1576results about "Filling planer surface with attributes" patented technology

The invention discloses a multi-modal semantic and physical law driven remote sensing image generation method, belongs to the technical field of computer vision and remote sensing image generation, and aims to solve the problems of insufficient cross-modal semantic alignment, low reliability of a generation result and insufficient physical mechanism fusion. The four-stage method comprises the following steps: firstly, rejecting low-quality samples from original data and unifying a spatial scale; then, extracting a multi-modal semantic vector by adopting a BLIP model and a CLIP model, and introducing a remote sensing physical rule to carry out vector optimization; then position coding and physical constraint conditions are embedded in the submerged space, and multi-source information joint modeling is achieved through a cross-modal encoder; and finally, by taking text description, physical priori knowledge and diffusion time steps as joint conditions, performing de-noising reasoning based on a Transform architecture, and completing back diffusion reconstruction by means of a trans-attention mechanism. According to the method, physical rationality and semantic consistency are improved, and a more reliable technical normal form is provided for remote sensing image generation in the fields of disaster monitoring, military simulation and the like.

The invention relates to the technical field of image processing, in particular to a glioma area marking method and system for a neuromedical image, and the method comprises the following steps: obtaining a brain nerve image, segmenting a left brain area and a right brain area, carrying out the gray correction, extracting a contour boundary, carrying out the calibration, repairing a broken contour, dividing grids, and recognizing a texture extension path. And matching the transparency level and performing visual rendering to obtain a visual marking result of the glioma region. According to the invention, gray correction is carried out through the symmetry of the brain, the accuracy and the anti-interference capability of boundary point identification are improved by combining a boundary screening mode driven by gray difference, an angle change continuity detection mechanism is adopted, the integrity and the path stability of a curvature structure are enhanced, and a rasterized texture path extraction mode is adopted. And realizing continuous expression of cross-regional texture features, and optimizing a visual hierarchy and detail comparison effect of the marked region in combination with a transparency setting scheme of gray offset matching.

Artificial intelligence-based systems and methods are described for providing personalized skin product recommendations. Natural language data of a user is received using a conversation engine, such as a generative pretrained transformer AI model. The natural language data is input into a synthetic image generation model for generating a digital twin image depicting skin condition(s). A product recommendation model inputs the digital twin image and / or phenotype and / or demographic classifications of the user, and outputs a skin care product recommendation for the user. An image simulation model inputs the product recommendation, the digital twin image and phenotype and / or demographic classifications of the user to output a simulated image of the user having one or more graphical enhancements. The simulated image may be displayed to the user on display screen along with natural language data describing the simulated image as depicted skin as predicted to appear following treatment with the skin care product.

The pattern generation method based on diffusion model fine tuning comprises the following steps: constructing a data set; the generation model comprises an edge detection model ControlNet and a stable diffusion model, the stable diffusion model comprises a text encoder CLIP, a diffusion model U-Net and an image decoder VAE, the CLIP text encoder converts an input natural language into word vector features and inputs the word vector features into a U-Net network in a submerged space, and the diffusion model U-Net and the image decoder VAE are connected with the edge detection model ControlNet and the diffusion model U-Net; the U-Net network is controlled to carry out iterative denoising on pure noise in a low dimension to generate a compressed image, and finally the compressed image is restored to an original pixel image through a decoder VAE, so that text content control image generation is realized; carrying out fine tuning training on the generative model by adopting a LoRA parameter efficient fine tuning technology; and intelligently generating a batik style pattern. The method has the advantages that the texture precision of the generated image can be improved, and the personalized style image can be generated.

This document relates to providing adaptive teleconferencing experiences using generative image models. For example, the disclosed implementations can employ inpainting and / or image-to-image restyling modes of a generative image model to generate images for a teleconference. The images can be generated based on prompts relating to the teleconference. Users can be superimposed on the generated images, thus giving the appearance that the users are present in an environment generated by the generative image model.

