CPC G06T 7/0004 (2013.01) [G06F 16/53 (2019.01); G06F 17/15 (2013.01); G06N 3/04 (2013.01); G06N 20/00 (2019.01); G06T 2207/20081 (2013.01); G06T 2207/20084 (2013.01)] | 20 Claims |
1. A method comprising, by a computing system:
receiving one or more querying images associated with a container of a pharmaceutical product, wherein each of the one or more querying images is based on a particular angle of the container of the pharmaceutical product;
calculating, for the container of the pharmaceutical product, one or more confidence scores associated with one or more defect indications, respectively, by processing a plurality of pixels of the one or more querying images using a target machine-learning model; and
determining, for the container of the pharmaceutical product, a defect indication from the one or more defect indications based on a comparison between the one or more confidence scores and one or more predefined threshold scores, respectively, wherein:
the defect indication comprises one or more of a critical defect, a major defect, or a minor defect,
the pharmaceutical product comprises a lyophilized product, and
the major defect comprises a cake appearance defect, the cake appearance defect comprising one or more of an extreme product splash, a slanted cake, or a shrunken cake.
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