244 results about "Model image" patented technology

The invention discloses an image processing method and device, a medium, electronic equipment and a program product. The method comprises the following steps: acquiring an article image comprising a first article and a model image comprising an interaction posture of a model and a second article; superposing the article image to the position of the first limb in the model image to replace the second article in the model image with the first article to obtain a first image; obtaining a first mask picture of the foreground area including the first article and the first limb; and according to the first mask image, performing local redrawing on the first limb in the first image to obtain a second image. Through superposition of the article image and the model image, the first article and the model are fused, and the real consistency of the generated content can be ensured. And according to the first mask image, local redrawing is carried out on the shielding conflict area in the first image, so that the natural interaction feeling of the model and the first article is improved.

The invention relates to the technical field of industrial detection, and provides a real-time monitoring method and device for slag in a boiler. A plurality of high-temperature-resistant cameras are installed around an observation opening in the bottom of a boiler in an annular array mode, the slag accumulation condition in the boiler is collected in real time through the high-temperature-resistant cameras, and a single-view-angle image is obtained; evaluating the visual field states of the high-temperature-resistant cameras according to the single-visual-angle images, and determining a plurality of to-be-modeled images from the plurality of high-temperature-resistant cameras; and generating slag point cloud data by using the at least one to-be-modeled image, and performing three-dimensional reconstruction on the slag point cloud data to obtain the slag pile volume. According to the method, the slag falling condition of the boiler bottom of the power plant boiler is monitored and recognized in real time, and the problems that the slag falling at the boiler bottom cannot be detected in real time depending on manpower, the detection accuracy is insufficient, the three-dimensional form of the slag falling at the boiler bottom cannot be synthesized by detecting the slag falling at the boiler bottom through sensor equipment, and practicability is poor are solved.

The invention relates to the technical field of computer vision and artificial intelligence, in particular to a visual state space model-based neural network optimization method for bridge diseases, which comprises the following steps of: constructing a neural network comprising a feature extraction backbone network and a task adaptation head network, modeling an image feature sequence by the backbone network based on a visual state space model, the task adaptive header network is used for capturing local details and long-distance global dependence and outputting disease categories, confidence coefficients and positions; a standardized data set is used for training a model, and dynamic optimization is completed by evaluating the importance of neurons and sorting and cutting redundant neurons; and preprocessing a to-be-detected image, inputting the preprocessed to-be-detected image into the optimization model, and outputting a precise disease identification result through feature extraction, multi-branch processing and non-maximum suppression. The method improves the disease feature extraction precision, achieves the light weight of the model, adapts to multi-scale disease detection, improves the practicability of an identification result, and is suitable for a bridge disease intelligent detection scene.

To realize a service for easily generating an apparel image.SOLUTION: According to an embodiment of the present invention, an apparel image generating system has: a display unit for displaying a selected screen for which a user can select at least one of a model image, an item image, a background image, a face image and a pose image; and an image generating unit for using an image generation model to generate an apparel image from the image selected by the user.SELECTED DRAWING: Figure 9

Disclosed in the embodiments of the present application are a model rendering method and a related apparatus. The method comprises: for an initial three-dimensional model to be processed, simplifying the model structure of the initial three-dimensional model on the basis of a topological structure feature of the initial three-dimensional model, so as to obtain a simplified three-dimensional model, wherein the number of meshes comprised in the simplified three-dimensional model is less than the number of meshes comprised in the initial three-dimensional model, and the difference between the simplified three-dimensional model and the initial three-dimensional model meets a preset similarity requirement; by means of lighting simulation processing, determining a lighting intensity corresponding to a vertex in the simplified three-dimensional model when the simplified three-dimensional model is in a virtual environment; and on the basis of the simplified three-dimensional model and the lighting intensity corresponding to the vertex in the simplified three-dimensional model, rendering the simplified three-dimensional model, so as to obtain a model image for representing the simplified three-dimensional model. The method can automatically reconstruct and render a three-dimensional model, thereby improving the reconstruction efficiency of the three-dimensional model and reducing labor costs.

Disclosed are example embodiments of systems and methods for virtual try-on of articles of clothing. An example method of virtual try-on of articles of clothing includes selecting a garment from a pre-existing database. The method also includes loading a photo of a source model wearing the selected garment. Additionally, the method includes generating a semantic segmentation of the model image. The method also includes extracting the selected garment from the photo of the model. Additionally, the method includes determining a correspondence between a target model and the source model by performing a feature point detection and description of the target model and the source model, and performing feature matching and correspondence validation. The method also includes performing garment warping and alignment of the extracted garment. Additionally, the method includes overlaying and rendering the garment.