The invention discloses a structured data self-learning method based on a graph neural network, and the method comprises the following steps: S1, analyzing structured data, extracting entity fields and relation fields, and constructing a structure candidate graph; s2, generating a node embedding feature matrix, and initializing and recording the adjacency relation of candidate edges; s3, constructing a graph neural network model, inputting node features and an adjacent matrix, and defining a task loss function; s4, evaluating the gradient contribution degree of edge connection by adopting a gradient sensitive sparse adjacency self-learning algorithm, and updating the graph structure representation; s5, introducing an embedded interpretability gradient backtracking mechanism, correcting an edge connection relation and enhancing interpretability; s6, training the graph neural network by using the corrected structure, and updating the node embedding and graph structure; and S7, outputting a final graph structure and an interpretability index, and generating a graph modeling visualization result. According to the method, efficient modeling and explanatory analysis of structured data are realized through a dynamic graph structure learning and gradient backtracking mechanism.

An image processing method, performed by a computer device, comprising: extracting sketch texture features at multiple scales from a sketch image; extracting image noise features at multiple scales from preset noise; determining color guide information corresponding to the sketch image; encoding, for each scale, a noise feature based on a sketch texture feature and the color guide information to obtain multi-scale image features; and performing multi-scale decoding on these image features to obtain a colored image comprising a sketch texture corresponding to the sketch image and a color based on the color guide information. A related training method and apparatus are also provided to develop models for this image processing technique.

The invention discloses a deep learning-based cold resistance evaluation system for medicago sativa L., and the system comprises a data generation module which is used for generating a phenotypic image and corresponding physiological data of medicago sativa L. under low-temperature stress through a diffusion model embedded with plant low-temperature response physical constraints; the evaluation model module is used for extracting cold resistance characteristics from the image and physiological data by adopting a causal-driven dual-channel adaptive network; and the decision module comprises a hierarchical model distillation unit and a federal reinforcement learning unit, and the hierarchical model distillation unit and the federal reinforcement learning unit realize joint training of model compression and decision strategy optimization through an edge-cloud collaborative architecture, output a cold-resistant decision and realize visualization through an augmented reality interface. The method can effectively solve the core problems of traditional medicago sativa cold resistance assessment in the aspects of data generation, model generalization, decision-making efficiency and the like.

The invention discloses a multi-platform-oriented intelligent interface adaptation and rendering optimization method and system, and belongs to the technical field of interface rendering. The method comprises the following steps: firstly, acquiring and analyzing interface description information, and extracting hierarchical structures and constraint relationships of interface elements to obtain abstract description features; performing adaptive layout mapping based on the environment characteristic parameters of the target platform, and dynamically adjusting space occupation and display priorities under the constraint of keeping the relative position relationship of interface elements unchanged to obtain a layout scheme after platform adaptation; determining resource consumption nodes according to interface element distribution characteristics, and determining a layered rendering strategy by analyzing visibility states and updating frequency characteristics; applying the layout scheme and the rendering strategy to a rendering execution process to generate output; and collecting performance feedback data to adaptively update a space occupation and rendering strategy. According to the method and the device, automatic adaptation and rendering performance optimization of the cross-platform interface are realized, and the multi-platform interface rendering efficiency and the user experience are improved.

The invention discloses a remote sensing image semantic segmentation prediction method and system based on a vision-language pre-training model. The method comprises the following steps: acquiring a source domain image with a label and a target domain image without a label; adding a pseudo tag to the target domain image without the tag by using a teacher network; performing style conversion on the labeled source domain image to obtain a style migration image with a target domain image visual style; extracting text embedding features of the labeled source domain image by using a pre-trained vision-language pre-training model to obtain text embedding features of a semantic category; fusing the tagged source domain image, the style migration image and the text embedding features of the semantic category to generate an intermediate domain fusion image containing double-domain information and language priori knowledge; performing random mask processing on the intermediate domain fusion image; and inputting the multi-scale context features and the text embedding features of the student network extraction mask image into a vision-language decoder, and then carrying out semantic segmentation on a prediction result.

