Systems and methods for image classification

1. A method for inspecting features of an image using an image inspection controller that includes a processor communicatively coupled to a memory, said method comprising:

receiving, at the processor, an input image;

performing, 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

prompting a user to select between approving and rejecting the displayed output image, and, in response to the user rejecting the displayed output image, performing at least one of i) an additional semantic segmentation process on the displayed output image, and ii) an additional object classification process on the displayed output image.

2. The method in accordance with claim 1 , further comprising receiving user input indicating a selection of performing the additional semantic segmentation process on the displayed output image.

3. The method in accordance with claim 2 , further comprising performing the additional semantic segmentation process on the displayed output image, the additional semantic segmentation process comprising generating and displaying an updated output image.

4. The method in accordance with claim 3 , further comprising prompting the user to select between approving the displayed updated output image, and at least one of i) performing a further semantic segmentation process on the displayed updated output image, and ii) performing a further object classification process on the displayed updated output image.

5. The method in accordance with claim 1 , further comprising receiving user input indicating a selection of performing the additional object classification process on the displayed output image.

6. The method in accordance with claim 5 , further comprising performing the additional object classification process on the displayed output image, the additional object classification process comprising generating and displaying an updated output image.

7. The method in accordance with claim 6 , further comprising prompting the user to select between approving the displayed updated output image, and at least one of i) performing a further semantic segmentation process on the displayed updated output image, and ii) performing a further object classification process on the displayed updated output image.

8. The method in accordance with claim 1 , wherein annotating at least one segment of the input image or annotating at least one object in the object mask comprises annotating the input image or the object mask, based on user input, on a graphical user interface displayed on a display device communicatively coupled to the processor.

9. 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 and rejecting the displayed output image, and, in response to the user rejecting the displayed output image, performing at least one of i) an additional semantic segmentation process on the displayed output image, and ii) an additional object classification process on the displayed output image.

10. The image inspection computing device in accordance with claim 9 , wherein said processor is further configured to receive user input indicating a selection of performing the additional semantic segmentation process on the displayed output image.

11. The image inspection computing device in accordance with claim 10 , wherein said processor is further configured to perform the additional semantic segmentation process on the displayed output image, the additional semantic segmentation process including generating and displaying an updated output image.

12. The image inspection computing device in accordance with claim 11 , wherein said processor is further configured to prompt the user to select between approving the displayed updated output image, and at least one of i) performing a further semantic segmentation process on the displayed updated output image, and ii) performing a further object classification process on the displayed updated output image.

13. The image inspection computing device in accordance with claim 9 , wherein said processor is further configured to receive user input indicating a selection of performing the additional object classification process on the displayed output image.

14. The image inspection computing device in accordance with claim 13 , wherein said processor is further configured to perform the additional object classification process on the displayed output image, the additional object classification process including generating and displaying an updated revised output image.

15. The image inspection computing device in accordance with claim 14 , wherein said processor is further configured to prompt the user to select between approving the displayed updated output image, and at least one of i) performing a further semantic segmentation process on the displayed updated output image, and ii) performing a further object classification process on the displayed updated output image.

16. The image inspection computing device in accordance with claim 9 , wherein to annotate at least one segment of the input image or to annotate at least one object in the object mask, said processor is configured to annotate the input image or the object mask, based on user input, on a graphical user interface displayed on a display device communicatively coupled to said processor.

17. 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 and rejecting the displayed output image, and, in response to the user rejecting the displayed output image, performing at least one of i) an additional semantic segmentation process on the displayed output image, and ii) an additional object classification process on the displayed output image.

18. The non-transitory computer-readable storage media in accordance with claim 17 , wherein to annotate at least one segment of the input image, the computer-executable instructions cause the computing device to receive user input indicating a selection of performing the additional semantic segmentation process on the displayed output image.

19. The non-transitory computer-readable storage media in accordance with claim 17 , wherein the computer-executable instructions cause the computing device to convert the object mask to a semantic segmentation mask.

20. The non-transitory computer-readable storage media in accordance with claim 17 , wherein the computer-executable instructions cause the computing device to convert a semantic segmentation mask to the object mask.