937 results about "Mobile end" patented technology

The invention relates to a method and system for encrypting and isolating storage data of a credential mobile terminal, and belongs to the technical field of information. The method comprises the following steps: encrypting and partitioning the whole storage area, and setting an access strategy according to user permission; when a user requests to access, executing multi-factor authentication containing a password and an external hardware certificate, and adding biological characteristic authentication; after the authentication is passed, an encryption key is taken from the domestic security chip; and encrypting and decrypting data by using the secret key, and opening corresponding partition access according to authority. The system comprises a storage partition module, an identity authentication module, a key management module, an encryption and decryption module and an authority control module and is used for executing the method. The method also comprises the steps of equipment startup trusted boot and firmware upgrade verification, is based on a custom curing system, and is compatible with Android 10 +. The problems of poor hardware controllability and positioning security risk of the creative mobile terminal are solved, and full-link data security protection is realized.

The invention discloses a multi-platform real-time field rice ear detection and counting method based on a visual converter, which is suitable for various acquisition platforms from a portable mobile terminal to an unmanned aerial vehicle terminal and the like, and meets the requirements of small-range accurate identification and large-range high-throughput monitoring. Aiming at the characteristics of multiple scales, multiple varieties, phenotype difference, time sequence change, complex field environment and the like in a data set, a rice spike detection counting network comprising a feature enhancement module, an efficient cross-space feature extraction network, a lightweight bidirectional feature fusion module and a number estimation and detection head module is constructed. The average precision mean value (mAP50) of the model reaches 0.8906 and is improved by 11.5% compared with that of an original model, the parameter quantity is reduced by 29%, and the calculated quantity (GFLOPs) is reduced by 48%. The method can effectively process rice ear images of different scales and growth periods, adapts to morphological change, overcomes interference such as illumination, phenotypic difference and shielding, and provides technical support for rice yield evaluation and field rice ear quality analysis.

The invention belongs to the technical field of intelligent measurement, and discloses a mobile terminal automatic measurement method and system based on YOLO key point detection and an AR platform, and the method comprises the steps: obtaining multi-modal data, and carrying out the preprocessing; performing target detection and key point positioning based on the RGB image to obtain two-dimensional key point coordinates; based on the depth image and the pose information, a three-dimensional space coordinate system is established, the two-dimensional key point coordinates are converted into the three-dimensional space coordinate system, and in the conversion process, a self-adaptive weight fusion mechanism is adopted to perform fusion on the multi-modal data to obtain a fusion result; a nonlinear error propagation control model is adopted to suppress error accumulation in the process of converting the two-dimensional coordinates into the three-dimensional coordinates; and calculating morphological parameters of the target object based on the converted three-dimensional key point coordinates. According to the invention, the problems of low measurement efficiency, poor precision, high equipment cost, insufficient cross-platform adaptation and the like in the prior art are solved, and high-precision, real-time and low-cost automatic measurement of various types of target objects at the mobile terminal is realized.

The invention relates to a heading machine pose measurement and control method and system based on visual direction finding and communication distance measurement. The system comprises a base station end measuring system in a roadway, a mobile end measuring system on a heading machine body and a motion control module. The method comprises the following steps: S1, establishing a base station end coordinate system; s2, establishing a mobile terminal coordinate system; s3, the base station side identifies and measures the vector information of the characteristic light source of the mobile terminal through a visual sensor; s4, the base station end and the mobile end measure the distance between the base station end and the mobile end through communication ranging equipment; s5, calculating the three-dimensional position of the mobile terminal in the coordinate system of the base station terminal based on the vector information and the distance information; s6, according to the three-dimensional position and the inertial measurement data of the mobile terminal, carrying out combined navigation calculation based on an EKF algorithm; and S7, performing pose control based on a combined navigation calculation result. According to the invention, a means of combining visual direction finding, communication distance measurement and inertial measurement is adopted, so that the position measurement precision is improved.

The invention relates to the technical field of block chains, and particularly discloses a virtual article secure transaction method, device and system, a medium and a server. The method relates to a mobile terminal, a proxy server and an issuing server, is executed by the proxy server and is used for receiving encrypted ciphertext transaction data sent by the mobile terminal and transmitting the data to the issuing server, so that the issuing server issues a virtual article corresponding to the transaction data obtained by decryption to the mobile terminal, and after the issuing server issues the virtual article, the virtual article is sent to the mobile terminal. And the proxy server and the issuing server carry out account checking. According to the method, the transaction data is encrypted by using the fully homomorphic encryption algorithm in the data transmission process, it is ensured that the proxy server cannot obtain plaintext transaction data, and account checking is performed by the proxy server and the issuing server, so that the problem of non-uniform bills is solved.