The invention relates to the field of intelligent city planning, and discloses a street space quality intelligent evaluation and image generation method and system based on deep learning, and the method specifically comprises the following steps: movably collecting a street space image, and recording the geographic position information; performing perspective correction and multi-view image segmentation on the acquired street image data, and performing spatial matching with geographical location information to obtain a fused image database; and performing semantic segmentation on the image in the fused image database based on a deep learning model, calculating objective and subjective visual perception indexes and facility function indexes of the image, and generating a street space quality evaluation result. The method solves the problems that in the prior art, evaluation dimensions are limited, and an automatic response generation mechanism is lacked, and has the advantages of being intelligent, efficient and comprehensive in subjective and objective evaluation.

A method of generating digital piping data from a paper isometric image. The method includes receiving a 2-Dimensional (2D) isometric image corresponding to a piping structure. The 2D isometric image comprises one or more piping components corresponding to the piping structure. The method also includes identifying at least one a direction, an orientation, a name, and dimensions of each of the piping components in a 3D space. The method further includes identifying 3D coordinate information corresponding to a start point and an end point of each of the piping components. Furthermore, the method includes generating 3D geometry configuration data corresponding to each of the piping components based on the corresponding identified 3D coordinate information, and the corresponding at least one of the direction, an orientation, and a dimension in a predefined standard format.

The unmanned intelligent concrete vibrating system comprises the steps that a to-be-poured bin surface is subjected to high-angle shooting through a camera, a vibrating forbidding area is obtained through marking according to a high-angle shot picture, and meanwhile coordinates and elevation information of all points of the bin surface are obtained through the surveying and mapping function of a space positioning system; the computer system is used for planning a vibrating operation route according to the high-angle image and coordinates and elevation information of all points of the bin surface obtained through the surveying and mapping function of the space positioning system; and the unmanned aerial vehicle is used for carrying a vibrating rod to conduct vibrating according to the vibrating operation route, and whether vibrating is completed or not is judged according to the actual situation of concrete. The advantages that the unmanned aerial vehicle flies stably and is easy to control and has certain loading capacity can be fully utilized, the functions of vibration route design, intelligent vibration end point judgment and the like are combined, the unmanned aerial vehicle carries the vibration system to conduct vibration operation, traditional manual operation is replaced, and the vibration quality and efficiency of concrete are improved.

The technology introduces 3D Moments, a new computational photography effect. As input a pair of near-duplicate photos is taken (FIG. 1A), i.e., photos of moving subjects from similar viewpoints, which may be very common in people's photo collections. As output, the system produces a video that smoothly interpolates the scene motion from the first photo to the second, while also producing camera motion with parallax that gives a heightened sense of 3D (FIG. 1B). To achieve this effect, the scene is represented as a pair of feature-based layered depth images augmented with scene flow (306). This representation enables motion interpolation along with independent control of the camera viewpoint. The system produces photorealistic space-time videos with motion parallax and scene dynamics (322), while plausibly recovering regions occluded in the original views. Experimentation demonstrating superior performance over baselines on public benchmarks and in-the-wild photos.

Techniques are described for using data capture devices at a building to automatically generate a building floor plan and to determine associated absolute location data for the generated floor plan, such as by associating separately captured GPS data or other absolute location data with the floor plan. In some situations, a building floor plan is automatically generated by analyzing visual data of images captured at multiple image acquisition locations by a camera device to determine room shapes of surrounding rooms, and GPS absolute location data is associated with the generated floor plan using additional data captured at other data capture locations at the building by a separate mobile device that moves independently from the camera device, such as by extending the absolute location data from the mobile device to the camera device's image acquisition location and its surrounding room shape.

The invention discloses an AI exhibition hall control method and system based on crowd thermal distribution monitoring, and the method comprises the steps: obtaining crowd density distribution data, behavior data and environment data through constructing a full-coverage sensing network, employing a thermal imaging camera, a WiFi probe and an infrared sensor, and generating a thermal distribution diagram; through converting discrete density point fusion and labeling into a data set of a continuous thermal field, crowd distribution characteristics are visually displayed, spatial-temporal correlation of crowd flow is effectively modeled by combining a convolutional neural network and a spatial-temporal diagram neural network, a prediction-adjustment-verification closed loop is realized based on a prediction result 6-8 minutes ahead of time, and the prediction efficiency is improved. The control strategy is dynamically adjusted according to the predicted crowd distribution trend and the business target, the guide route or the interaction form can be dynamically adjusted according to the crowd density, the exhibit layout can be adjusted in advance, the number of tourists going back and forth is reduced, the overall flow efficiency is improved, and therefore the display effect of the AI exhibition hall is improved.

