A method including receiving a spatial query on spatial data. The spatial query has a spatial query extent including a sub-portion of the spatial data. A projection type is selected for the spatial query. A framebuffer is created for the selected projection type. Vertex buffers are established to hold a geometry of the selected projection type. The vertex buffers are passed from a CPU to a GPU. A spatial geometry of the spatial query extent is rendered into the framebuffer by projecting feature vertex data for features that fall at least partly within the spatial query extent into the vertex buffers. Rendering generates rendered framebuffer pixel values. Pixel values of the rendered framebuffer are retrieved as bytes on the CPU. A spatial query result is processed that includes or uses the pixel values.

A method including receiving a spatial query on spatial data. The spatial query has a spatial query extent including a sub-portion of the spatial data. A projection type is selected for the spatial query. A framebuffer is created for the selected projection type. Vertex buffers are established to hold a geometry of the selected projection type. The vertex buffers are passed from a CPU to a GPU. A spatial geometry of the spatial query extent is rendered into the framebuffer by projecting feature vertex data for features that fall at least partly within the spatial query extent into the vertex buffers. Rendering generates rendered framebuffer pixel values. Pixel values of the rendered framebuffer are retrieved as bytes on the CPU. A spatial query result is processed that includes or uses the pixel values.

Various methods and systems are provided for computed tomography imaging. In one embodiment, a method includes acquiring, with an x-ray detector and an x-ray source coupled to a gantry, a three-dimensional image volume of a subject while the subject moves through a bore of the gantry and the gantry rotates the x-ray detector and the x-ray source around the subject, inputting the three-dimensional image volume to a trained deep neural network to generate a corrected three-dimensional image volume with a reduction in aliasing artifacts present in the three-dimensional image volume, and outputting the corrected three-dimensional image volume. In this way, aliasing artifacts caused by sub-sampling may be removed from computed tomography images while preserving details, texture, and sharpness in the computed tomography images.

Disclosed herein are an apparatus and method for classifying clothing attributes based on deep learning. The apparatus includes memory for storing at least one program and a processor for executing the program, wherein the program includes a first classification unit for outputting a first classification result for one or more attributes of clothing worn by a person included in an input image, a mask generation unit for outputting a mask tensor in which multiple mask layers respectively corresponding to principal part regions obtained by segmenting a body of the person included in the input image are stacked, a second classification unit for outputting a second classification result for the one or more attributes of the clothing by applying the mask tensor, and a final classification unit for determining and outputting a final classification result for the input image based on the first classification result and the second classification result.

The present invention provides a data processing method and an electronic terminal. The electronic terminal obtains target data that includes at least one data item, converts the target data into a data image by using a data visualization technology, and then sets the data image as wallpaper, where the data image includes at least one graphic element, and the graphic element is in a one-to-one correspondence with the data item. The target data is user data, and may include operation event information of operating the electronic terminal by a user, or information that is associated with a user account and that is based on at least one network platform, so as to automatically generate the wallpaper, show the user data to the user by using the wallpaper, and improve user experience.

The present invention provides a data processing method and an electronic terminal. The electronic terminal obtains target data that includes at least one data item, converts the target data into a data image by using a data visualization technology, and then sets the data image as wallpaper, where the data image includes at least one graphic element, and the graphic element is in a one-to-one correspondence with the data item. The target data is user data, and may include operation event information of operating the electronic terminal by a user, or information that is associated with a user account and that is based on at least one network platform, so as to automatically generate the wallpaper, show the user data to the user by using the wallpaper, and improve user experience.

Methods of encoding and decoding video data are provided. In an encoding method, source video data comprising one or more source views is encoded into a video bitstream. Depth data of at least one of the source views is nonlinearly filtered and downsampled prior to encoding. After decoding, the decoded depth data is up-sampled and nonlinearly filtered.

This application discloses a for displaying a two-dimensional figure of a virtual object performed by a computer device. The method includes: rendering a two-dimensional image of a virtual object based on a corresponding three-dimensional figure model according to a plurality of preset parameters; displaying a target interface comprising the two-dimensional image of the virtual object; and displaying an updated two-dimensional image of the virtual object when an update condition is met, wherein the updated two-dimensional image corresponds to the three-dimensional figure model of the virtual object.

Method for compressing a sequence of images comprising a first image and a second image, the method comprising the steps of: generating a first descriptor comprising parameters for displaying a computer-generated graphical element in the first image, the graphical element being of non-photographic origin, and the display parameters not comprising pixel values; processing the second image so as to determine an event which gave rise to a potential variation in the parameters for displaying the graphical element between the first image and the second image; generating a second descriptor comprising an event code indicating the determined event.

Method for compressing a sequence of images comprising a first image and a second image, the method comprising the steps of: generating a first descriptor comprising parameters for displaying a computer-generated graphical element in the first image, the graphical element being of non-photographic origin, and the display parameters not comprising pixel values; processing the second image so as to determine an event which gave rise to a potential variation in the parameters for displaying the graphical element between the first image and the second image; generating a second descriptor comprising an event code indicating the determined event.