The invention discloses a three-dimensional visualization head and neck tumor preoperative imaging system based on deep learning. The method comprises the following steps: image analysis and preprocessing; carrying out image denoising and spatial-temporal feature extraction based on a deep learning convolutional neural network architecture, and introducing a u-Net model to realize image segmentation and semantic annotation; performing three-dimensional reconstruction and surface rendering by adopting a Marking Cubes algorithm, and realizing visual interaction image presentation and personalized operation by combining volume rendering and surface rendering; and data is output through multiple ports, and data viewing and interactive operation of a web terminal and a mobile terminal are supported. The method has the advantages that according to the technical scheme, through fusion of a three-dimensional attention mechanism and multi-phase data, the tumor segmentation Dice coefficient reaches 0.92 + / -0.03, and the method is superior to a traditional threshold segmentation method.

The invention discloses a fuzzy video real-time jitter removing method and system, and the method comprises the steps: distributing feature points through multi-scale FAST detection, lightweight MLP detection and dynamic weight, combining a MobileNet-FPN network and the lightweight MLP dynamic weight to extract the robust features of the feature points, modeling the global matching relation of the feature points of two adjacent frames through Transform, and carrying out the real-time jitter removing of a fuzzy video. And a Bayesian adaptive RANSAC algorithm is adopted to realize high-efficiency mismatching pair elimination, and finally an affine transformation matrix is solved and reverse mapping is performed to compensate jitter. According to the method, while the real-time performance of the mobile terminal is ensured, the image stabilization precision in a violent shaking scene is remarkably improved.

The invention belongs to the technical field of oil and gas drilling well control equipment, and particularly relates to a ram blowout preventer state confirmation method with a locking indication window, which comprises the following steps: arranging a transparent observation window on a blowout preventer shell, and calibrating the alignment position of the end face of a locking shaft and an inner side reference scribed line; after the locking action is executed, the alignment state is confirmed through multi-angle visual observation; a switchable auxiliary light source is integrated to eliminate visual interference; an industrial camera is used for collecting images, displacement deviation is recognized through an edge detection algorithm, and an alarm is given if the displacement deviation exceeds the limit; and generating an encrypted digital report containing a timestamp and equipment information, uploading the encrypted digital report to a monitoring platform, and supporting real-time check and electronic signature of a mobile terminal. Through three layers of mechanisms of standardized vision-mechanical mapping, optical enhancement and digital perception, high-reliability, high-compatibility and traceable locking state confirmation is realized.

The invention relates to the technical field of mobile application continuous integration automation, and discloses a multi-channel APP automatic packaging system which comprises the steps that byte code files in a released mobile terminal APP installation package are acquired, and an occupied symbol space set is generated; generating an available confusion namespace by using set complementary operation; extracting method-level code change by using an abstract syntax tree difference algorithm, and generating a change method set; generating a patch special confusion rule for the change method set by using a namespace allocation algorithm; compiling and obfuscating the change method set by applying a patch special obfuscating rule to generate a safe obfuscating patch byte code; performing packaging and signature operation on the safe obfuscation patch byte code, and outputting a minimized obfuscation safe hot repair patch pack; according to the method, the technical problems that class definition conflicts or method calling errors occur after the hot repair patch is loaded, and the downloading success rate of a user is affected due to the overlarge size of the hot repair patch are solved.

The invention relates to the technical field of intelligent wearable equipment, and discloses an intelligent wearable system integrating multi-modal physiological monitoring and active intervention, which comprises a ring end acquisition module, a mobile end cache module and a cloud intelligent analysis module, and the cloud intelligent analysis module comprises a multi-modal fusion analysis unit, an active intervention decision unit and a user digital twinborn model construction unit, and is used for calculating a sleep score, a readiness score, a pressure index, a blood oxygen trend and a menstrual period prediction result according to the multi-source physiological characteristics, and executing an active intervention decision based on a health state. The sensing module is integrated in the ring body, the light-weight design is suitable for long-term wearing, all-weather data acquisition is guaranteed, compared with a bracelet or a watch, the ring is comfortable and hidden to wear, the continuous use willingness of a user is enhanced, meanwhile, the ring is suitable for high-voltage office or sports scenes, and non-inductive health monitoring is achieved.