The invention discloses an AI diffusion model pattern generation platform and method, the generation platform comprises a visual interaction module, an image generation module and a pattern mapping module, and the image generation module comprises a training sub-module and a reasoning sub-module; the generation method comprises the following steps: preprocessing a text input by a user and an optional structure image, and outputting standardized data; a semantic embedding vector is generated through text coding; carrying out LoRA fine tuning to obtain a style weight module; a ControlNet structure condition is injected; performing diffusion sampling to generate candidate patterns; performing CLIP scoring to screen an optimal pattern; and outputting the optimal pattern and previewing the carrier map. According to the platform and the method provided by the invention, the LoRA low-rank fine tuning, the ControlNet structure condition control and the CLIP similarity evaluation algorithm are fused, so that the effects of customizing the special style pattern with a small number of samples at low cost and accurately controlling the structure and style of the pattern are realized.

The embodiment of the invention provides a document processing method and device, equipment and a medium, and relates to the technical field of data processing.The method comprises the steps that a to-be-processed document is converted into a single-page atlas on the basis of the reading sequence of the to-be-processed document, layout analysis is conducted on the single-page atlas, the single-page atlas is split into a single-bar graph sequence, and the single-bar graph sequence is stored in the single-page atlas sequence; and sequentially extracting single-column pages in the single-column graph sequence according to the reading sequence, and carrying out target detection on the corresponding single-column pages according to a preset scanning sequence so as to determine page elements in the single-column pages based on a detection result. And performing target identification on the page element to determine position information of the page element in the corresponding single-column page, and converting the page element into a page object in a target format based on an identification result. The page objects are re-typeset based on the reading sequence, the scanning sequence and the position information and assembled into the document result in the target format, so that the reliability of document processing is improved.

The present disclosure generally describe user interfaces related to time. In accordance with embodiments, user interfaces for displaying and enabling an adjustment of a displayed time zone are described. In accordance with embodiments, user interfaces for initiating a measurement of time are described. In accordance with embodiments, user interfaces for enabling and displaying a user interface using a character are described. In accordance with embodiments, user interfaces for enabling and displaying a user interface that includes an indication of a current time are described. In accordance with embodiments, user interfaces for enabling configuration of a background for a user interface are described. In accordance with embodiments, user interfaces for enabling configuration of displayed applications on a user interface are described.

The invention relates to the technical field of packaging image processing, and provides a customizable cultural and creative packaging design system based on AIGC, and the system comprises the following modules: a data input module which is used for receiving cultural and creative themes, cultural element preferences and packaging specification parameters inputted by a user; the culture element database is used for storing multi-dimensional culture symbol data including patterns, color pedigree, historical allusions and semantic association rules; and the AIGC generation engine is used for extracting features from the culture element database according to the input parameters based on a generative adversarial network (GAN) and a Transform model, and generating an initial design draft. 10 versions of high-quality design schemes can be generated within 5 minutes through an AIGC engine, the speed is increased by 8 times compared with a traditional process, meanwhile, the modification feedback period is shortened to 2 hours through AR real-time preview, the user satisfaction degree reaches 94%, the pattern semantic matching accuracy is improved to 89%, the historical allusion misuse rate is reduced to 3% or below, and the design efficiency is improved. And the material waste rate of the automatically generated printing file is reduced to 12%, and the delivery cycle is shortened by 40%.

