Test data generator – model.evaluate()

Hello, I’m trying to measure the performance (accuracy and loss) of my model and I discovered the evaluate() function for this.

My test data (34 pictures) is saved in a ‘test’ folder, so I tried to create an ImageDataGenerator and then to generate my data using flow_from_directory.

I receive a “Found 34 images belonging to 1 classes.” message. However, the result I get in the terminal for this code line result = seqModel.evaluate(data, batch_size=1, verbose=1) is a very weird one: 2/2 [==============================] – 0s 5ms/step – loss: 282.6923 – accuracy: 0.7353

Why do I receive a “2/2” everytime when running the script now, no matter what batch_size I choose? And why is my loss 282.6923, while accuracy is 0.7353? Doesn’t it look super weird? I know I’m doing something wrong, but I just can’t figure it out – maybe when creating the data generator or maybe when using flow_from_directory? (When I add the validationDataGenerator as first argument – in order to test it – it seems all fine, but here I just can’t figure it out.)

A little bit of help would be appreciated. 🙂