A method and system for generating music uses artificial intelligence to analyze existing musical compositions and then creates a musical composition that deviates from the learned styles. Known musical compositions created by humans are presented in digitized form along with a style designator to a computer for analysis, including recognition of musical elements and association of particular styles. A music generator generates a draft musical composition for similar analysis by the computer. The computer ranks such draft musical composition for correlation with known musical elements and known styles. The music generator modifies the draft musical composition using an iterative process until the resulting musical composition is recognizable as music but is distinctive in style.

Systems and methods are described for generating automatic illustrator guides. The method may include generating a plurality of candidate guides for a digital image (e.g., using an automated shape detection engine), where each of the plurality of candidate guides is a simple shape such as a line or a circle, combining at least two of the candidate guides based on the shape information to create refined candidate guides, generating a pixel coverage map for each of the refined candidate guides, prioritizing the refined candidate guides based on the corresponding pixel coverage maps, selecting one or more drawing guides from the one or more refined candidate guides based on the prioritization, and displaying the digital image along with the one or more drawing guides.

Systems and methods are described for generating automatic illustrator guides. The method may include generating a plurality of candidate guides for a digital image (e.g., using an automated shape detection engine), where each of the plurality of candidate guides is a simple shape such as a line or a circle, combining at least two of the candidate guides based on the shape information to create refined candidate guides, generating a pixel coverage map for each of the refined candidate guides, prioritizing the refined candidate guides based on the corresponding pixel coverage maps, selecting one or more drawing guides from the one or more refined candidate guides based on the prioritization, and displaying the digital image along with the one or more drawing guides.

There is provided a method for filling at least one color in one or more outline images at a multi-function device. The method includes providing a user interface for displaying a color fill option. Based on receiving a selection of the color fill option, a file including at least one outline image is received by a controller. The at least one outline image includes at least one image field. Then, it is identified by an image processor, if the at least one image field includes at least one color marking. Based on the identification, the at least one image field is automatically filled by the image processor according to the at least one color marking to generate a color filled image.

There is provided a method for filling at least one color in one or more outline images at a multi-function device. The method includes providing a user interface for displaying a color fill option. Based on receiving a selection of the color fill option, a file including at least one outline image is received by a controller. The at least one outline image includes at least one image field. Then, it is identified by an image processor, if the at least one image field includes at least one color marking. Based on the identification, the at least one image field is automatically filled by the image processor according to the at least one color marking to generate a color filled image.

In some embodiments, a graphics manipulation application accesses, for a received brushstroke input, brushstroke parameters that include a maximum alpha-deposition parameter and a fractional alpha-deposition parameter. The graphics manipulation application computes an alpha flow increment from the maximum alpha-deposition parameter and the fractional alpha-deposition parameter. The graphics manipulation application computes an output canvas color from the alpha flow increment and a current canvas opacity, and obtains an output canvas opacity based on the current canvas opacity and the maximum alpha-deposition parameter. If the current canvas opacity exceeds or equals the maximum alpha-deposition parameter, the current canvas opacity is selected as the output canvas opacity. Otherwise, the graphics manipulation application computes the output canvas opacity by increasing the current canvas opacity based on the alpha flow increment. The graphics manipulation application updates a canvas portion affected by the brushstroke input to include the output canvas opacity and the output canvas color.

In some embodiments, a graphics manipulation application accesses, for a received brushstroke input, brushstroke parameters that include a maximum alpha-deposition parameter and a fractional alpha-deposition parameter. The graphics manipulation application computes an alpha flow increment from the maximum alpha-deposition parameter and the fractional alpha-deposition parameter. The graphics manipulation application computes an output canvas color from the alpha flow increment and a current canvas opacity, and obtains an output canvas opacity based on the current canvas opacity and the maximum alpha-deposition parameter. If the current canvas opacity exceeds or equals the maximum alpha-deposition parameter, the current canvas opacity is selected as the output canvas opacity. Otherwise, the graphics manipulation application computes the output canvas opacity by increasing the current canvas opacity based on the alpha flow increment. The graphics manipulation application updates a canvas portion affected by the brushstroke input to include the output canvas opacity and the output canvas color.

A virtual try-on system includes one or more hardware processors configured to function as a learning unit, an acquisition unit, a deriving unit, and a generation unit. The learning unit learns, by machine learning using three-dimensional data of a try-on person, a learning model using a teacher try-on person image as input data, and using a body shape parameter indicating a body shape of the try-on person represented by the teacher try-on person image and compositing position information of a clothing image in the teacher try-on person image as output data. The acquisition unit acquires a try-on person image. The deriving unit derives output data of the try-on person represented by the try-on person image using the try-on person image and the learning model. The generation unit generates a virtual try-on image by compositing the try-on person image and the clothing image using the derived output data.

A method and system for generating art uses artificial intelligence to analyze existing art forms and then creates art that deviates from the learned styles. Known art created by humans is presented in digitized form along with a style designator to a computer for analysis, including recognition of artistic elements and association of particular styles. A graphics processor generates a draft graphic image for similar analysis by the computer. The computer ranks such draft image for correlation with artistic elements and known styles. The graphics processor modifies the draft image using an iterative process until the resulting image is recognizable as art but is distinctive in style.

A method and system for generating art uses artificial intelligence to analyze existing art forms and then creates art that deviates from the learned styles. Known art created by humans is presented in digitized form along with a style designator to a computer for analysis, including recognition of artistic elements and association of particular styles. A graphics processor generates a draft graphic image for similar analysis by the computer. The computer ranks such draft image for correlation with artistic elements and known styles. The graphics processor modifies the draft image using an iterative process until the resulting image is recognizable as art but is distinctive in style.