The invention discloses a diffusion model image completion method based on boundary preserving perception, and belongs to the technical field of artificial intelligence and image generation. The method comprises the following steps: firstly, preprocessing an input image and a corresponding defect mask, and extracting gradient attenuation boundary features and a structure edge graph; a boundary sensing convolution module is introduced into the completion model and is used for boundary information modeling of a coding end; meanwhile, a gating mechanism is adopted in U-Net jump connection, the weight of a gradient attenuation mask is combined, and the boundary information transmission intensity is dynamically adjusted; furthermore, in the diffusion generation process, a region self-adaptive scheduling strategy is adopted, only high-step diffusion iteration is carried out on a defect region and a boundary neighborhood, and low-step or freezing operation is carried out on a non-defect region, so that balance between boundary consistency and calculation efficiency is realized. Experimental results show that the method is superior to an existing diffusion model image completion method in the aspects of structure retentivity, edge continuity and visual quality, and has wide application prospects.

Systems and techniques are described herein for segmenting images. For instance, a method for segmenting images is provided. The method may include encoding, using a machine-learning-model image encoder, an image to generate a plurality of image features; selecting a first image feature from among the plurality of image features; determining a first image point related to the first image feature; encoding, using a machine-learning-model prompt encoder, the first image point as a first encoded prompt; generating, using a machine-learning-model image decoder, a first mask based on the plurality of image features and the first encoded prompt, wherein the first mask is indicative of pixels of the image that are semantically similar to the first image point; and storing the first mask.

The invention relates to the technical field of computer vision and deep learning, and discloses a cascade diffusion model-based virtual fitting method, which comprises the following steps of: inputting a model image and a target clothing image into a multi-condition diffusion model, and outputting a posture control variable and a depth control variable; integrating the posture control variable and the depth control variable into a de-noising U network through a multi-control injection module, and generating a low-resolution try-on image of the model wearing the target garment; inputting the low-resolution fitting image into the super-resolution diffusion model, and performing feature extraction on the low-resolution fitting image; feature codes corresponding to feature extraction are transmitted to a control network space through a full connection layer, then the feature codes are integrated into a super-resolution diffusion model through a cross attention mechanism, the super-resolution diffusion model is guided to reconstruct a low-resolution try-on image, and a high-resolution try-on image is generated. According to the method, high-fidelity and high-resolution clothing try-on image generation is realized through a multi-condition control and super-resolution reconstruction technology.

The invention discloses an image generation method and system, electronic equipment and a storage medium. The method comprises the following steps: acquiring an initial model image; performing human body posture recognition and mask segmentation processing on the initial model image to obtain a mask image; generating a clothing text cue word according to the basic quality constraint parameter, the semantic enhancement parameter and the attribute combination generation parameter; performing image generation processing on the mask image through a generation model according to the clothing text cue word to obtain a target generated image; and carrying out anti-detection edge optimization processing on the target generation image to obtain a target model image. The image generation efficiency can be improved, and the method can be widely applied to the technical field of image processing.

A respiratory motion plane alignment system and method based on ultrasound images is disclosed. The system acquires three-dimensional ultrasound images of respiratory organs at at least two different respiratory phases, calculates the motion direction of the respiratory organs based on the three-dimensional ultrasound images, controls and adjusts an ultrasound direction adjustment mechanism to align the scanning plane of the ultrasound probe with the motion direction of the respiratory organs, acquires a three-dimensional model image of the respiratory organs and multiple frames of real-time two-dimensional ultrasound images, performs registration between the multiple frames of real-time two-dimensional ultrasound images of the respiratory organs, and / or registers the three-dimensional model image and the multiple frames of real-time two-dimensional ultrasound images, acquires three-dimensional position data of a target point during respiratory motion, determines the tracking path of the ultrasound probe based on the three-dimensional position data of the target point during respiratory motion, and controls the ultrasound probe to move along the tracking path, thereby achieving long-term stable observation or tracking of target points in the respiratory organs.

The invention relates to the technical field of image restoration, in particular to a diffusion model image restoration method based on regional mask and dynamic exit, and mainly solves the technical problems of high calculation overhead and iteration step number redundancy of an existing diffusion model image restoration method. According to the method, on the basis of an extension architecture of encoding and decoding, a UNet denoising network and a ControlNet conditional constraint module, on the basis of retaining the core functions of an existing encoder, an existing decoder and an existing Unet denoising network, a space region mask generation sub-module, a back diffusion dynamic exit module and the ControlNet conditional constraint module are creatively integrated; and a triple optimization architecture of'constrain structure protection, space redundancy reduction and time step number reduction 'is formed, so that the structure consistency is met and efficient acceleration is realized during image restoration.

