Methods and Systems for Processing Imagery

A computer-implemented method comprising:

• providing, by one or more computing devices, one or more machine learning (ML) models configured to process imagery to identify images determined to be suitable for one or more different and distinct uses;
• receiving, by the one or more computing devices, data describing imagery comprising a plurality of different and distinct frames for processing using the one or more ML models;
• determining, by the one or more computing devices, based at least in part on the one or more ML models and the data describing the imagery, and for each frame of the plurality of different and distinct frames, one or more scores for the frame, each score of the one or more scores indicating a determined measure of suitability of the frame with respect to a use of the one or more different and distinct uses;
• and
• communicating, by the one or more computing devices, data indicating, for each frame of one or more frames of the plurality of different and distinct frames, at least one of the one or more scores for the frame.

A system comprising:

• one or more processors;
• and
• a memory storing instructions that when executed by the one or more processors cause the system to perform operations comprising:
• receiving data describing imagery comprising a plurality of different and distinct frames;
• determining, based at least in part on one or more machine learning (ML) models and the data describing the imagery, and for each frame of the plurality of different and distinct frames, one or more scores for the frame, each score of the one or more scores indicating a determined measure of suitability of the frame with respect to one or more of various different and distinct uses for which the one or more ML models are configured to determine suitability of imagery;
• providing a graphical user interface that identifies at least one of the frames as suitable for the one or more of various different and distinct uses based at least in part on the scores determined for the plurality of different and distinct frames.

One or more non-transitory computer-readable media that store instructions that, when executed by one or more processors, cause the one or more processors to perform operations, the operations comprising:

• receiving data describing imagery comprising a plurality of different and distinct frames;
• and
• determining, based at least in part on one or more machine learning (ML) models and the data describing the imagery, and for each frame of the plurality of different and distinct frames, one or more scores for the frame, each score of the one or more scores indicating a determined measure of suitability of the frame with respect to one or more of various different and distinct uses for which the one or more ML models are configured to determine suitability of imagery;
• and
• providing a graphical user interface that identifies at least one of the frames as suitable for the one or more of various different and distinct uses based at least in part on the scores determined for the plurality of different and distinct frames.