The invention relates to the technical field of traffic engineering management, and particularly discloses a traffic engineering quality safety dynamic supervision and management system and method, and the method comprises the steps: constructing a multi-dimensional sensing network which comprises an entity, an environment and a behavior sensing layer, and collecting data; a three-dimensional model is built based on the BIM technology, and standardized data and model millisecond mapping are fused and visualized; an LSTM and random forest hybrid algorithm is adopted to establish a three-level early warning model, and risks are identified and pushed in a graded manner; matching the disposal flow according to the early warning level, tracking the progress by the mobile terminal, and checking the closed loop in a grading manner; and key node data are stored through a multi-level block structure, an alliance chain permission, a consensus mechanism and an intelligent contract, so that reverse tracing is realized. According to the invention, real-time acquisition, dynamic modeling, intelligent early warning, co-processing and credible tracing of quality safety data in the traffic engineering construction process are realized, the quality safety risk is reduced, and the management efficiency and supervision transparency are improved.

A portable air-cooled fiber laser device disclosed by the present invention comprises a box body, a laser pumping source, a fiber output assembly, a power supply assembly, a heat dissipation engine and a control circuit are integrated in the box body, the power supply assembly adopts a drawable structure, a replaceable battery is arranged in the power supply assembly, and energy supply without an external power supply is realized. The heat dissipation engine is arranged in a sandwich type structure and is composed of a heat dissipation fin set and heat pipes embedded in the heat dissipation fin set, a transverse ventilation heat dissipation channel is formed through a heat dissipation fan, and efficient heat management is achieved. Connection with a mobile terminal or computer equipment in a wired or wireless mode is supported, and remote control over the operation state of the laser is achieved. The device is compact in structure, efficient in heat dissipation and convenient to carry, has good heat dissipation performance, independent power supply capacity and environmental adaptability, is suitable for application scenes such as multi-scene field operation and emergency use, and has good practicability and popularization value.

The invention discloses an ultra-short baseline positioning method based on a binary short baseline, and belongs to the technical field of underwater acoustic target navigation positioning. The method comprises the following steps: S1, designing a spread spectrum underwater acoustic communication signal for underwater acoustic communication between an ultra-short baseline transceiver and a transponder; s2, solving ultra-short baseline time delay information by adopting a frequency domain correlation method, and obtaining high-precision time delay information through an interpolation method; s3, two sets of transceivers with known positions are installed at the ship end at a preset interval distance, and the two sets of transceivers form a binary short baseline framework; installing at least one group of transponders at the mobile terminal, and obtaining the distance information of the two groups of transceivers and the transponders and the initial position information of the mobile terminal; and S4, based on the two groups of distance information and the initial position information, performing binary short baseline positioning calculation by adopting an iterative optimization algorithm to obtain high-precision position information of the mobile terminal. The ultra-short baseline positioning method based on the binary short baseline is high in positioning precision and high in stability, and can still realize high-precision target positioning in a low signal-to-noise ratio environment.

The invention discloses a mobile terminal real-time action monitoring method and system. The method belongs to the technical field of neural network target monitoring. The problem that the application effect of an existing mobile terminal motion monitoring model in real-time scenes such as monitoring APP and AR interaction is seriously restricted due to the fact that the existing mobile terminal motion monitoring model is difficult to balance the monitoring precision, the model size and the reasoning speed is solved. A complete data set construction process of data collection, frame extraction, standardized preprocessing, multi-dimensional enhancement and double-input construction is provided, and the generalization ability of the model is remarkably improved; a 3D convolution and ResNet fused lightweight model is designed, the action spatial-temporal feature capture capability and the mobile terminal deployment requirement are considered, and the model parameter scale is only 60% of that of a traditional 3D CNN model; through double-input data construction and a result optimization mechanism, the monitoring accuracy of the model in a real scene is not lower than 84%, and the actual application requirement is met.

The invention discloses a hospital inquiry system based on the Internet. The hospital inquiry system comprises a business platform layer, a multi-terminal application layer, a composite interaction layer and a verification layer, the service platform layer is constructed by adopting a Java Springboot and SpringCloud micro service architecture, and a plurality of core functions can be packaged into an independent service process; the multi-end application layer can select an optimal technology stack to form a multi-end application based on operation habits and performance requirements of different terminal users, and each end performs front-end and back-end separated interaction with the service middle station through an API gateway; and the composite interaction layer is used for establishing a communication link between a doctor and a patient so as to carry out a full-service process of online inquiry, prescription making and medicine distribution. According to the system, a one-stop business process of online inquiry, prescription extraction, medicine purchasing and distribution is realized, meanwhile, doctors are supported to receive diagnosis through a mobile terminal or a computer anytime and anywhere, and the problem that the licensing behaviors of the doctors are bound to fixed places and time of physical hospitals is solved.

