Optimal format selection for video players based on predicted visual quality using machine learning

An apparatus comprising:

• a memory to store a video;
• and
• a processing device, operatively coupled to the memory, to:
• provide sampled frames of the video as input to a trained machine learning model;
• obtain one or more outputs from the trained machine learning model;
• and
• extract, from the one or more outputs, a quality score that indicates a perceptual quality of the video at a first video format, a first transcoding configuration, and a first display resolution.

A non-transitory machine-readable storage medium storing instructions which, when executed, cause a processing device to perform operations comprising:

• generating training data for a machine learning model to be trained to identify quality scores for a set of transcoded versions of a new video at a set of display resolutions, wherein generating the training data comprises:
• generating a plurality of reference transcoded versions of a reference video;
• obtaining quality scores for frames of the plurality of reference transcoded versions of the reference video;
• generating a first training input comprising a set of color attributes, spatial attributes, and temporal attributes of the frames of the reference video;
• and
• generating a first target output for the first training input, wherein the first target output comprises the quality scores for the frames of the plurality of reference transcoded versions of the reference video;
• and
• providing the training data to train the machine learning model on (i) a set of training inputs comprising the first training input and (ii) a set of target outputs comprising the first target output.