Shape error in image classification model in Keras R - r

Question

I am having trouble with one area of code and it prevents me from finishing my research paper. I am new to Machine Learning and R, but I have learned a lot so far. Here is my code:
# Install packages and libraries
install.packages("keras")
source("http://bioconductor.org/biocLite.R")
library(keras)
library(EBImage)
# Read images
setwd('C:/Users/ebarn/Desktop/DataSet')
pics <- c('p1.jpg', 'p2.jpg', 'p3.jpg', 'p4.jpg', 'p5.jpg',
'p6.jpg','c1.jpg', 'c2.jpg', 'c3.jpg', 'c4.jpg', 'c5.jpg',
'c6.jpg')
mypic <- list()
for (i in 1:12) {mypic[[i]] <- readImage(pics[i])}
# Explore
print(mypic[[1]])
display(mypic[[1]])
display(mypic[[8]])
summary(mypic[[1]])
hist(mypic[[12]])
str(mypic)
# Resize
for (i in 1:12) {mypic[[i]] <- resize(mypic[[i]], 28, 28)}
str(mypic)
# Reshape
28*28*3
for (i in 1:12) {mypic[[i]] <- array_reshape(mypic[[i]], c(28,
28, 3))}
str(mypic)
# Row Bind
trainx <- NULL
for(i in 1:5) {trainx <- rbind(trainx, mypic[[i]])}
str(trainx)
for(i in 7:11) {trainx <- rbind(trainx, mypic[[i]])}
str(trainx)
testx <- rbind(mypic[[6]], mypic[[12]])
trainy <- c(0,0,0,0,0,1,1,1,1,1)
testy <- c(0, 1)
# One Hot Encoding
trainLabels <- to_categorical(trainy)
testLabels <- to_categorical(testy)
trainLabels
# Model
model <- keras_model_sequential()
model %>%
layer_dense(units = 256, activation = 'relu', input_shape =
c(2352))
%>%
layer_dense(units = 128, activation = 'relu')
%>%
layer_dense(units = 2, activation = 'softmax')
summary(model)
# Compile
model %>%
compile(loss = 'sparse_categorical_crossentropy',
optimizer = optimizer_rmsprop(),
metrics = c('accuracy'))
# model.add(Dense(10, activation = 'softmax'))
# Fit Model
history <- model %>%
fit(trainx, trainLabels, epochs = 30, batch_size = 32,
validation_split = 0.2)
plot(history)
# Evaluation & Prediction - train data
model %>% evaluate(trainx, trainLabels)
The Fit Model method will not print out my graph. Here is the error it gives me:
ValueError: Error when checking target: expected dense _1 to have shape (1,) but got array with shape (2,)

Answer 1

You are one-hot encoding the labels:
# One Hot Encoding
trainLabels <- to_categorical(trainy)
testLabels <- to_categorical(testy)
Therefore, they are no longer sparse labels and you need to use categorical_crossentropy as the loss function instead of sparse_categorical_crossentropy. Alternatively, you can comment the one-hot encoding lines.