The invention discloses an overhead line foreign matter detection method and system based on a lightweight YOLO network, and relates to the technical field of power transmission lines. Multi-scene power transmission line images are collected through an unmanned aerial vehicle, a multi-scene power transmission line foreign matter data set is constructed, the images are amplified through a mixed data enhancement method, and a target image set is obtained; inputting the target image set into a preset target model to detect the foreign matter of the overhead line; if the foreign matter is detected, generating a foreign matter label; adding the foreign matter label into a preset 3D model diagram of the power transmission line; the foreign matter label comprises position coordinates and identification types of the foreign matters. The YOLOv5 model is improved to reduce the parameter quantity of the model, the performance improvement and real-time detection are realized, and the system can be carried on embedded equipment with limited storage space and calculation capability, such as a mobile terminal, so that the system can be deployed in an actual power transmission line inspection system to meet the actual application requirements.

The invention belongs to the technical field of power equipment fault diagnosis, and particularly discloses a knowledge distillation-based 1D-CNN online partial discharge identification method, which comprises the following steps of performing Fourier transform on an original signal and then implementing four data enhancements of amplitude modulation, phase modulation, frequency band enhancement and frequency domain noise injection; constructing a multi-branch one-dimensional convolutional neural network to extract time-frequency features, and training a teacher model in combination with residual connection and an SE attention mechanism; compressing the teacher model into a lightweight student model by adopting a knowledge distillation strategy of a preset temperature parameter and a weight coefficient; the student model is converted into a mobile terminal compatible format, and a mobile phone APP is established through a QT upper computer; and online real-time identification is realized. According to the method, the problem of sample imbalance is effectively relieved, in addition, the knowledge distillation realizes model volume compression and reasoning speed increase while keeping relatively high accuracy, the calculated amount is small, the real-time performance is high, and the precision is high.

The invention discloses a new media advertisement putting and monitoring integrated system, and the system comprises a user portrait construction module which obtains the browsing behavior, geographic position and social interaction data of a user at a mobile terminal, a PC terminal and an intelligent terminal through a multi-source data collection unit, and generates a dynamically updated user interest tag; the intelligent advertisement putting engine is used for matching advertisement contents with user portraits in real time based on a deep reinforcement learning algorithm and supporting programmed cross-platform bidding and private market direct putting; according to the invention, through multi-dimensional effect evaluation, emotion analysis and user life cycle value prediction are introduced, and a comprehensive evaluation system is constructed; data security is enhanced, and through homomorphic encryption and block chain technologies, user privacy is guaranteed and a non-tampering effect auditing voucher is provided. The customer obtaining cost of advertisers can be obviously reduced, and the rate of return on investment is improved.

The invention relates to a road and bridge engineering quality supervision method and system based on mobile internet multi-terminal cooperation. The method comprises the following steps: generating a space-time composite label by fusing engineering data collected by a mobile terminal, a Beidou time service signal, multi-source positioning information and BIM component characteristics; dynamic drift compensation is carried out on the digital twin model by utilizing the attenuation characteristic of the material, and position deviation caused by long-period construction is eliminated; intelligent arbitration of multi-terminal operation conflicts is realized based on space-time overlap analysis; generating a lightweight incremental data packet according to the change priority; and finally, synchronously generating a visual supervision interface fusing the BIM model, the quality anomaly annotation and the drift thermodynamic diagram at a mobile terminal, a PC terminal and a large screen terminal through a multi-resolution rendering engine. According to the invention, three core problems in the prior art that the positions of the model and the entity are mismatched, multi-terminal collaborative conflicts frequently occur and the visualization efficiency of heterogeneous equipment is low are solved, and the accuracy, the collaboration and the decision-making efficiency of road and bridge engineering quality supervision are remarkably improved.

The invention discloses an ADHD screening method and system based on mobile terminal eye movement tracking and a multi-modal agent. The method comprises the following steps: (1) collecting and preprocessing mobile terminal eye movement data; (2) performing fixation point estimation based on a lightweight MGazeNet model; (3) eye movement feature extraction based on a multi-normal form interaction task; and (4) carrying out comprehensive diagnosis analysis based on machine learning and a large model agent. The invention further provides an ADHD screening system based on mobile terminal eye movement tracking and the multi-modal intelligent agent. The ADHD screening system sequentially comprises the following modules: (1) a front-end data acquisition and preprocessing module; (2) an end side eye movement tracking reasoning module; (3) an interactive task control and feature calculation module; and (4) a multi-mode intelligent diagnosis and analysis module. The ADHD screening method effectively solves the problems that traditional ADHD screening depends on expensive professional equipment and subjective scales, so that the popularity rate is low, and objectivity is poor, screening portability and diagnosis objective accuracy are improved, and the intelligent level of ADHD auxiliary diagnosis and user interaction experience are improved.

