10 results about "Image name" patented technology

1. The name of the design product: electric rice cooker control graphical user interface for electronic devices. 2. The use of the design product: for electronic devices. 3. The design points of the design product: the content of the graphical user interface in the screen. 4. The picture or photo that best indicates the design points: front view. 5. The use of the graphical user interface: the front view is the interface display in standby state. User clicks "smart rice box" button interface change state figure 1. Interface change state figure 1 is the smart rice box secondary page, the current user clicks "rice box storage" interface change state figure 2. Interface change state figure 2 is the selection of rice variety interface, the first card fixedly displays the rice card, the initial entering page displays "not added" word, and other cards can be added rice variety by the user. The current user clicks any "select rice variety" card interface change state figure 3. Interface change state figure 3 is the selection of rice variety interface, the left side displays the storage prompt composed of schematic diagram and annotation text, the middle can slide up and down to select rice variety, and the right side can slide to select storage date. Click the "save" button in the upper right corner interface change state figure 4. Interface change state figure 4 is the interface after all rice varieties are added, and the interface shows the card composed of the picture, name and storage day of each rice variety.

1. The name of the design product: the whole board display area of the electronic substrate inspection management graphical user interface of the electronic device and the list of part names. 2. The use of the design product: an electronic device. 3. The design points of the design product: the interface content of the graphical user interface. 4. The picture or photo that best indicates the design points: design 1 front view. 5. The design for which protection is sought contains color. 6. Design 1 is designated as the base design. 7. The use of the graphical user interface: overall use: for a device that takes X-ray perspective images of electronic substrates and performs non-destructive inspections, for a user to set inspection items and confirm inspection results; partial use: as shown in the front view of each design, when the user selects an image name from the list of part names at the bottom left of the graphical user interface, the image is displayed in the central part of the graphical user interface, the whole image of the substrate is displayed in the whole board display area at the top left of the graphical user interface, and the position of the currently selected and displayed image on the whole board is displayed in an emphasized manner. 8. Other circumstances that need to be explained: the part not requiring protection is indicated by a dashed line in the figure.

Methods, devices, and storage media are provided, including detecting adding a lock to an album stored in a first internal storage area corresponding to a gallery, and in response, adding the lock to the album and starting a system application corresponding to the lock, sending a picture name in the album to the system application through a file opening interface between the gallery and the system application, and where a second internal storage area corresponding to the system application does not include a picture file for the picture name, creating the picture file in the second internal storage area, obtaining a first file descriptor of the picture file, and returning the descriptor to the gallery, obtaining picture content written by the gallery into the second internal storage area based on the descriptor, disabling the file opening interface, and storing the picture content in the second internal storage area.

The invention relates to a multi-image named entity recognition method and device and electronic equipment, and relates to the technical field of natural language processing, and the method comprises the steps: calculating the similarity score of each image and a named entity in text data based on an image-text similarity discrimination model fed back by human beings, and calculating the similarity score of each image and the named entity in text data based on a multi-modal large language model and a similar example perception model; auxiliary knowledge is generated in combination with the text data, the multiple images and the manual annotation sample set; extracting multi-scale layered visual features of each image; and determining fusion visual features for the multi-scale layered visual features based on a dynamic gating mechanism, performing weighted aggregation on the fusion visual features according to similarity scores, performing cross-modal interaction on the aggregated fusion visual features and auxiliary knowledge to obtain a text hidden vector sequence, and identifying the named entities in the text data based on the text hidden vector sequence. Noise can be effectively filtered in a multi-image scene, multi-scale visual information is fused, reliable auxiliary knowledge is generated, and entity recognition accuracy is improved.

The invention provides an intelligent substation inspection defect detection method and system based on text prior, and belongs to the technical field of substation equipment defect image detection in the power industry. The method comprises the following steps: acquiring a substation patrol image, inputting the substation patrol image into a positive sample detection model, judging whether the patrol image is an abnormal image or not, and keeping the abnormal image; extracting text prior information in image names of the inspection images judged to be abnormal, and generating a normalized prior vector based on a mapping relation between equipment parts and defect types; inputting the abnormal image and the normalized prior vector into a negative sample detection model, performing directional defect detection, and outputting a defect type; the negative sample detection model is an improved YOLOv8 model, and the improved YOLOv8 model introduces a channel attention module behind each C2f module of the backbone network. According to the method, the detection precision is improved, the secondary auditing workload of operation and maintenance personnel is reduced, the calculation cost is reduced, and the detection real-time performance is improved.

This invention discloses a method, system, computer device, and medium for optimizing the size of an application installation package. The method includes: searching for resource information of all images in the APP package to be optimized; collecting the target image names reported by the APP package in the runtime environment within a preset period, and determining the loading frequency of each target image name based on the reported target image names; determining the image sequence to be optimized based on the loading frequency of each target image name and the resource information of all images; and optimizing the image sequence to generate an optimized APP package. Because this application determines the image sequence to be optimized by determining the loading frequency of each target image name, the loading frequency can determine the specific number of times each image is used, thereby ensuring that the APP package size is reduced without affecting the fast loading of frequently used images, thus improving the user experience.

