Using Keras, how can I input an X_train of images (more than a thousand images)?

Question

My application is accident-avoidance car systems using Machine Learning (Convolutional Neural Networks). My images are 200x100 JPG images and the output is an array of 4 element

Answer 1

This Keras blog post, Building powerful image classification models using very little data, is an excellent tutorial for training a model on images stored in directories. It also introduces the ImageDataGenerator class, which has the member function flow_from_directory referenced in @isaac-moore's answer. flow from directory can be used train on images, where the directory structure is used to deduce the value of Y_train.

The three python scripts that accompany the tutorial blog post can be found at the links below:

1. classifier_from_little_data_script_1.py
2. classifier_from_little_data_script_2.py
3. classifier_from_little_data_script_3.py

(Of course, these links are in the blog post itself, but the links are not centrally located.) Note that scripts 2 and 3 build on the output of the previous. Also, note that additional files will need to be downloaded from Kaggle and Github.