In this case you can use the save_model_weights_tf function. When building more advanced models you may not be able to save the entire model using the save_model_tf function. You can download this file if you want to try the app. Note that to keep the code simple, it will only accept JPEG images with 28x28 pixels. You can see a live version of this app here. If you are deploying to RStudio Connect or Shinnyapps.io, don’t forget to set the RETICULATE_PYTHON environment variable so rsconnect can detect what python packages are required to reproduce your local environment. This app can be used locally or deployed using any Shiny deployment option. Library(shiny) library(keras) # Load the model model % array_reshape(., dim = c( 1, dim(.), 1)) paste0( "The predicted class number is ", predict_classes(model, img)) }) output $image <- renderPlot( shinyApp(ui, server)
0 Comments
Leave a Reply. |
AuthorWrite something about yourself. No need to be fancy, just an overview. ArchivesCategories |