Hello,
I am having a problem with an image classification.
The classifier training performes quite well but the image classification only classifies in 2 classes and the confusion matrix is very strange with much less pixels than it should have.
I put the Log results of classification and confusion matrix in this file: Log_File.docx (14.4 KB)
I would really apreciate if someone has any clue of what might be happening.
Thanks in advance
Thank you Cédric,
I repeated all the process in C:, just to check any problem with working in my One Drive and i made prt sc’s from all the steps so you can see everything i used during the process.
Below each prt sc you can find the results of the correspondent Log tab.
I am not sure, but maybe the problem comes from the way the classification result is stored. By default, ImageClassifier stores its output as a uint8 image, i.e. with grayscale levels between 0 and 256, but your classes go way above these values. Can you try to change the output pixel type of the output image :
I think Cédric is right : here your code cannot be encoded and the ImageClassifier app will only encode codes with values below 255.
There an other thing I think you should check : you’ve selected all samples in the sample selection step (the rate is 1). Usually, you should use a part of the samples for training, and keep samples for validation.
Thank you so much!
That was the problem.
I repeated the ImageClassifier and ComputeConfusionMatrix steps and copied the results to this doc: Results.docx (553.7 KB)
As you can see it worked and the evaluation with the independent validation set turns out to be quite good!
You were right. I repeated defining the uint as 32 and worked.
In respect to your second point, i was using an independent validation set but only in the ComputeConfusionMatrix step. This test areas were in another shp just for the final model evaluation step.