The invention discloses a Lake and Hunan wood carving image generation method, device and equipment based on a LoRA model and a storage medium, and relates to the technical field of process digitization and image generation, and the method comprises the steps: constructing a Lake and Hunan wood carving manufacturing process feature library based on a material object scanning graph, wood texture data and a manufacturing process video of the Lake and Hunan wood carving; according to the feature library, performing hierarchical training on the initial LoRA model according to a texture layer-cutter layer-pattern layer hierarchical logic to obtain a hierarchical LoRA model, and performing hierarchical fusion on the hierarchical LoRA model and a potential diffusion model to form a lake and Hunan woodcarving image generation model; and analyzing text cue words input by a user by using a keyword system in the feature library, extracting wood carving types, timber texture parameters, folk pattern requirements and scene adaptation features, and inputting the features into the lake and Hunan wood carving image generation model to obtain a target lake and Hunan wood carving image. According to the method, the lake and Hunan woodcarving image with the process reduction degree and the scene adaptability can be generated.

The invention discloses a personalized customized vi design method and system, and relates to the technical field of visual identification design, the design method comprises the following specific steps: S100, data acquisition: docking with an enterprise internal management system to obtain core data, using a web crawler tool to collect Internet related information, and using the web crawler tool to store the core data; according to the method, data in multiple aspects of industry attributes, brand positioning and color preference of target audiences of an enterprise are deeply analyzed by utilizing an artificial intelligence technology, highly intelligent color analysis and recommendation are realized, and the color matching degree of the industry, the color preference of the target audiences and multiple dimensions of color coordination correction factors are comprehensively considered. According to the method, the color scheme meeting the enterprise image and the market demand can be accurately recommended to the user, the intelligent color recommendation not only improves the design efficiency, but also ensures that the color scheme is highly matched with the enterprise positioning and audience preference, and the visual impact and brand recognition degree of the design are enhanced.

The present disclosure relates to systems, methods, and non-transitory computer-readable media that detects shadows, removes shadows, and synthesizes shadows in a joint-framework. In particular, the disclosed systems access an object mask of an object and a digital image depicting the object and a shadow of the object. Furthermore, the disclosed systems perform object-centered shadow detection and removal to generate a modified digital image without the shadow by utilizing a shadow analyzer model. Moreover, the disclosed systems receive a user interaction to manipulate an object and generate a modified shadow utilizing a shadow synthesis model where the shadow synthesis model is conditioned on a shadow mask generated by the shadow analyzer model.

The embodiment of the invention relates to an image generation method and device, equipment and a medium, and the method comprises the steps: obtaining a first image set, the first image set comprises at least one frame of first image, and the at least one frame of first image comprises a color filling image containing a target role, and / or a line image containing the target role; a second image set is obtained, and the second image set comprises multiple frames of second images corresponding to the multiple three-dimensional angles of the target role; a first animation generation request is sent to a target animation generation model, the first animation generation request carries a first image set and a second image set, and the target animation generation model learns in advance to generate multiple video frames according to the input image set in response to the animation generation request; multiple video frames output by the target animation generation model are obtained, and the multiple video frames comprise multi-angle color filling images of the target role. According to the technical scheme, the animation generation efficiency is improved.

The invention provides a gait identity information desensitization method and system based on sparse contour hopping. The method comprises the steps that S1, a gait video is deframed into an image sequence, and binarization processing is conducted on the image sequence; s2, extracting identity features in the binary image sequence by using a gait recognition model, and calculating an adversarial disturbance matrix of each image according to a loss function; s3, binary image sequence key frames are selected at equal intervals, and adversarial disturbance meeting the pixel jump constraint is added to the human body contour edge in the key frames; s4, embedding the finally added disturbance value into the binary image sequence to obtain a reversible human body contour image sequence; and S5, pixel color backfilling is carried out on the modified binary image sequence, and a desensitized gait video is obtained. According to the method, the loss function of the image sequence before and after desensitization is maximized by means of the gait recognition model, so that the pixel directly generates binary hopping towards the gradient rising direction, non-directional or directional interference on the gait recognition result is realized, and the identity information privacy is protected.

