How can i give a trained model some images as an input ?

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I trained a model with classification learner to classify fruits. Now i want to test my model. How can i give the model some images as an input ?

Accepted Answer

Mukul Rao
Mukul Rao on 5 Dec 2017
Hello, in order to use the trained model to predict new data, you will first have to export the trained model to the workspace. You can click on the "Export Model" drop-down in the Classification Learner App, and select the first option. Once you have the trained model in the MATLAB workspace, you can call its "predict" method and supply new image data to make predictions.
  3 Comments
Mukul Rao
Mukul Rao on 5 Dec 2017
Hi Lukas, yes that makes sense. You might want to take a look at this example that demonstrates the workflow. Using the bag of features, you will have to create an "imageCategoryClassifierObject" with the "trainImageCategoryClassifier" function. You can call the "predict" method on the classifier object and plug in the the new image data set as the input without having to convert it to a table. I believe you might have referred the predict method for a different classifier class in the documentation.
Lukas Sohlbach
Lukas Sohlbach on 5 Dec 2017
Hi Mark, does the "imageCategoryClassifierObject" only works on SVM ? Because my trained model based on a Decision Tree. I attached my trained classifier. This classifier has a function "c.predictFcn" link (where c is a variable for the classifier name) and this function requests a table as an input. Is there any possibility, after using a bagOfFeatures to train a Decision Tree, to this function to make a prediction on a new image? By the way, thanks for helping me out.

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