This repository implements Neural Image Assessment (NIMA), a deep learning approach to predict perceived image quality. It uses Keras and TensorFlow to train convolutional neural networks on the AVA dataset, producing Mean + Standard Deviation quality scores for images. The project provides trained weights for multiple model architectures and includes evaluation scripts to score individual images or entire directories. It can also serve as a differentiable loss function to optimize image generation models.