Neural network-based image colorization on image/video editing applications
A computing system and method for neural network-based image colorization is provided. The computing system obtains a reference color image by selective application of a color effect on a region of interest of an input image and controls a display device to display a first node graph on a Graphical User Interface of an image/video editing application. The first node graph includes a colorization node representing a first workflow for colorization of at least a first object in grayscale images of a first image feed. The computing system selects the reference color image based on a user input and executes the first workflow associated with the colorization node by feeding the reference color image and the first image feed as an input to a neural network-based colorization model. The computing system receives a second image feed comprising colorized images as output of the neural network-based colorization model for the input.
1. A method, comprising:
in a computing system:
obtaining a reference color image by selectively applying a color effect on a region of interest (ROI) of an input image;
controlling a display device to display a first node graph on a Graphical User Interface (GUI) of an image/video editing application, wherein
the first node graph comprises a colorization node representing a first workflow for colorization of at least a first object in one or more grayscale images of a first image feed;
selecting the obtained reference color image based on a first user input; and
executing the first workflow associated with the colorization node, the executing comprising:
feeding the selected reference color image and the first image feed as an input to a neural network-based colorization model; and
receiving, as an output of the neural network-based colorization model for the input, a second image feed comprising one or more colorized images, each of which comprises at least the first object colorized based on color effect on the ROI.
2. The method according to claim 1 , further comprising:
controlling the display device to display a second node graph on the GUI of the image/video editing application,
wherein the second node graph represents a second workflow for obtaining the reference color image from the input image.
3. The method according to claim 2 , further comprising executing the second workflow, the executing comprising:
selecting the ROI from the input image;
applying a first set of image filters on the selected ROI; and
based on the application of the first set of image filters, applying the color effect on the selected ROI of the input image to obtain the reference color image.
4. The method according to claim 1 , wherein the colorization node corresponds to a software plugin which includes program instructions for execution of the first workflow.
5. The method according to claim 1 , further comprising:
controlling the display device to display a setting of the colorization node on the GUI of the image/video editing application,
wherein the setting includes a set of options corresponding to a set of neural network-based colorization models;
receiving a second user input comprising a selection of a first option of the set of options; and
selecting the neural network-based colorization model from among the set of neural network-based colorization models, based on the second user input.
6. The method according to claim 1 , wherein the neural network-based colorization model transfers the color effect on the ROI of the reference color image to at least the first object in each of the one or more grayscale images of the first image feed, to output the second image feed comprising the one or more colorized images.
7. The method according to claim 1 , further comprising controlling the display device to display the second image feed on the GUI of the image/video editing application.
8. A computing system, comprising:
circuitry configured to:
obtain a reference color image based on a selective application of a color effect on a region of interest (ROI) of an input image;
control a display device to display a first node graph on a Graphical User Interface (GUI) of an image/video editing application, wherein
the first node graph comprises a colorization node which represents a first workflow for colorization of at least a first object in one or more grayscale images of a first image feed;
select the obtained reference color image based on a first user input; and
execute the first workflow associated with the colorization node by:
feeding the selected reference color image and the first image feed as an input to a neural network-based colorization model; and
receiving, as an output of the neural network-based colorization model for the input, a second image feed comprising one or more colorized images, each of which comprises at least the first object colorized based on color effect on the ROI.
9. The computing system according to claim 8 , wherein the circuitry is further configured to control the display device to display a second node graph on the GUI of the image/video editing application, and
wherein the second node graph represents a second workflow to obtain the reference color image from the input image.
10. The computing system according to claim 9 , wherein the circuitry is further configured to execute the second workflow by:
selecting the ROI from the input image;
applying a first set of image filters on the selected ROI; and
based on the application of the first set of image filters, applying the color effect on the selected ROI of the input image to obtain the reference color image.
11. The computing system according to claim 8 , wherein the colorization node corresponds to a software plugin which includes program instructions for execution of the first workflow.
12. The computing system according to claim 8 , wherein the circuitry is further configured to:
control the display device to display a setting of the colorization node on the GUI of the image/video editing application,
wherein the setting includes a set of options corresponding to a set of neural network-based colorization models;
receive a second user input comprising a selection of a first option of the set of options; and
select the neural network-based colorization model from among the set of neural network-based colorization models, based on the second user input.
13. The computing system according to claim 8 , wherein the neural network-based colorization model transfers the color effect on the ROI of the reference color image to at least the first object in each of the one or more grayscale images of the first image feed, to output the second image feed comprising the one or more colorized images.
14. The computing system according to claim 8 , wherein the circuitry is further configured to control the display device to display the second image feed on the GUI of the image/video editing application.
15. A non-transitory computer-readable medium having stored thereon, computer-executable instructions which, when executed a computing system, causes the computing system to execute operations, the operations comprising:
obtaining a reference color image by selectively applying a color effect on a region of interest (ROI) of an input image;
controlling a display device to display a first node graph on a Graphical User Interface (GUI) of an image/video editing application, wherein
the first node graph comprises a colorization node representing a first workflow for colorization of at least a first object in one or more grayscale images of a first image feed;
selecting the obtained reference color image based on a first user input; and
executing the first workflow associated with the colorization node, the executing comprising:
feeding the selected reference color image and the first image feed as an input to a neural network-based colorization model; and
receiving, as an output of the neural network-based colorization model for the input, a second image feed comprising one or more colorized images, each of which comprises at least the first object colorized based on color effect on the ROI.
16. The non-transitory computer-readable medium according to claim 15 , wherein the operations further comprise controlling the display device to display a second node graph on the GUI of the image/video editing application, and
wherein the second node graph represents a second workflow for obtaining the reference color image from the input image.
17. The non-transitory computer-readable medium according to claim 16 , wherein the operations further comprise executing the second workflow, the executing comprising:
selecting the ROI from the input image;
applying a first set of image filters on the selected ROI; and
based on the application of the first set of image filters, applying the color effect on the selected ROI of the input image to obtain the reference color image.
18. The non-transitory computer-readable medium according to claim 15 , wherein the colorization node corresponds to a software plugin which includes program instructions for execution of the first workflow.
19. The non-transitory computer-readable medium according to claim 15 , wherein the operations further comprise:
controlling the display device to display a setting of the colorization node on the GUI of the image/video editing application,
wherein the setting includes a set of options corresponding to a set of neural network-based colorization models;
receiving a second user input comprising a selection of a first option of the set of options; and
selecting the neural network-based colorization model from among the set of neural network-based colorization models, based on the second user input.
20. The non-transitory computer-readable medium according to claim 15 , wherein the neural network-based colorization model transfers the color effect on the ROI of the reference color image to at least the first object in each of the one or more grayscale images of the first image feed, to output the second image feed comprising the one or more colorized images.