1. Name of the product in this design: Graphical user interface for viewing images and details of industrial vision software for electronic devices. 2. Purpose of this design: An electronic device. 3. The key design feature of this product is its graphical user interface. 4. The picture or photo that best illustrates the key design points: Design 1 front view. 5. Design 1 is designated as the basic design. 6. Purpose of the graphical user interface: A graphical user interface used for browsing images and viewing details of corresponding tags in industrial vision software. 7. Human-computer interaction method of graphical user interface: Design 1 main view is the product homepage; Clicking the image name in the left list of Design 1 main view displays the original image and label box, resulting in Design 1 interface change state diagram 1; Enter text in the input box in the lower right part of Design 1 interface change state diagram 1, resulting in Design 1 interface change state diagram 2; Click "Comment" in the lower right corner of Design 1 interface change state diagram 2 to comment on the image, resulting in Design 1 interface change state diagram 3; Hover the mouse over the image in Design 1 interface change state diagram 3 and scroll the mouse wheel inward to zoom in on the image, resulting in Design 1 interface change state diagram 4; Drag the "Draw Thick Line" button on the right side of Design 1 interface change state diagram 4 to obtain Design 1 interface change state diagram 5. Design 2's main view is the product homepage; clicking on the image name in the left-hand list of Design 2's main view displays the original image and its label box, resulting in Design 2's interface change state diagram 1; entering text in the input box in the lower right corner of Design 2's interface change state diagram 1 results in Design 2's interface change state diagram 2; clicking "Comment" in the lower right corner of Design 2's interface change state diagram 2 allows you to comment on the image, resulting in Design 2's interface change state diagram 3; hovering the mouse over the image in Design 2's interface change state diagram 3 and scrolling the mouse wheel inwards zooms in on the image, resulting in Design 2's interface change state diagram 4; dragging the "Background Transparency" indicator on the right side of Design 2's interface change state diagram 4 results in Design 2's interface change state diagram 5. Design 3's main view is the product homepage; clicking on the image name in the left-hand list of Design 3's main view displays the original image and its label box, resulting in Design 3's interface change state diagram 1; entering text in the input box in the lower right corner of Design 3's interface change state diagram 1 results in Design 3's interface change state diagram 2; clicking "Comment" in the lower right corner of Design 3's interface change state diagram 2 allows you to comment on the image, resulting in Design 3's interface change state diagram 3; hovering the mouse over the image in Design 3's interface change state diagram 3 and scrolling the mouse wheel inwards zooms in on the image, resulting in Design 3's interface change state diagram 4; clicking the label selection box on the right side of Design 3's interface change state diagram 4 deselects the label box for that image, resulting in Design 3's interface change state diagram 5. 8. Other situations requiring explanation: Other explanation: The gray blocks in the interface represent replaceable content screens.

The application discloses a method and device for copying an image, and relates to the technical field of cloud computing. A specific embodiment of the method comprises the following steps: receiving an image file downloading request sent by a terminal, wherein the image file downloading request carries an image name; creating a first directory according to the image name, downloading an image layer information table file and each layer file from a source image warehouse, and storing the image layer information table file and the each layer file under the first directory; compressing and encrypting the first directory to obtain an image compressed file; and returning the image compressed file to the terminal. The embodiment can solve the technical problems of time consumption, occupation of file system resources and security risks.

This invention discloses an intelligent screenshot storage method, device, and storage medium. After receiving an image acquisition command at a first screenshot command terminal, a screenshot operation is performed on a specified area of ​​the screen to acquire the target image. Field information from multiple text components—including at least a first text component for displaying and inputting first field content, and a second text component for displaying and updating second field content—is acquired. The acquired first and second field content are then combined according to a preset naming format to form an image name for the target image. The target image is named according to this image name and saved to a local image folder. Finally, the current second field content is modified according to a preset second field content update rule, saved, and displayed on the second text component. This achieves automated acquisition and management of various screenshots during computer system verification, reducing the tediousness and error rate of manual operations.

The invention discloses a container mirror image metadata analyzing, editing and uploading method and system based on a Web front end, and belongs to the technical field of computer software and containerization. The invention aims to solve the problems of network flow waste, large storage pressure and operation splitting caused by the fact that a complete Tar format file needs to be uploaded to a server for processing in a traditional scheme. According to the scheme, the OCI Tar format file selected by the user is directly analyzed at the browser end, the mirror image list is extracted and visually displayed, the user is supported to edit metadata such as mirror image names, labels and self-defined attributes on line, the mirror image is pushed to the remote warehouse through an incremental direct transmission mechanism after confirmation, and the uploading progress and the abnormal prompt are fed back in real time. The whole process does not need to be transferred by a server, so that the bandwidth and the storage overhead are remarkably reduced, the interaction efficiency and the user experience are improved, the lightweight and end-to-end container mirror image management capability is realized, and the method is suitable for DevOps platforms, private cloud environments and edge computing scenes.