The image classification algorithm takes an image as input and outputs a probability for each provided class label. Training datasets must consist of images in .jpg, .jpeg, or .png format.

It is possible to create an MNIST image classification model by feeding the model one-dimensional vectors of 784 values. However, this approach isn't feasible for large images with millions of pixels, ...

Fortunately, with ample spare time, those who share my problem can now use an image captioning model in TensorFlow to caption their photos and put an end to the pesky first-world problem.