6results about How to "Realize automatic labeling" patented technology

The utility model discloses an egg box gluing and labeling automatic integrated device which comprises a conveying assembly, a bearing assembly, a gluing assembly and a rubberizing assembly, a rubberizing station is arranged on a conveying path of the conveying assembly, the conveying assembly is used for conveying egg boxes to be labeled to the rubberizing station in the first direction, the bearing assembly is arranged on the side of the rubberizing station, and the rubberizing assembly is used for conveying the egg boxes to be labeled to the rubberizing station in the second direction. The bearing assembly is used for bearing a label to be glued; the rubberizing assembly comprises a first driving part and a picking part, the driving end of the first driving part is connected with the picking part, the first driving part is used for driving the picking part to transversely move and ascend and descend so that the picking part can sequentially move to the material taking station, the rubberizing station and the rubberizing station, and the picking part is used for picking or releasing a label; and the gluing assembly is used for gluing the mounting surfaces of the labels picked up by the pick-up piece on the gluing station. According to the automatic gluing and labeling integrated device for the egg boxes, through cooperation of the conveying assembly, the bearing assembly, the gluing assembly and the gluing assembly, automatic labeling of the egg boxes is achieved, and the working efficiency is improved.

This disclosure provides a method and apparatus for drawing a vector map of an accident scene. The method includes: performing object recognition on a global top-view of a target accident scene to determine at least one object included in the target accident scene; symbolizing the at least one object in the global top-view to obtain at least one object symbol; determining at least one reference element based on the distribution of the at least one object in the global top-view; determining annotation information for at least one key accident point in the global top-view based on the at least one reference element; and obtaining a symbolized vector map of the scene with annotation information based on the annotation information of the at least one key accident point and the at least one object symbol. This disclosure enables the automatic drawing of a standard vector map of a target accident scene while automatically annotating the details of the accident scene.

The utility model relates to the technical field of labeling instruments, in particular to a blood sampling test tube labeling machine which comprises a fixing disc, a labeling device, a fixing device, a storage device and a taking device, the labeling device is installed on the fixing disc, and the labeling device is used for fixing blood sampling test tubes and labeling the test tubes at the same time; the fixing device is mounted on one side of the labeling device, and is used for fixing the test tubes so as to be matched with the labeling device to complete labeling; the labeling device is used for labeling blood collection test tubes, the storage device is installed on one side of the labeling device and used for storing the blood collection test tubes, and the taking device is installed above the storage device and used for moving the blood collection test tubes into the labeling device to complete labeling work.

This disclosure provides a labeling device for electronic devices, comprising: a printing mechanism for printing labels and outputting the printed labels after separating them from release paper; a label receiving mechanism for receiving the labels after separation from the release paper; a conveying mechanism for conveying electronic devices to be labeled; and a labeling head assembly for transferring the labels from the label receiving mechanism to the corresponding positions on the electronic devices.

This application discloses an automatic image annotation method, apparatus, device, and storage medium. The method includes: annotating an original screenshot and saving the annotation information and image resolution of the original screenshot, the annotation information including annotation coordinate positions; recognizing the text information annotated in the original screenshot, the text information including text content and text coordinate positions; obtaining the image resolution of a new screenshot and recognizing the text content of the new screenshot to obtain the text information of the new screenshot; calculating a scaling ratio based on the image resolutions of the original and new screenshots, and obtaining the number of occurrences of the text content corresponding to the annotation coordinate positions in the original screenshot in the new screenshot by comparing the text content in the original screenshot with the text content in the new screenshot; obtaining the annotation information of the new screenshot based on the number of occurrences and the scaling ratio, and annotating the new screenshot based on the annotation information of the new screenshot. This improves the technical problem of low annotation efficiency in existing technologies that rely on manual image annotation.

This application belongs to the field of intelligent input technology, specifically relating to a method, apparatus, and computer-readable storage medium for labeling adjacent key mis-touch information. The method includes: acquiring log information generated by a user inputting information via a keyboard; parsing the log information to obtain target information corresponding to the same input cycle, wherein the target information includes typed information and on-screen information; acquiring the information type corresponding to the typed information and determining target rules based on the information type; performing adjacent key mis-touch analysis on the target information according to the target rules, and labeling adjacent key mis-touch information based on the analysis results, so as to train an adjacent key mis-touch recognition model based on the labeled adjacent key mis-touch information. This application can achieve automated labeling of adjacent key mis-touch information, shortening the information labeling time, reducing mis-labeling caused by manual labeling, accelerating the iteration speed of the adjacent key mis-touch recognition model, and improving the model's accuracy and input accuracy.