The invention belongs to the technical field of image processing, and particularly relates to a boundary intrusion target detection method based on machine vision, and the method comprises the steps: obtaining a boundary monitoring video frame sequence, extracting a grayscale image, and constructing a background model image based on a historical frame sequence; according to the gray scale change of the pixel point in the time window, a time sequence fluctuation index is obtained through the standard deviation of the time sequence gray scale set and the overturning frequency of the gray scale difference value; according to texture distribution characteristics in a pixel point neighborhood, obtaining a spatial discrete entropy through a gray level histogram; obtaining a direction chaos index through the vector sum modulus and the algebraic modulus sum of the motion gradient vector; and correcting the original motion response diagram according to the time sequence fluctuation index, the spatial discrete entropy and the direction chaos index to obtain an intrusion confidence coefficient, and carrying out connected region detection according to the intrusion confidence coefficient. According to the method, the environmental dynamic interference is effectively inhibited by fusing the time sequence oscillation, the space texture and the motion direction, and the accuracy of boundary intrusion detection is improved.

The invention relates to the technical field of image processing, in particular to an anesthesiology department airway intubation image recognition method based on artificial intelligence. The method comprises the following steps: acquiring an airway CT image of a patient at double view angles, constructing a multi-curvature airway model and generating a corresponding image; correcting the model image in combination with the inherent distortion parameter of the lens to obtain a distortion corrected image; secondly, the influence of different curvatures on distortion is quantified under a multi-curvature distortion correction image, and a curvature-direction-distortion correction factor mapping relation is generated; acquiring a current airway image in real-time intubation, extracting curvature features by performing pixel-level matching with the distortion correction image, associating the curvature features with the mapping relation, and determining a distortion correction index corresponding to the current airway image; and finally, performing double correction on the current airway image by combining the lens distortion parameter and the distortion correction index, and generating a high-credibility airway correction image for subsequent image recognition.

Provided are an image recognition program capable of accurately counting the population of nematodes that are detection targets even when a plurality of detection targets overlap each other, an image recognition device using the same, a detection target population counting method, and a model image creation device for image recognition learning to be used therefor.An image recognition program causes a control unit 11 and a storage unit 12 of an image recognition device 1 to function as detection target image acquisition means for acquiring a detection target image showing a plurality of nematodes 3, extraction means for extracting from the detection target image a detection target presence area that possibly includes an image of the nematodes 3, storage means for storing a plurality of pattern images including a single-body pattern image showing one of the nematodes 3 and a multiple-bodies pattern image corresponding to an image showing two or more of the nematodes 3 overlapping each other, and recognition means for recognizing the population of nematodes 3 included in the detection target presence area by detecting a degree of concordance between an image of the detection target presence area and each of the pattern images.

The invention discloses an RH refining furnace control method and related equipment, and relates to the technical field of steel smelting, the method comprises the following steps: obtaining in-furnace color image data of a target RH refining furnace; performing flame state recognition on the color image data in the furnace through a first preset model to obtain a flame detection result; performing material adding action recognition on the color image data in the furnace through a second preset model to obtain blanking event information; performing metallurgy stage feature extraction on the color image data in the furnace through a third preset model to obtain a refining state recognition result; and according to the flame detection result, the blanking event information and the refining state recognition result, interlocking control operation is triggered. Automatic judgment and interlocking control of key working conditions of the RH refining furnace are achieved through multi-model image recognition, the control precision and the system stability can be improved, and energy conservation, consumption reduction and refining quality improvement can be achieved.

The embodiment of the invention discloses a model rendering method and a related device, and the method comprises the steps: carrying out the simplification processing of a model structure of a to-be-processed target three-dimensional model based on the topological structure characteristics of the target three-dimensional model, and obtaining a simplified three-dimensional model; wherein the number of grids included in the simplified three-dimensional model is smaller than the number of grids included in the target three-dimensional model, and the difference between the simplified three-dimensional model and the target three-dimensional model meets a preset difference requirement; through illumination simulation processing, determining illumination intensity corresponding to a vertex in the simplified three-dimensional model when the simplified three-dimensional model is in the target virtual environment; and based on the simplified three-dimensional model and the illumination intensity corresponding to the vertexes in the simplified three-dimensional model, rendering the simplified three-dimensional model to obtain a model image for representing the simplified three-dimensional model. According to the method, the three-dimensional model can be automatically reconstructed and rendered, the reconstruction efficiency of the three-dimensional model is improved, and the labor cost is reduced.

