Feline comfort level classification system and method

1 . A method for generating a feline comfort level classification, the method comprising:

receiving one or more images of a feline;

generating a feline classification from the images with a feline classification model, wherein the feline classification corresponds to a feline type;

selecting a face detection model from one or more face detection models, wherein the selected face detection model corresponds to the feline type;

generating a positive facial indication for one or more of the images with the selected face detection model;

selecting a comfort level classification model from one or more comfort level classification models, wherein the selected comfort level classification model corresponds to the feline type; and

generating a feline comfort level classification from the images with the selected comfort level classification model;

wherein generating the feline classification comprises:

generating a set of feline probabilities, wherein each of the feline probabilities corresponds to one of the images and comprises a feline type and a confidence interval; and

generating the feline classification from the set of feline probabilities;

 wherein generating the feline classification from the set of feline probabilities comprises:

selecting the feline probabilities from the set of feline probabilities with a confidence interval higher than a first threshold confidence interval;

grouping the selected feline probabilities by feline type;

averaging the confidence intervals of the feline probabilities in each feline type group; and

generating the feline classification based at least in part on the feline type of the group with the highest average confidence interval.

2 . The method according to claim 1 , wherein the feline classification model comprises a machine-learning algorithm trained with a set of feline training images, wherein each of the feline training images comprises an image classified as either depicting a feline or not depicting a feline.

3 . The method according to claim 1 , wherein the feline classification model comprises a machine-learning algorithm trained with a set of feline training images, wherein each of the feline training images comprises an image classified as depicting a feline of a feline type from among a group of two or more feline types, or not depicting a feline of any of the feline types.

4 . The method according to claim 3 , wherein the group of feline types includes: brachycephalic, dolichocephalic, and mesocephalic.

5 . The method according to claim 1 , wherein the face detection model comprises a machine-learning algorithm trained with a set of facial training images, wherein each of the facial training images comprise an image classified as either depicting a face of the feline type or not depicting a face of the feline type.

6 . The method according to claim 1 , wherein the selected comfort level classification model is a machine-learning algorithm trained with a set of comfort level training images, wherein each of the comfort level training images comprises an image classified with a comfort level.

7 . The method according to claim 6 , wherein each of the comfort level training images is classified with a comfort level selected from a group comprising two discrete comfort levels.

8 . The method according to claim 6 , wherein each of the comfort level training images is classified with a comfort level selected from a group comprising two or more of: no pain, mild discomfort, discomfort, extreme discomfort, pain, acute pain, and chronic pain.

9 . The method according to claim 1 , wherein the images form a sequence of video frames.

10 . The method according to claim 1 , wherein receiving the images comprises capturing one or more images of the feline with an image capture device.

11 . The method according to claim 10 , wherein the image capture device comprises a camera of a tablet computer or a camera of a smartphone.

12 . An apparatus for generating a feline comfort level classification, the apparatus comprising a memory module storing instructions that when executed by a processor perform the method according to claim 1 .

13 . An apparatus according to claim 12 , wherein the memory module comprises a memory of a tablet computer or a memory of a smartphone.

14 . A method for generating a feline comfort level classification, the method comprising:

receiving one or more images of a feline;

generating a feline classification from the images with a feline classification model, wherein the feline classification corresponds to a feline type;

selecting a face detection model from one or more face detection models, wherein the selected face detection model corresponds to the feline type;

generating a positive facial indication for one or more of the images with the selected face detection model;

selecting a comfort level classification model from one or more comfort level classification models, wherein the selected comfort level classification model corresponds to the feline type; and

generating a feline comfort level classification from the images with the selected comfort level classification model;

wherein generating the feline classification comprises:

generating a set of feline probabilities, wherein each of the feline probabilities corresponds to one of the images and comprises a feline type and a confidence interval; and

generating the feline classification from the set of feline probabilities;

 wherein generating the positive facial indication comprises:

selecting the feline probabilities from among the set of feline probabilities with a confidence interval higher than a second threshold confidence interval and a feline type corresponding to the feline classification;

selecting the images corresponding to the selected feline probabilities;

generating a set of facial probabilities, wherein each of the facial probabilities corresponds to one of the selected images and comprises a facial indication and a confidence interval; and

generating the positive facial indication based at least in part on the set of facial probabilities.

15 . The method according to claim 14 , wherein generating the positive facial indication from the set of facial probabilities comprises:

selecting the facial probabilities from the set of facial probabilities with a confidence interval higher than a threshold confidence interval;

averaging the confidence interval of each of the selected facial probabilities to generate an average confidence interval; and

verifying the average confidence interval exceeds a positive facial indication threshold.

16 . A method for generating a feline comfort level classification, the method comprising:

receiving one or more images of a feline;

generating a feline classification from the images with a feline classification model, wherein the feline classification corresponds to a feline type;

selecting a face detection model from one or more face detection models, wherein the selected face detection model corresponds to the feline type;

generating a positive facial indication for one or more of the images with the selected face detection model;

selecting a comfort level classification model from one or more comfort level classification models, wherein the selected comfort level classification model corresponds to the feline type; and

generating a feline comfort level classification from the images with the selected comfort level classification model;

wherein generating the feline classification comprises:

generating a set of feline probabilities, wherein each of the feline probabilities corresponds to one of the images and comprises a feline type and a confidence interval; and

generating the feline classification from the set of feline probabilities;

wherein generating the feline comfort level classification comprises:

selecting the feline probabilities from the set of feline probabilities with a confidence interval higher than a threshold and a feline type corresponding to the feline classification;

selecting the images corresponding to the selected feline probabilities;

generating a set of comfort level probabilities comprising, for each one of the selected images, a comfort level and a confidence interval; and

generating the feline comfort level classification based at least in part on the set of comfort level probabilities.

17 . The method according to claim 16 , wherein generating the feline comfort level classification from the set of comfort level probabilities comprises:

selecting the comfort level probabilities from among the set of comfort level probabilities with a confidence interval higher than a threshold comfort confidence interval;

averaging the confidence interval of each of the selected comfort level probabilities for each comfort level; and

generating the feline comfort level classification based at least in part on the comfort level with the highest average confidence interval.