Disclosed is a transparency detecting method based on machine vision. The transparency detecting method includes 1) operating a Secchi disk to start the water transparency measurement, and turning on the camera for shooting; 2). determining a critical position of the Secchi disk; 3) identifying a water ruler and calculating a reading of the water ruler; 4) outputting and displaying the calculated reading.

A method for training a text positioning model includes: obtaining a sample image, where the sample image contains a sample text to be positioned and a text marking box for the sample text; inputting the sample image into a text positioning model to be trained to position the sample text, and outputting a prediction text box for the sample image; obtaining a sample prior anchor box corresponding to the sample image; and adjusting model parameters of the text positioning model based on the sample prior anchor box, the text marking box and the prediction text box, and continuing training the adjusted text positioning model based on a next sample image until model training is completed, to generate a target text positioning model.

A computer-implemented method for assisted parking, an electronic device, and a storage medium are provided. The method for assisted parking includes: obtaining a set of images around a vehicle; determining environment information for the vehicle based on the set of images; obtaining location information associated with a target parking location according to the environment information; and sending the location information to provide such to a user terminal.

A computer-implemented method for assisted parking, an electronic device, and a storage medium are provided. The method for assisted parking includes: obtaining a set of images around a vehicle; determining environment information for the vehicle based on the set of images; obtaining location information associated with a target parking location according to the environment information; and sending the location information to provide such to a user terminal.

The present disclosure relates to a font detection method using a neural network. The font detection method using the neural network according to the present disclosure includes receiving a target text image including a text; resizing a horizontal or vertical size to a reference input size according to an aspect ratio of the input target text image; and inputting the resized target text image into a trained neural network and outputting a font of the text included in the text image, and the neural network may be trained with a unit image extracted as a unit region of the reference input size from a training image generated by synthesizing a background with the text. According to the present disclosure, fonts according to various usage examples may be effectively detected.

The present disclosure provides a training method and apparatus for a document processing model, a device, a storage medium and a program, which relate to the field of artificial intelligence, and in particular, to technologies such as deep learning, natural language processing and text recognition. The specific implementation is: acquiring a first sample document; determining element features of a plurality of document elements in the first sample document and positions corresponding to M position types of each document element according to the first sample document; where the document element corresponds to a character or a document area in the first sample document; and performing training on a basic model according to the element features of the plurality of document elements and the positions corresponding to the M position types of each document element to obtain the document processing model.

An identification card authenticity determining method based on deep learning according to the disclosure for automatically checking authenticity of an identification card includes: inputting identification card data to a feature information extraction model to extract pieces of feature information, expressing an indicator for checking authenticity of the identification card, from the identification card data; inputting the extracted pieces of feature information to a classification model to determine authenticity of the identification card; and when it is determined that the identification card is falsified, extracting a class activation map, where a falsification region of the identification card data is activated, from the pieces of feature information.

An information processing apparatus includes a processor configured to extract a mark specified in advance from an image of a document; and acquire a character string by performing character recognition on a region located in a particular direction with respect to a position of the mark, the direction being associated in advance with the mark.

A method for processing text in an image, an electronic device and a storage medium are provided in the present application. A user operation instruction carrying location information is acquired, and the location information is configured to indicate an operation location of a user's operation performed on the image. Target text corresponding to the location information in the image is identified, according to the user operation instruction. A display element is displayed overlying on the image, and the target text is displayed on the display element.

A verification system or method for detecting whether a CPA device is in a pre-lock position or in a full-lock position relative to the housing based on a scan system’s detection that a portion of a predetermined word or character on the CPA device and another portion of the predetermined word or character are separated from each other or joined together to form the predetermined word or character. The CPA device is fully engaged or in full-lock position or status with the housing when the scan system has recognized or determined that the portion of the predetermined word or character on the CPA device and the another portion of the predetermined word or character on the housing within a scan window are joined together to form the complete or full predetermined word or character.