The invention discloses a large model mobile terminal inference method supporting MoE slicing and video memory virtualization, and belongs to the field of artificial intelligence calculation. The method is realized through cooperation of a dynamic MoE slice scheduler and a video memory-memory unified virtualization manager, the scheduler evaluates hardware and model states in a multi-dimensional manner, an expert activation and loading mode is dynamically determined, and secondary experts are cut when a video memory is insufficient; the virtualization manager maintains hot, warm and cold hierarchical storage pools and executes data prefetching and swapping out, and expert slices of different computing cores complete topology sensing communication through an on-chip high-speed bus. According to the method, video memory self-adaptive scheduling is achieved, lossless and smooth degradation can be achieved, reasoning time delay and power consumption are reduced, the resource utilization rate is increased, a storage structure and a slice object can be flexibly adjusted, and the method is suitable for various mobile hardware and suitable for a mobile terminal large model reasoning scene.

The invention provides an inspection information off-line management method, which comprises the following steps that: an information input module acquires inspection information of a task area, and a mobile terminal establishes a problem processing item and an inspection table according to the inspection information; continuously detecting the network state between the mobile terminal and the gateway, and when the mobile terminal and the gateway are in an offline state, caching problem processing items and a patrol table into the database; when the mobile terminal and the gateway are in a networking state, the server module automatically acquires problem processing items and patrol tables from the database in real time; and the server module matches a corresponding execution unit according to the problem processing item and the patrol table, and pushes the problem processing item and the patrol table to the execution unit. According to the technical scheme of the embodiment, off-line information can be effectively collected and managed, and the data management efficiency is improved.

The invention provides a virtual environment rendering method and device, electronic equipment and a storage medium. The method comprises the steps that a scene visual area corresponding to a controlled virtual object located in a game scene is recognized; the area type of each grid in the scene visible area is obtained, and the multiple grids are obtained by dividing the game scene; and rendering the scene visible area according to an illumination execution mode corresponding to the area type. According to the method, the illumination quality and the performance overhead can be balanced, and the problems that a full-baking scheme cannot support a dynamic light source and the baking time is long are solved to a certain extent, and the problems that a full-real-time GI scheme is high in performance consumption and low in frame rate at a mobile terminal are solved.

The invention relates to the technical field of artificial intelligence and the field of medical information security and financial services, in particular to a short message anti-fraud method and device based on artificial intelligence, equipment and a medium. According to the method, the to-be-sent short message is analyzed, the to-be-sent short message and the equipment information are subjected to feature classification extraction, for any feature category, the corresponding feature vector is evaluated according to the evaluation model, all evaluation results are fused, and the communication number is marked as the blacklist number. And receiving the short message of the communication number is blocked. The method can be applied to business scenes such as financial service and medical information security, the to-be-sent short message is analyzed by using the first anti-fraud model through the mobile terminal, if the short message is a problem short message and a user confirms sending, the short message is reported to the cloud, the result is evaluated and fused, and the global blacklist is updated to stop receiving the short message. Therefore, the short messages are comprehensively analyzed in the short message sending process of the mobile terminal, and the short messages meeting the conditions are accurately marked and blocked.

The invention provides an electronic old-age card data closed-loop processing method and system based on an intelligent card. According to the method, biological characteristic information of a user is collected through a mobile terminal application, identity information is submitted, a government affair data platform interface is called to carry out remote identity verification, and encrypted identity element data of old people is generated; an APDU instruction stream is dynamically generated based on the JavaCard specification, and encrypted identity element data is written into a secure storage area of the smart card through a machine-card communication channel; reading encrypted data of the smart card in a business scene through NFC card reading equipment, generating a triple verification record in combination with a merchant identifier and a transaction timestamp, and feeding back a verification result to a merchant terminal; and synchronizing the triple verification record to a government affair data platform to form a traceable subsidy data chain for the government to approve subsidy issuing. According to the invention, remote safe writing and non-contact automatic verification of the identity information of the old people are realized, and the service convenience and the data credibility are improved.

