From 2f44bde4b45c1211da61f9c09ab145ca3ee72560 Mon Sep 17 00:00:00 2001 From: Dustin Franklin Date: Wed, 5 Apr 2023 11:30:58 -0400 Subject: [PATCH] updated docs --- README.md | 1 + docs/imagenet-camera-2.md | 4 ++-- docs/imagenet-tagging.md | 4 ++-- 3 files changed, 5 insertions(+), 4 deletions(-) diff --git a/README.md b/README.md index 696cf258b..770b41eb9 100644 --- a/README.md +++ b/README.md @@ -40,6 +40,7 @@ Hello AI World can be run completely onboard your Jetson, including inferencing * [Coding Your Own Image Recognition Program (Python)](docs/imagenet-example-python-2.md) * [Coding Your Own Image Recognition Program (C++)](docs/imagenet-example-2.md) * [Running the Live Camera Recognition Demo](docs/imagenet-camera-2.md) + * [Multi-Label Classification for Image Tagging](docs/imagenet-tagging.md) * [Object Detection](docs/detectnet-console-2.md) * [Detecting Objects from Images](docs/detectnet-console-2.md#detecting-objects-from-the-command-line) * [Running the Live Camera Detection Demo](docs/detectnet-camera-2.md) diff --git a/docs/imagenet-camera-2.md b/docs/imagenet-camera-2.md index 79623da2c..631490e7f 100644 --- a/docs/imagenet-camera-2.md +++ b/docs/imagenet-camera-2.md @@ -1,5 +1,5 @@ -

Back | Next | Contents +

Back | Next | Contents
Image Classification

@@ -47,7 +47,7 @@ The application can recognize up to 1000 different types of objects, since the c This concludes this section of the Hello AI World tutorial on image classification. Next, we're going to start using Object Detection networks, which provide us with the bounding box coordinates of multiple objects per frame. ## -

Next | Locating Object Coordinates with DetectNet +

Next | Multi-Label Classification for Image Tagging
Back | Coding Your Own Image Recognition Program

© 2016-2019 NVIDIA | Table of Contents

diff --git a/docs/imagenet-tagging.md b/docs/imagenet-tagging.md index 47a0ace6b..ea9d9644f 100644 --- a/docs/imagenet-tagging.md +++ b/docs/imagenet-tagging.md @@ -19,9 +19,9 @@ $ imagenet --model=resnet18-tagging-voc --topK=0 --threshold=0.25 "images/object $ imagenet.py --model=resnet18-tagging-voc --topK=0 --threshold=0.25 "images/object_*.jpg" images/test/tagging_%i.jpg" ``` -Using `--topK=0` means that all the classes with a confidence score exceeding the threshold will be returned. +Using `--topK=0` means that all the classes with a confidence score exceeding the threshold will be returned by the classifier. -

Next | Object Detection +

Next | Detecting Objects from Images
Back | Running the Live Camera Recognition Demo

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