1,000 images is not a very large data set but you should try and see if the model will be able to show reasonable accuracy. The important thing is to set aside a small portion of this data set for validation and check the accuracy on the images that were not used for training.
You can use data augmentation methods as is demonstrated in this tutorial: Data augmentation  |  TensorFlow Core 2
Random horizontal flips, random changes in brightness and contrast and some other transformations could be safely used to make your data set more diverse.