Abstract: Provided are a defect detection method and apparatus, and a computer-readable storage medium. Specifically, the method includes: obtaining a to-be-detected image; obtaining a feature map of the to-be-detected image based on the to-be-detected image, where the feature map of the to-be-detected image includes a feature map of spatial position coordinate information; and performing defect detection on the to-be-detected image based on the feature map of the to-be-detected image. By modifying a neural network structure of defect detection and extracting the feature map of spatial position coordinate information during the detection, this application makes the neural network for use of defect detection sensitive to a spatial position, thereby enhancing sensitivity of a detection neural network to the spatial position, and in turn, increasing accuracy of detecting some specific defect types by the detection neural network, and increasing accuracy of defect detection.

Abstract: A debugging method for production line devices may include: receiving control commands for a plurality of first devices in a production line, where respective control programs may be configured for the plurality of first devices; and calling the control programs for the plurality of first devices according to the control commands for the plurality of first devices respectively so as to debug the plurality of first devices.

Abstract: Embodiments of this application provide a method and apparatus for testing stability of a vision system, which can test whether the vision system is stable, so as to report a fault in a timely manner when the vision system is unstable, thereby guaranteeing accuracy of a measurement result of the vision system. The method includes: obtaining first position information of a spot inspection piece in a current image under the vision system; performing affine transformation on a reference contour model of the spot inspection piece for a position of the spot inspection piece in the current image based on the first position information, and obtaining, through fitting, a current contour model of the spot inspection piece in the current image based on the reference contour model; and determining stability of the vision system based on the reference contour model and the current contour model.

Abstract: A welding mark inspection method includes acquiring a picture including a welding mark, and obtaining a classification type of the welding mark based on the picture and a welding mark classification model. The welding mark classification model is configured to classify the welding mark based on characteristics of the welding mark.

Abstract: This application provides an apparatus and method for detecting tab folds, and an image analyzer. The apparatus for detecting tab folds includes: a first image obtaining module, configured to obtain a first image of a first lateral face of tabs of a battery cell; a second image obtaining module, configured to obtain a second image of a second lateral face of the tabs, where the second lateral face is different from the first lateral face; and an image analyzer, configured to obtain, based on the first image, a first number of layers of the tabs corresponding to the first lateral face, and obtain, based on the second image, a second number of layers of the tabs corresponding to the second lateral face, and determine, based on at least one of the first number of layers or the second number of layers, whether the tabs are in a folded state.

Abstract: A spot-checking method for a visual inspection system includes obtaining a plurality of to-be-inspected images, inspecting the plurality of to-be-inspected images to obtain defect types and/or parameters of a target object in the plurality of to-be-inspected images, and confirming availability of the visual inspection system based on the defect types and/or the parameters.

Abstract: A method and a device for defect detection are provided. The method includes: obtaining a defect eigenvector of an image to be detected; calculating a similarity score of the image to be detected for each known defect type according to the defect eigenvector; and performing defect classification on the image to be detected according to the similarity score. The similarity score between the defect eigenvector of the image to be detected and each known defect type is calculated, and then it is possible to distinguish known defects from unknown defects and accurately classify the known defects according to the similarity scores, so as to effectively detect the defects.

Abstract: Embodiments of the present application provide a detection method, a detection device, and a storage medium. The detection method may comprise: obtaining a to-be-detected image; obtaining a plurality of confidence levels corresponding to a plurality of detection items according to the to-be-detected image; and determining a detection result of the to-be-detected image according to the plurality of confidence levels and a plurality of detection thresholds, where the plurality of detection thresholds may be corresponding to the plurality of detection items and may be a non-inferior solution of objective functions of an overkill rate and a missed detection rate, the overkill rate may be the ratio of qualified ones detected as defective, and the missed detection rate may be the ratio of defective ones detected as qualified.

Abstract: A tab bending detection method and apparatus, an electronic device, and a storage medium are provided. The method includes: performing skeleton extraction on a sectional image of multiple layers of tabs to obtain a skeleton image of the multiple layers of tabs; merging damaged connected components in the skeleton image to obtain a merged connected component, where the damaged connected components are connected components on which breaking occurs in a same tab section; calculating a target number of the multiple layers of tabs based on the merged connected component and an undamaged connected component; and detecting, based on the target number and a preset number, whether any tab in the multiple layers of tabs is in a bending state. The damaged connected components are merged to obtain the merged connected component.

Abstract: A welding mark inspection method includes acquiring a picture including a welding mark, and obtaining a classification type of the welding mark based on the picture and a welding mark classification model. The welding mark classification model is configured to classify the welding mark based on characteristics of the welding mark.

