1. A method of generating contextual thumbnail previews, the method comprising:
extracting, by a server, data associated with a project comprising at least one component,
wherein the data comprises one or more breakpoints, and one or more locales defined for the at
5 least one component of the project;
generating, by the server, a contextual map based on the data received;
generating, by the server, one or more interim thumbnails based on the contextual map;
mapping, by the server, the one or more interim thumbnails with pre-stored thumbnails
within a database through a Machine Learning (ML) model;
10 generating, by the server, a consolidated contextual map based on the contextual map and
the mapping; and
generating, by the server, one or more final thumbnails corresponding to the contextual
thumbnail previews based on the consolidated contextual map.
15 2. The method of claim 1, wherein the one or more interim thumbnails are stored in a temporary
database and removed after generating the one or more final thumbnails.
3. The method of claim 1, further comprising:
determining, by the server, a similarity score for each of the one or more interim
20 thumbnails based on the mapping; and
assigning, by the server, a category from a plurality of pre-defined categories to the each
of the one or more interim thumbnails, based on the similarity score and a pre-defined tolerance.
25 4. The method of claim 3, wherein the plurality of categories comprises an identical-match
category, a similar match category, and a non-match category.
5. The method of claim 4, wherein the contextual map and the consolidated contextual map
correspond to a matrix that comprises a plurality of cells, wherein each of the plurality of cells
30 represents a thumbnail.
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6. The method of claim 5, wherein cells corresponding to thumbnails with the identical-match
category, or the similar-match category are consolidated to generate the contextual thumbnail
previews, and cells corresponding to thumbnails with the non-match category are retained.
5 7. The method of claim 3, further comprising:
transmitting, by the server, a notification to a user, upon failure in assigning the category
from the plurality of pre-defined categories;
receiving, by the server, a feedback from the user, in response to transmitting the
notification; and
10 training, by the server, the ML model based on the feedback received from the user,
through a feedback mechanism.
8. The method of claim 1, wherein the one or more locales are extracted from a hyper localization
database, and wherein the one or more locales comprises at least one of a geography and a
15 language.
9. The method of claim 1, further comprising:
identifying, by the server, a change in the contextual map, wherein a type of the change
is at least one of a structural change, a metadata change, and a data change; and
20 upon a successful identification of the change, updating, by the server, the contextual
thumbnail previews.
10. A system for generating contextual thumbnail previews, the system comprising:
a processing circuitry; and
25 a memory communicatively coupled to the processing circuitry, wherein the memory
stores processor-executable instructions, which, on execution, causes the processing circuitry to:
extract data associated with a project comprising at least one component, wherein
the data comprises one or more breakpoints, and one or more locales defined for the at least
one component of the project;
30 generate a contextual map based on the data received;
generate one or more interim thumbnails based on the contextual map;
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map the one or more interim thumbnails with pre-stored thumbnails within a
database through a Machine Learning (ML) model;
generate a consolidated contextual map based on the contextual map and the
mapping; and
5 generate one or more final thumbnails corresponding to the contextual thumbnail
previews based on the consolidated contextual map.