---
title: "Pre-Trained Keras models"
author: "Prof. Eric A. Suess"
format: html
---

Here is a nice introduction to running pre-trained keras models for image recognition.  [pretrained](https://cran.rstudio.com/web/packages/keras/vignettes/applications.html)

```{r}
library(keras)

# instantiate the model
model <- application_resnet50(weights = 'imagenet')

# load the image
img_path <- "car.jpg"
img <- image_load(img_path, target_size = c(224,224))
x <- image_to_array(img)

# ensure we have a 4d tensor with single element in the batch dimension,
# the preprocess the input for prediction using resnet50
x <- array_reshape(x, c(1, dim(x)))
x <- imagenet_preprocess_input(x)

# make predictions then decode and print them
preds <- model %>% predict(x)
imagenet_decode_predictions(preds, top = 3)[[1]]
```