CPC G06N 3/04 (2013.01) [G06T 7/11 (2017.01); G06T 7/74 (2017.01); G06V 10/243 (2022.01); G06V 10/764 (2022.01); G06V 10/82 (2022.01); G06V 20/13 (2022.01); G06V 20/17 (2022.01); G06T 2207/20081 (2013.01); G06T 2207/20084 (2013.01)] | 12 Claims |
1. A computer-implemented method for detecting and correcting an orientation of a target object in an image, the method comprising:
training a deep neural network using a set of training images;
providing the image as input to the deep neural network, wherein the image is a segmented image;
utilizing the deep neural network to determine an initial orientation prediction for the target object; and
utilizing the deep neural network to obtain a rectified image from the segmented image based at least in part on the initial orientation prediction, wherein an orientation of the target object in the rectified image is within a threshold value of a target orientation,
wherein utilizing the deep neural network to obtain the rectified image comprises:
determining that the initial orientation prediction deviates from the target orientation by more than the threshold value; and
generating an aligned image from the segmented image.
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