Systems and Methods for Image Classification

An image inspection computing device comprising:

• a memory device;
• and
• at least one processor communicatively coupled to said memory device, wherein said at least one processor is configured to:
• receive an input image;
• perform, on the input image, one of a semantic segmentation process and an object classification process to generate an output image;
• wherein the semantic segmentation process comprises:
• annotating, by the processor, at least one segment of the input image to produce a semantic segmentation annotated image;
• generating, by the processor, a semantic segmentation model based on a semantic segmentation training vector derived from the semantic segmentation annotated image;
• applying, by the processor, the semantic segmentation model to each pixel of the input image to generate the output image;
• and
• displaying the output image;
• and
• wherein the object classification process comprises:
• annotating, by the processor, at least one object in an object mask to produce an object classification annotated image;
• generating, by the processor, an object classification model based on an object classification training vector derived from the object classification annotated image;
• applying, by the processor, the object classification model to the object mask to generate the output image;
• and
• displaying the output image;
• and
• prompt a user to select between approving the displayed output image, and at least one of i) performing an additional semantic segmentation process on the displayed output image, and ii) performing an additional object classification process on the displayed output image.

A non-transitory computer-readable storage media having computer-executable instructions embodied thereon, wherein when executed by a computing device comprising at least one processor in communication with a memory, the computer-executable instructions cause the computing device to:

• receive, at the processor, an input image;
• perform, on the input image, one of a semantic segmentation process and an object classification process to generate an output image;
• wherein the semantic segmentation process comprises:
• annotating, by the processor, at least one segment of the input image to produce a semantic segmentation annotated image;
• generating, by the processor, a semantic segmentation model based on a semantic segmentation training vector derived from the semantic segmentation annotated image;
• applying, by the processor, the semantic segmentation model to each pixel of the input image to generate the output image;
• and
• displaying the output image;
• and
• wherein the object classification process comprises:
• annotating, by the processor, at least one object in an object mask to produce an object classification annotated image;
• generating, by the processor, an object classification model based on an object classification training vector derived from the object classification annotated image;
• applying, by the processor, the object classification model to the object mask to generate the output image;
• and
• displaying the output image;
• and
• prompt a user to select between approving the displayed output image, and at least one of i) performing an additional semantic segmentation process on the displayed output image, and ii) performing an additional object classification process on the displayed output image.