Automatic picture classifying system and method in a dining environment

1. An automatic classifying system in a dining environment, comprising:

a server for directly or indirectly receiving a set of pictures, the server including a picture analysis component to classify a picture, from the set of pictures, wherein the set of pictures are received from an electronic device,

wherein the server includes a picture learning engine for analyzing a plurality of pictures to find a first feature associated with at least some pictures from the plurality of pictures,

wherein the picture analysis component selects a first classification for the picture based on determining whether the first feature is present in the picture,

wherein the server transmits the analysis result to a web-platform system for initiating display of the picture,

wherein the server provides access of the picture to a social media platform, the social media platform displaying the picture, the social media platform enabling one or more users of the social media platform to interact with the picture,

wherein the first feature associated with the at least some pictures from the plurality of pictures comprises a common feature associated with the at least some pictures, and

wherein the picture analysis component selects the first classification for the picture based on a first classification weight associated with the first classification being greater than a second classification weight associated with a second classification.

2. The system of claim 1 , wherein the picture learning engine operates based on a deep learning operation.

3. The system of claim 1 , wherein the picture analysis component further selects the first classification for the picture based on the first classification weight associated with the first classification being greater than the second classification weight associated with the second classification.

4. The system of claim 1 , wherein the plurality of pictures are associated with a single classification.

5. The system of claim 1 , wherein the plurality of pictures are associated with multiple classifications.

6. The system of claim 1 , wherein the first feature associated with the at least some pictures from the plurality of pictures comprises the common feature associated with the at least some pictures.

7. The system of claim 6 , wherein the plurality of pictures are analyzed by the picture learning engine before the server receives the set of pictures.

8. The system of claim 7 ,

wherein the picture comprises at least one of a dining environment appearance-related picture, a dining environment staff-related picture, a dining environment menu-related picture, a main course-related picture, a drink-related picture, or a dessert-related picture, and

wherein the picture learning engine operates based on a deep learning operation.

9. The system of claim 1 , wherein the server modifies the first classification associated with the picture to the second classification or a third classification based on picture-creating time data associated with the picture.

10. The system of claim 1 , wherein the server modifies the first classification associated with the picture based on comparing the first classification weight associated with the picture with a weight approximation of a classification corresponding to a time-checking point.

11. The system of claim 10 , wherein the time-checking point is earlier than or later than the picture-creating time.

12. The system of claim 1 , wherein the server modifies the first classification associated with the picture to the second classification or a third classification based on a second picture received in the set of pictures being classified as the second classification or the third classification and based on time data associated with the picture or the second picture.

13. The system of claim 1 , wherein the server modifies the first classification associated with the picture to the second classification or a third classification based on a second picture received in the set of pictures being classified as the second classification or the third classification.

14. The system of claim 13 , wherein the second picture is positioned or ordered immediately before or immediately after the picture.

15. The system of claim 1 , wherein the server modifies the first classification associated with the picture to the second classification or a third classification based on a second picture received in the set of pictures being classified as the second classification or the third classification and based on a third picture received in the set of pictures being classified as the second classification or the third classification.

16. The system of claim 15 , wherein the second picture is positioned or ordered immediately before the picture and the third picture is positioned or ordered immediately after the picture.

17. The system of claim 1 , wherein the server reassigns the first classification associated with the picture to the second classification or a third classification based on data not associated with the picture.

18. The system of claim 1 , wherein the server modifies the first classification associated with the picture to the second classification or a third classification based on data associated with a second picture or a third picture received, positioned, or ordered before, after, or simultaneously with the picture.

19. The system of claim 1 , wherein the server modifies the first classification associated with the picture to the second classification or a third classification based on data associated with a second picture and a third picture received, positioned, or ordered before and after the picture, respectively.

20. The system of claim 1 , wherein the server modifies the first classification associated with the picture to the second classification or a third classification based on comparing a classification weight associated with the picture with a weight approximation associated with the picture and a second picture received, positioned, or ordered before, after, or simultaneously with the picture.