The invention discloses a virtual staining method and system for a pathological section image, and belongs to the technical field of image processing, and the method comprises the steps: constructing a registration data pair for different staining styles through real staining as training data, meanwhile, a virtual dyeing lookup table model comprising a self-adaptive feature encoder, a self-adaptive weight predictor and a basic virtual dyeing lookup table is constructed, and in the model, a feature map and a weight are generated in a self-adaptive mode based on an input original image; the basic virtual dyeing lookup tables are weighted based on the weights to construct the virtual dyeing lookup table for adaptive fusion of the original image, and then the virtual dyeing lookup table is utilized to perform virtual color dyeing of various chemical dyeing styles, so that the dyeing efficiency in the process is high, the dyeing styles can be diversified, and the image quality is improved. The positions and forms of the pixels are not changed, only color values are changed, dyeing is achieved, the dyeing self-adaption is high, the dyeing quality is guaranteed, and the dyeing area has interpretability.

The invention discloses a privacy protection type video fuzzy processing method and device. The method comprises the following steps: S1, detecting a privacy area and a type in real time; s2, predicting a motion track of the privacy area; s3, dynamically adjusting the fuzzy strategy; s4, processing the privacy area; s5, fusing and outputting the protected video; according to the invention, through the multi-mode privacy identification model and optical flow trajectory prediction, the privacy information of the moving target is continuously and accurately positioned, and in combination with sensitivity evaluation, the privacy protection intensity and the video information integrity are balanced under the change of a complex scene; an adaptive fuzzy algorithm is adopted, contour natural transition is reserved, key feature points are only tracked in a privacy area, a fuzzy area is automatically expanded for an emergent high-speed target, and the response requirement of a real-time monitoring scene is met; through a metadata embedding technology, full-link auditing of a privacy processing process is supported, and a sensitive scene threshold value and a boundary extension pixel value enable the system to be flexibly adaptive to different security and protection grade scenes.

This disclosure describes one or more implementations of systems, non-transitory computer-readable media, and methods that utilizes a segmentation approach that distinguishes between smooth-shaded regions from high-frequency regions in an image within a vectorization pipeline to generate a vector image. For instance, the disclosed systems utilize a smoothing function to identify non-overlapping sets of pixels that include locally smooth pixels and pixels with high frequency details for an image. Furthermore, in some instances, the disclosed systems generate separate sets of fill functions (representing color-based regions) using color-based pixel clustering for the non-overlapping sets of pixels. Moreover, in one or more instances, the disclosed systems merge neighboring color-based regions in the sets of fill functions (using color similarity) to generate a set of segmented regions for an image. In some implementations, the disclosed systems utilize the set of segmented regions, from the image, to generate a vector image from the image.

The embodiment of the invention discloses a picture drawing method and device, equipment and a storage medium. The picture drawing method comprises the steps that multiple original pictures uploaded by a user are acquired; the original picture is converted into a to-be-displayed picture to be added in a canvas, the size of the to-be-displayed picture is equal to the to-be-displayed size of the original picture in a viewport, and the viewport comprises an area, displayed in a display screen, in the canvas; a texture image set is created, the texture image set is used for storing the texture of each to-be-displayed picture displayed in the viewport, and the size of the texture image set is determined according to the size of each to-be-displayed picture in the viewport and the position coordinates of the to-be-displayed pictures; drawing the to-be-displayed picture into the texture image set; and drawing the texture atlas into a canvas area in the viewport. According to the technical means, the technical problem that in the related technology, when a user uploads a plurality of pictures in a collaborative drawing board, the collaborative drawing board renders each picture, generated system memory resource occupation is too high is solved.

The invention provides a text description generation method and device and electronic equipment, and the method comprises the steps: obtaining a plurality of first visual angle images shot by a target vehicle; synthesizing a third view angle image containing the target vehicle based on the plurality of first view angle images; wherein the third view angle image comprises a complete part of the target vehicle under a specified view angle; inputting the third visual angle image into a pre-trained description generation model, and outputting a text description corresponding to the target vehicle; wherein the description generation model is trained by using a sample image in advance, and the sample image is a third visual angle image of the specified vehicle; the textual description includes a behavioral description and / or an environmental description of the target vehicle. In the mode, the plurality of first view angle images are synthesized to obtain the third view angle image, and the third view angle image is compatible with the pre-trained model, so that the accuracy of the generated text description is improved.