Digital image generation typesetting system and method
A digital image and image technology, which is applied in the field of digital image generation and typesetting system, can solve the problems of inability to digital image typesetting and digital image typesetting effect, etc., and achieve the effects of simple operation, perfect production and simple operation.
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Embodiment 1
[0052] The digital image generating typesetting system of the present embodiment, such as figure 1 shown, including:
[0053] The cloud database 3 is used to establish a data transmission network to provide to each digital network for data interaction and store digital image data;
[0054] User login system 2, used for user login system control;
[0055]The main control module 1 is the general control terminal of the system, which is used to analyze the user population to classify users, and execute commands for execution by lower-level modules;
[0056] An image acquisition unit 4, configured to acquire the digital image provided, and confirm the utility level of the digital image by using a web crawler;
[0057] A retrieval unit 5, configured to retrieve the usage frequency of the user's current digital image;
[0058] The classification unit 6 is used to set the typesetting threshold with reference to the classified image element data;
[0059] An evaluation module 7, c...
Embodiment 2
[0081] At the specific implementation level, on the basis of Embodiment 1, this embodiment refers to figure 1 As shown, the daily protection system for stroke patients in Embodiment 1 is further specifically described, and the digital image generation and typesetting method is as follows: figure 2 shown, including the following steps:
[0082] Step101: Use web crawler tracking to judge the user's usage frequency according to the practicality of digital images;
[0083] Step102: Classify users with reference to user preferences and user usage frequency;
[0084] Step103: Acquire at least one digital image according to the classification group, and use the deep neural network discriminator to score the image;
[0085] Step104: Obtain image data constituting the target image, and form at least one image layer according to the image data;
[0086] Step105: Carry out image element category classification according to at least one image layer;
[0087] Step106: Analyze the gene...
Embodiment 3
[0092] At the specific implementation level, on the basis of Embodiment 2, this embodiment refers to figure 2 As shown in embodiment 2, the daily preventive method for stroke patients is further specified, as figure 2 as shown,
[0093]The user classification of described step Step102 comprises the following steps:
[0094] Acquire user information, form image data of the target image, and determine at least one classification layer group according to the image data;
[0095] An initial typesetting image state is obtained according to the initial state of the classification layer group, and the initial typesetting image state is input to the deep neural network discriminator for image scoring.
[0096] like figure 2 As shown, in Step 104, the sample image is collected according to the frequency of use of the user, and the standard score of the sample image is obtained, which is used as the score label of the sample image to form the image layer.
[0097] like figure 2...
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