Systems and methods for using image data to analyze an image

1 . A method, comprising:

identifying, by one or more processors coupled to non-transitory memory, a respective classification and a respective bounding box generated using an artificial intelligence model for an object depicted in each image of a sequence of images captured during operation of an autonomous vehicle;

tracking, by the one or more processors, the object in the sequence of images based on the respective bounding box of each image of the sequence of images and a tracking identifier corresponding to the object;

determining, by the one or more processors, a correction to the respective classification of at least one image of the sequence of images responsive to tracking the object in the sequence of images, determining the correction further comprising:

calculating, by the one or more processors, a number of images in the sequence of images having the same respective classification for the object; and

training, by the one or more processors, the artificial intelligence model based on the correction,

wherein tracking the object further comprises executing, by the one or more processors, a voting algorithm based on the number of images in the sequence of images having the same respective classification for the object.

2 . The method of claim 1 , wherein tracking the object in the sequence of images comprises determining, by the one or more processors, a predicted position of the respective bounding box of a second image of the sequence of images based on the respective bounding box of a first image of the sequence of images.

3 . The method of claim 1 , wherein the voting algorithm comprises assigning, by the one or more processors, for the voting algorithm, a respective weight value to the respective classification of each image of the sequence of images in which the object was tracked.

4 . The method of claim 1 , further comprising:

providing, by the one or more processors, the artificial intelligence model to an autonomy system of the autonomous vehicle.

5 . The method of claim 1 , wherein tracking the object in the sequence of images comprises determining, by the one or more processors, a distance of the object from the autonomous vehicle.

6 . A system, comprising:

one or more processors coupled to memory, the one or more processors configured to:

identify a respective classification and a respective bounding box generated using an artificial intelligence model for an object depicted in each image of a sequence of images captured during operation of an autonomous vehicle;

track the object in the sequence of images based on the respective bounding box of each image of the sequence of images and a tracking identifier corresponding to the object;

determine a correction to the respective classification of at least one image of the sequence of images responsive to tracking the object in the sequence of images, determine the correction further comprising:

calculate a number of images in the sequence of images having the same respective classification for the object; and

train the artificial intelligence model based on the correction,

wherein the one or more processors are further configured to track the object by executing a voting algorithm based on the number of images in the sequence of images having the same respective classification for the object.

7 . The system of claim 6 , wherein the one or more processors are further configured to:

determine a predicted position of the respective bounding box of a second image of the sequence of images based on the respective bounding box of a first image of the sequence of images.

8 . The system of claim 6 , wherein the one or more processors are further configured to:

assign, for the voting algorithm, a respective weight value to the respective classification of each image of the sequence of images in which the object was tracked.

9 . The system of claim 6 , wherein the one or more processors are further configured to:

provide the artificial intelligence model to an autonomy system of the autonomous vehicle.

10 . The system of claim 6 , wherein the one or more processors are further configured to:

determine a distance of the object from the autonomous vehicle.

11 . An autonomous vehicle having a processor configured to:

receive a sequence of images captured during operation of the autonomous vehicle;

generate, using an artificial intelligence model, a respective classification and a respective bounding box for an object depicted in each image of the sequence of images;

track the object in the sequence of images based on the respective bounding box of each image of the sequence of images and a tracking identifier corresponding to the object;

determine a correction to the respective classification of at least one image of the sequence of images responsive to tracking the object in the sequence of images, determine the correction further comprising:

calculate a number of images in the sequence of images having the same respective classification for the object; and

provide the correction to an autonomous navigation process of the autonomous vehicle,

wherein the processor is further configured to track the object by executing a voting algorithm based on the number of images in the sequence of images having the same respective classification for the object.

12 . The autonomous vehicle of claim 11 , wherein the processor is further configured to determine a distance of the object from the autonomous vehicle.

13 . The autonomous vehicle of claim 11 , wherein the processor is further configured to:

determine a predicted position of the respective bounding box of a second image of the sequence of images based on the respective bounding box of a first image of the sequence of images.

14 . The autonomous vehicle of claim 11 , wherein the processor is further configured to:

assign, for the voting algorithm, a respective weight value to the respective classification of each image of the sequence of images in which the object was tracked.