A system can receive downhole acquisition data relating to a wellbore. The system can pre-process the downhole acquisition data. The system can generate an incomplete borehole image using the downhole acquisition data. The system can determine a sparse representation based on the incomplete borehole image by performing an optimization with respect to the incomplete borehole image. The system can generate a complete borehole image based on an inverse of the sparse representation.

An image processing method to provide a final panoramic image of at least a portion of a head of a patient, wherein a plurality of different provisional panoramic images are calculated from captured frame data sets through the variation of a reconstruction parameter; the provisional panoramic images are scanned for recognizable structures; the imaging quality of the recognizable structures is determined; the variation of the at least one reconstruction parameter for the calculation of different provisional panoramic images of those frame data sets which have recognizable structures with the highest imaging quality is determined; and with reference to the determined variation of the reconstruction parameter of step a final panoramic image is calculated. A computer-readable storage medium comprising instructions which cause a computer to perform the method and an imaging system having such a storage medium are also described.

Disclosed is a distortion rectification method, comprising: taking a wide-angle photograph using a camera of a terminal; determining distortion regions and non-distortion regions in the wide-angle photograph; obtaining a target distortion region selected by a user; dividing the target distortion region into M grid regions of a first pre-set size, wherein M is an integer greater than or equal to one; and respectively performing distortion rectification on the M grid regions of the first pre-set size. Also disclosed is a terminal.

In one embodiment, the system may determine an estimated distance of an eye of a user to a display plane of a display. The system may access, from a memory storage, a number of transmission maps characterizing non-uniform transmission characters of the display as measured from a number of pre-determined view positions within a measurement plane. The measurement plane may be separated from the display plane by a known distance. The system may generate a custom transmission map for the estimated distance of the eye based on the transmission maps using light field rendering. The system may determine a custom correction map based on the custom transmission map. The system may adjust an image to be displayed on the display using the custom correction map. The system may display the image adjusted using the custom correction map on the display.

Described herein are systems and methods of converting media dimensions. A device may identify a set of frames from a video in a first orientation as belonging to a scene. The device may receive a selected coordinate on a frame of the set of frames for the scene. The device may identify a first region within the frame including a first feature corresponding to the selected coordinate and a second region within the frame including a second feature. The device may generate a first score for the first feature and a second score for the second feature. The first score may be greater than the second score based on the first feature corresponding to the selected coordinate. The device may crop the frame to include the first region and the second region within a predetermined display area comprising a subset of regions of the frame in a second orientation.

The present disclosure relates to systems, non-transitory computer-readable media, and methods that implement a neural network framework for interactive multi-round image generation from natural language inputs. Specifically, the disclosed systems provide an intelligent framework (i.e., a text-based interactive image generation model) that facilitates a multi-round image generation and editing workflow that comports with arbitrary input text and synchronous interaction. In particular embodiments, the disclosed systems utilize natural language feedback for conditioning a generative neural network that performs text-to-image generation and text-guided image modification. For example, the disclosed systems utilize a trained model to inject textual features from natural language feedback into a unified joint embedding space for generating text-informed style vectors. In turn, the disclosed systems can generate an image with semantically meaningful features that map to the natural language feedback. Moreover, the disclosed systems can persist these semantically meaningful features throughout a refinement process and across generated images.

Aspects described herein provide a computer-implemented method and system for generating topographic map data at different scales. More specifically, the topographic map data is reduced from large scale to small scale, wherein the scale of the vector features is reduced according to their geometry, feature type and attributes. In order to quickly and easily output digital maps at different scales so that a user may quickly zoom in and out of a map, different zoom levels are produced for different scales, each zoom level containing a variable amount of detail according to its scale, with larger scale zoom levels generally containing more detail than small scale zoom levels. Each zoom level is made up of one or more vector tiles representative of a geographic area, wherein the vector tiles may contain one or more vector features that are representative of objects within that geographic area, and other information related to that geographical area.

An example computing system is configured to extract gridline information from a two-dimensional drawing file and determine, for the gridline information, first coordinate information that is based on a first datum. The computing system converts the first coordinate information into second coordinate information that is based on a second datum, where the second coordinate information is used by a three-dimensional drawing file. The computing system is also configured to receive a request to generate a two-dimensional view of the three-dimensional drawing file, where the two-dimensional view includes an intersection of two meshes within the three-dimensional drawing file. The computing device generates the two-dimensional view of the three-dimensional drawing file and adds, to the generated two-dimensional view, (i) at least one gridline corresponding to the gridline information and (ii) dimensioning information involving the at least one gridline and at least one of the two meshes.

In one implementation, a method includes: displaying a UI element as an overlay in a UI associated with a first FOV, wherein the first FOV is characterized by a first viewing vector of a physical environment; detecting a change from the first FOV to a second FOV, wherein the second FOV is characterized by a second viewing vector of the physical environment; and in response to detecting the change from the first FOV to the second FOV, determining a prominence-display value for the UI element; if the prominence-display value for the UI element exceeds a prominence threshold, displaying the UI element as the overlay in the UI associated with the second FOV; and if the prominence-display value for the UI element does not exceed the prominence threshold, ceasing display of the UI element in the UI associated with the second FOV.

Methods, systems, and articles of manufacture to improve image recognition searching are disclosed. In some embodiments, a first document image of a known object is used to generate one or more other document images of the same object by applying one or more techniques for synthetically generating images. The synthetically generated images correspond to different variations in conditions under which a potential query image might be captured. Extracted features from an initial image of a known object and features extracted from the one or more synthetically generated images are stored, along with their locations, as part of a common model of the known object. In other embodiments, image recognition search effectiveness is improved by transforming the location of features of multiple images of a same known object into a common coordinate system. This can enhance the accuracy of certain aspects of existing image search/recognition techniques including, for example, geometric verification.