Using machine learning to selectively overlay image content

A method performed by a computer system to modify a style of an image so the style subsequently corresponds to a different style, said method comprising:

• accessing a first image generated by a first camera that generates images having a first style such that the first image is of the first style, wherein the first camera is one of a low light camera or a visible light camera, and wherein the first style is one of a low light style or a visible light style;
• accessing a second image generated by a second camera that generates images having a second style such that the second image is of the second style, wherein the second camera is a thermal imaging camera, and wherein the second style is a thermal data style;
• subsequent to a deep neural network (DNN) learning the first style and the second style, feeding a copy of the first image as input to the DNN;
• causing the DNN to modify the first image copy by transitioning the first image copy from being of the first style to subsequently being of the second style such that a modified style of the transitioned first image copy bilaterally matches the second style;
• and
• displaying one or more portions of the first image or the transitioned first image copy on a display.

A method performed by a computer system to modify a style of an image so the style subsequently corresponds to a different style, said method comprising:

• accessing a first image generated by a first camera that generates images having a first style such that the first image is of the first style, wherein the first camera is one of a low light camera or a visible light camera, and wherein the first style is one of a low light style or a visible light style;
• accessing a second image generated by a second camera that generates images having a second style such that the second image is of the second style, wherein the second camera is a thermal imaging camera, and wherein the second style is a thermal data style;
• subsequent to a deep neural network (DNN) learning the first style and the second style, feeding a copy of the first image as input to the DNN;
• causing the DNN to modify the first image copy by transitioning the first image copy from being of the first style to subsequently being of the second style such that a modified style of the transitioned first image copy bilaterally matches the second style;
• overlaying selected portions of the transitioned first image copy onto the first image to generate a composite image;
• and
• displaying the composite image.