt' -o='./frozen_inference_graph_trt.pb'

python3 convert_rt_model.py -c='../models/research/object_detection/samples/configs/ssd_inception_v2_coco.config' -m='../object_detection_tools/models/ssd_inception_v2_coco_2018_01_28/model.ckpt' -o='./frozen_inference_graph_trt.pb'

importの追加

object_detection.py
import tensorflow as tf
import tensorflow.contrib.tensorrt as trt # <-- add

物体検出

cd ./object_detection_tools
python3 scripts/object_detection.py -l='models/coco-labels-paper.txt' -m='../tf_trt_models/frozen_inference_graph_trt.pb' -d='jetson_nano_raspi_cam'

お世話になった情報

https://qiita.com/karaage0703/items/67050f2418aa6bb3851a

Why not register and get more from Qiita?
  1. We will deliver articles that match you
    By following users and tags, you can catch up information on technical fields that you are interested in as a whole
  2. you can read useful information later efficiently
    By "stocking" the articles you like, you can search right away
Comments
No comments
Sign up for free and join this conversation.
If you already have a Qiita account
Why do not you register as a user and use Qiita more conveniently?
You need to log in to use this function. Qiita can be used more conveniently after logging in.
You seem to be reading articles frequently this month. Qiita can be used more conveniently after logging in.
  1. We will deliver articles that match you
    By following users and tags, you can catch up information on technical fields that you are interested in as a whole
  2. you can read useful information later efficiently
    By "stocking" the articles you like, you can search right away
ユーザーは見つかりませんでした