The application relates to the technical field of image processing, and provides a model material replacement method and device for a design drawing. The method comprises the following steps: determining a target model from each model of a design drawing according to a received material selection instruction; obtaining a target material map corresponding to the material selection instruction from each material map of the target model; and merging the target material map, a light map, a diffuse reflection map and a reflection refraction map of the design drawing to obtain a model image of the target model in the design drawing; wherein the design drawing is an image obtained through rendering; the light map, the diffuse reflection map and the reflection refraction map are each layer obtained after the design drawing is rendered. The model material replacement method for the design drawing provided by the application can reduce the calculation amount of the model in the design drawing when the material is replaced, and reduce the resources consumed when the model material is replaced.

The present invention relates to a method for processing three-dimensional measurement data from a scanning probe microscopy system to provide three-dimensional topographic image data, as well as a method for performing scanning probe microscopy, a scanning probe microscopy system, a computer-implemented method, and a computer program product. The method comprises receiving 3D measurement data acquired by the SPM system into a processing device, the 3D measurement data typically mapping the topography of a structure provided by the substrate. The method further comprises digitally constructing model image data using shape contour data of the shape, and a regression operation to fit the model image data to the 3D measurement data. This results in a composite model image of the 3D measurement data that can be used as a topographic image.

To provide a driving assistance device capable of displaying a three-dimensional object without causing distortion or stretching relative to its original shape, even when displaying an image captured by an imaging device.SOLUTION: A driving assistance device is configured to: detect tires of other vehicles included in a captured image where a periphery of an own vehicle is captured; acquire a model image 55 showing appearance of a vehicle excluding tire portions; and based on positions of the tires of the other vehicles included in the captured image, perform editing, on the model image 55, including at least one or more of enlarging, reducing, and rotating; and generate a support image 61 by combining the edited model image 55 while aligning the combined support image with the position of the tires of the other vehicles included in the captured image; and display the generated support image on the liquid crystal display 4.SELECTED DRAWING: Figure 8

Provided is a driving assistance device in which: an overhead image in which surroundings of a vehicle is viewed vertically downward from a virtual viewpoint set above the vehicle is displayed on a display device; when there is an object of attention, which is an object requiring attention for the vehicle, around the vehicle, a model image indicating an appearance of the object of attention is disposed and displayed at a position of the object of attention in the overhead image; and in displaying the model image, the model image is inclined and displayed in a direction in which a display area of the model image in the overhead image increases according to a state of the object of attention.

The appearance customization method of a three-dimensional model, an electronic device and a storage medium provided by the present application relate to the technical field of three-dimensional modeling. The method comprises: obtaining a texture coordinate mapping diagram of a target three-dimensional model surface, the texture coordinate mapping diagram being used to represent a mapping relationship from the three-dimensional model surface to a two-dimensional plane; generating an appearance design texture file based on an image material selected by a user and a target region in the texture coordinate mapping diagram; and fitting the appearance design texture file to the target three-dimensional model surface based on the mapping relationship defined by the texture coordinate mapping diagram to obtain a virtual appearance model image. Thus, the present application can customize the appearance requirements of a three-dimensional model according to the personal preferences of a user, thereby avoiding the problem of aesthetic fatigue caused by fixed preset styles and improving the interactive interest and user participation of the three-dimensional model.

The invention provides a heterogeneous computing power model scheduling method and device, electronic equipment and a storage medium, and relates to the technical field of heterogeneous computing power resource dynamic scheduling. The heterogeneous computing resource demand parameter can be automatically analyzed, the real-time heterogeneous resource state of each computing node in the cluster is obtained, and the target computing node meeting the demand is accurately determined through the preset multi-dimensional resource matching strategy. Then, a containerized task instance is automatically started on the target node, heterogeneous computing resources are distributed according to requirements, the corresponding model mirror image is loaded, and the execution instruction is executed. The problems that in the prior art, due to the fact that a model mirror image management system and a scheduling system are separated, a scheduling strategy cannot sense the heterogeneous computing power requirement of an AI model, task definition lacks a reusable template and is tedious in operation, nodes are appointed manually, efficiency is low, errors are prone to occurring, and the resource utilization rate is low can be solved.

