Implementation of Neural Image Assessment in Keras + Tensorflow with weights for MobileNetV2 model trained on AVA and TID dataset.
There are evaluater\evaluate_mobilenet_v2*.py scripts which can be used to evaluate an image using a specific model. The weights for the specific model must be downloaded from the [Releases Tab] and placed in the weights directory.
-t : Pass 'ava' or 'tid' dataset as train data.
The AVA dataset is required for training these models. I used 250,000 images to train and the last 5000 images to evaluate .
In direct training, you have to ensure that the model can be loaded, trained, evaluated and then saved all on a single GPU.
Use the train\train_mobilenet_v2.py scripts for direct training.
- Keras
- Tensorflow (CPU to evaluate, GPU to train)
- Numpy