フィルターのクリア

classify an image?

1 回表示 (過去 30 日間)
Tathva
Tathva 2023 年 5 月 15 日
編集済み: Tathva 2023 年 7 月 16 日
. Thank you. help has been appreciated
  1 件のコメント
KSSV
KSSV 2023 年 5 月 15 日
Save the net and use it. You need to provide inputs in the way you have trained.

サインインしてコメントする。

回答 (1 件)

Sandeep
Sandeep 2023 年 5 月 22 日
Hi Tathva,
To use a trained neural network in MATLAB to classify a random image, you can use the classify function when you have your trained network stored in an appropriate variable. Assuming that you have your network stored in variable called net a sample implementation is given below,
% Load the pretrained network
load('network.mat');
% Load a random image to classify
im = imread('my_image.jpg');
% Resize the image to the same size as the training images
im = imresize(im,net.Layers(1).InputSize(1:2));
% Classify the image
label = classify(net,im);
% Display the predicted label
disp([char(label)]);
The image is resized to the same size that was used during training of the neural network. We use the classify function to classify the image, which returns the predicted label for the image.
For more insight about the classify function, refer the following documentation: Classify data using trained deep learning neural network

カテゴリ

Help Center および File ExchangeImage Data Workflows についてさらに検索

製品


リリース

R2022b

Community Treasure Hunt

Find the treasures in MATLAB Central and discover how the community can help you!

Start Hunting!

Translated by