To provide an image generation device suitable for apparel design.SOLUTION: The image generation device generates an image representing a state in which a model wears clothing. The image generation device receives an input of clothing shape information indicating a shape of clothing, receives an input of fabric information regarding a fabric, receives an input of a model image including a model, and generates a wearing image based on the clothing shape information, the fabric information, and the model image. The wearing image is an image representing a state in which the model wears virtual clothing, and the virtual clothing is clothing in a case where clothing represented by the clothing shape information is manufactured using the fabric represented by the fabric information.SELECTED DRAWING: Figure 2

The invention discloses a camera quick calling and visualization method based on natural language understanding, and relates to the technical field of video monitoring and artificial intelligence crossing. Comprising the steps that S1, a full-amount camera database is constructed, S2, a camera space retrieval interface is provided, and S3, a map visualization front end is constructed; s4, providing an address-coordinate conversion service; s5, local privatization deployment: deploying a camera space retrieval interface, a front-end static resource and a large language model mirror image in an intranet GPU server; s6, constructing a large model knowledge newly establishing a knowledge base table Knowledgeprompt in the model mirror image for writing data, and constructing the large model knowledge base, and S7, receiving a query demand of a user for inputting a natural language in a dialog box; s8, performing semantic understanding, and calling an interface to return data; step S9, automatically dotting the map; and S10, playing the video stream as required.

This application discloses a method for identifying groove areas in aircraft parts, relating to the field of machining, and aims to solve the technical problem of low efficiency in existing methods for identifying groove areas in aircraft parts. The method includes the following steps: performing a first identification on a three-dimensional model image of the aircraft part to obtain a first identification result, wherein the first identification involves identifying groove areas in the three-dimensional model image of the aircraft part. The first identification includes a first coarse identification based on mathematical morphological pattern difference evaluation, a second coarse identification based on the feature patch attributes of the groove region's neighborhood, and a third coarse identification based on deep neural network learning; obtaining groove area identification result data based on the first identification result; and interactively judging the groove area identification result data with the three-dimensional model image of the aircraft part to obtain the groove areas in the three-dimensional model image of the aircraft part. This application can achieve automated identification of groove areas in aircraft parts, improving the efficiency of groove area identification.

A kind of well safety valve on-line detection and calibration method, comprising the following steps: (1) deployment downhole television, obtains safety valve image;(2) given the ground pressure needing calibration, record the image of safety valve;(3) utilize three-dimensional modeling and calibration software to draw model;(4), adjust model parameters to make model image consistent with actual camera parameters, obtain the image of safety valve in well, and record model safety valve opening degree;The present application utilizes downhole camera to detect safety valve gate position, measures the opening degree of safety valve by three-dimensional model imaging and parameter matching, calibrates the relationship between ground hydraulic system pressure and downhole safety valve opening degree, to realize the detection and calibration of downhole safety valve.

A driving assistance device includes: a vehicle surrounding image aquisitor acquiring a captured image of surroundings of a vehicle or by processing the captured image, as a vehicle surrounding image where the surroundings of the vehicle are visually recognized from a set viewpoint; an object detector detecting an object of attention being an object present around the vehicle requiring attention; a model image acquisitor acquiring a model image indicating an appearance of the object of attention; an assistance image generator generating an assistance image where the model image is synthesized with the vehicle surrounding image according to a position of the object of attention; and an image display displaying the assistance image on a display device such that the vehicle surrounding image excluding the model image has a luminance difference or a contrast ratio with the model image increasing stepwise as a distance from the viewpoint increases.

The present application relates to the technical field of image rendering, in particular to a rendering method and system for a model image interface, comprising the following steps: obtaining a view angle parameter and generating a screen pixel mapping result set of a surface patch, calculating a screen occupation ratio of the surface patch, generating a screen change feature of the surface patch in combination with a frame difference, generating a rendering scheduling sequence set based on the occupation ratio and the change feature, calling data in sequence to perform rasterization processing, and generating a rendering result of the model image interface. In the present application, the visual presentation weight under the current visual field is calculated by extracting vertex coordinate mapping, the difference in occupation ratio between the front and back frames is analyzed by using the finite difference method to capture the dynamic change trend, the dynamic rendering scheduling sequence is constructed based on the double dimensions of the occupation ratio and the change feature, the calculation resources are accurately tilted to the high screen occupation ratio and the high dynamic change area, the rendering quality of the core visual area is ensured, the invalid calculation overhead is greatly reduced, and the interface rendering real-time performance and frame rate stability in complex scenes are effectively improved.