Abstract: Embodiments of this application provide a defect detection method and apparatus. The method includes: obtaining an image for inspection; performing anomaly detection on the image for inspection to obtain an anomaly region image corresponding to the image for inspection; and performing defect classification on the anomaly region image to obtain defect detection information of the image for inspection. The defect detection method of the embodiments of this application is divided into two steps of anomaly detection and defect classification. Anomaly detection is performed on the image for inspection first, and then defect classification needs to be performed only on an anomaly region, reducing the workload of defect classification, thereby improving the efficiency of defect detection.

Abstract: Embodiments of this application provide a measurement method and a measurement apparatus. The measurement method includes: acquiring a first image and a second image of a target object, where the first image is acquired by a camera located on a non-backlight side of the target object, and the second image is acquired by a camera located on a backlight side of target object; and measuring the target object for size information according to the first image and the second image. The technical solution of this application can improve accuracy and precision of inspection while improving production efficiency.

Abstract: A method for detecting a number of tabs includes determining a pixel value of a first target pixel based on at least one pixel value of at least one first adjacent pixel adjacent to a first target pixel on a tab framework, and determining the number of tabs based on the pixel value of the first target pixel. Each of the at least one first adjacent pixel is an adjacent pixel of the first target pixel on a side in a first direction on the tab framework.

Abstract: A tab bending detection method and apparatus, an electronic device, and a storage medium are provided. The method includes: performing skeleton extraction on a sectional image of multiple layers of tabs to obtain a skeleton image of the multiple layers of tabs; merging damaged connected components in the skeleton image to obtain a merged connected component, where the damaged connected components are connected components on which breaking occurs in a same tab section; calculating a target number of the multiple layers of tabs based on the merged connected component and an undamaged connected component; and detecting, based on the target number and a preset number, whether any tab in the multiple layers of tabs is in a bending state. The damaged connected components are merged to obtain the merged connected component.

Abstract: An embodiment of this application discloses a method and device for detecting a defect of an electrode assembly, and a computer-readable storage medium. The method may include: determining a first segmented image of an electrode assembly body in an electrode assembly image based on a first preset threshold; determining a second segmented image of a tab in the electrode assembly image based on a second preset threshold, where the second preset threshold is less than the first preset threshold; and determining defect status of the electrode assembly based on the first segmented image and the second segmented image.

Abstract: This application provides a method for measuring dimensions to reduce measurement time and improve production efficiency, including: obtaining a first image and a second image of a to-be-measured workpiece, where the first image and the second image are images captured by a first camera and a second camera at different positions respectively; extracting a first corner set of the to-be-measured workpiece from the first image and a second corner set of the to-be-measured workpiece from the second image separately; rectifying position coordinates of the first corner set and position coordinates of the second corner set to obtain a position coordinate value of the first corner set and a position coordinate value of the second corner set in a same coordinate system; and obtaining dimensions of the to-be-measured workpiece based on the position coordinate value of the first corner set and the position coordinate value of the second corner set.

Abstract: Embodiments of this application disclose a method and apparatus for processing graphic symbol and a computer-readable storage medium. The method may include: obtaining a luminance component image of a to-be-processed image, performing binarization processing based on the luminance component image of the to-be-processed image to obtain a binarized image, and performing a grayscale morphological operation based on the binarized image to obtain a target image.

Abstract: This application provides a method for measuring dimensions to reduce measurement time and improve production efficiency, including: obtaining a first image and a second image of a to-be-measured workpiece, where the first image and the second image are images captured by a first camera and a second camera at different positions respectively; extracting a first corner set of the to-be-measured workpiece from the first image and a second corner set of the to-be-measured workpiece from the second image separately; rectifying position coordinates of the first corner set and position coordinates of the second corner set to obtain a position coordinate value of the first corner set and a position coordinate value of the second corner set in a same coordinate system; and obtaining dimensions of the to-be-measured workpiece based on the position coordinate value of the first corner set and the position coordinate value of the second corner set.

Abstract: Embodiments of the present application provide a detection method, a detection device, and a storage medium. The detection method may comprise: obtaining a to-be-detected image; obtaining a plurality of confidence levels corresponding to a plurality of detection items according to the to-be-detected image; and determining a detection result of the to-be-detected image according to the plurality of confidence levels and a plurality of detection thresholds, where the plurality of detection thresholds may be corresponding to the plurality of detection items and may be a non-inferior solution of objective functions of an overkill rate and a missed detection rate, the overkill rate may be the ratio of qualified ones detected as defective, and the missed detection rate may be the ratio of defective ones detected as qualified.

Abstract: Embodiments of this application provide a method for detecting a target point in an image. The method may include: obtaining an image under test, where the image under test may include a structure-stable first target object and a structure-unstable second target object; and processing the image under test based on a target point detection model to obtain a target point in the image under test, where the target point may include a feature point on the structure-stable first target object and a feature point on the structure-unstable second target object.