The invention discloses a multi-terminal cooperative interaction method of an innovative practice teaching experiment platform, and belongs to the technical field of teaching experiment platforms, the innovative practice teaching experiment platform comprises a server, a plurality of terminals and experiment equipment, the terminals comprise a PC terminal, a mobile terminal and an experiment equipment terminal, the method comprises the following steps of terminal access authentication, unified protocol adaptation, resource scheduling and distribution, real-time data cooperative transmission and real-time data cooperative transmission. According to the invention, through the terminal access authentication step, the security of the terminal access platform is ensured, and threats to platform data and resources caused by access of illegal terminals are avoided; meanwhile, an encrypted communication link is established, so that the security of data transmission is ensured; by adopting an adaptive protocol conversion mechanism, uniform adaptation of communication protocols of different terminals is realized, the problem of data transmission caused by non-uniform communication protocols between different terminals in the prior art is solved, and standardization and high efficiency of data transmission are improved.

The invention relates to the technical field of television control, in particular to a television remote control method and system based on mixed gestures, the system comprises a mobile terminal and a television box terminal, the mobile terminal is used for obtaining an input event triggered by a user aiming at a touch interface, arbitrating the input event based on a preset conflict arbitration strategy, and sending the arbitration result to the television box terminal; and determining a target gesture type expected to be executed by the user, generating a corresponding control instruction and transmitting the control instruction to the television box end. And the television box end receives and analyzes the control instruction to obtain the operation content and the coordinate information so as to control the television interface to execute the corresponding target operation. Therefore, a user can realize accurate mixed gesture operation through the mobile terminal of the system without an additional physical remote controller, and the interaction effect of a mouse and a touch screen is simulated at the television box end, so that the operation efficiency of the television box end and the user interaction experience are improved.

The invention discloses a hardware perception lightweight target detection method and system, and belongs to the field of computer vision and artificial intelligence. According to the method, MobileNetV4 is taken as a main network, efficient feature extraction is realized in combination with a unified reverse bottleneck module (UIB), and a multi-query attention mechanism is embedded in a key position; in the multi-scale fusion stage, a bidirectional feature pyramid network BiFPN is adopted to enhance cross-scale information flow, and a detection head adopts a decoupling structure and introduces depth separable convolution to reduce calculation overhead; nAS is searched through a hardware perception neural architecture, and a network structure is optimized by taking delay, model size and power consumption as constraints; in the training stage, model precision is improved by means of knowledge distillation technology. According to the invention, low-delay and high-precision real-time target detection is realized in a mobile terminal, an embedded device and an edge computing device.

The invention discloses a TBR implementation method of a desktop GPU for mobile 3D application optimization, which comprises the following steps: defining block metadata of screen blocks in a Mesa driver, establishing a block manager, when a mobile application context is detected, acquiring GPU core parameters by the block manager, calculating the size of a basic block, dividing a screen into areas corresponding to shader arrays in number, and storing the areas in a memory; establishing a mapping table of a basic block, a computing unit and an L2 cache slice, generating a resource hash table, analyzing block metadata and the mapping table after whole frame rendering is started, determining a hardware channel according to the mapping table, scheduling rendering tasks according to priorities, and configuring a GPU rendering state. Then executing a vertex shader, rasterization, a fragment shader, depth testing and color mixing to complete block rendering, updating block metadata, merging intermediate data into a final frame buffer according to geometric information after rendering of all basic blocks is completed, and submitting the final frame buffer to a window system to complete single-frame display. And the operation efficiency of the mobile operation system and the mobile terminal 3D application on the desktop platform is optimized.

The invention relates to the technical field of mobile terminal testing, and discloses a 3D engine testing method and system, electronic equipment and a storage medium. A mobile terminal obtains a target test case set and a corresponding rendering test scene configuration file, loads the rendering test scene configuration file corresponding to a current test case and executes rendering operation; the verification frame is sent to the cloud, rendering target texture test diagrams corresponding to all rendering pipelines in the verification frame are obtained, an obtained rendering target texture test diagram set and a current test case identifier are sent to the cloud, the cloud compares the reference diagram with the test diagrams for the same rendering pipeline, the abnormity judgment result of each rendering pipeline is determined, and the abnormity judgment result is sent to the cloud. Compared with the prior art, the exported texture test chart is compared with the theoretical expected value of the rendering pipeline instead of depending on visual subjective judgment, the test result can be quantified, the similar fuzzy conclusion in visual sense is avoided, and the objectivity and reproducibility of the test are improved.