Digital image generation typesetting system and method
A digital image and image technology, applied in the field of digital image generation typesetting system, can solve the problems such as inability to digital image typesetting, digital image typesetting effect, etc., and achieve the effect of simple operation, perfect production, and high fidelity
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Embodiment 1
[0052] The digital image generation typesetting system of this embodiment, such as figure 1 shown, including:
[0053] The cloud database 3 is used to establish a data transmission network to provide data exchange to various digital networks, and to store digital image data;
[0054] User login system 2, used for user login system control use;
[0055]The main control module 1 is the total control terminal of the system, which is used to analyze user populations for user classification, and execute commands for lower-level modules to execute;
[0056] An image acquisition unit 4, configured to acquire the provided digital image, and use a web crawler to confirm the practical level of the digital image;
[0057] a retrieval unit 5 for retrieving the frequency of use of the current digital image of the user;
[0058] Classification unit 6, for setting a typesetting threshold with reference to the classified image element data;
[0059] The evaluation module 7 is used for ana...
Embodiment 2
[0081] At the specific implementation level, on the basis of Embodiment 1, this embodiment will further describe in detail, the digital image generation and typesetting method, such as figure 2 shown, including the following steps:
[0082] Step101: Use web crawler tracking to judge the user's frequency of use according to the practicability of digital images;
[0083] Step102: Classify users with reference to user preferences and user usage frequency;
[0084] Step103: Obtain at least one digital image according to the classification group, and use the deep neural network discriminator to score the image;
[0085] Step104: Acquire image data constituting the target image, and form at least one image layer according to the image data;
[0086] Step105: Classify image element categories according to at least one image layer;
[0087] Step 106: Analyze the generated image categories, and automatically make typesetting for the materials provided by the user.
[0088] When us...
Embodiment 3
[0092] At the specific implementation level, on the basis of Embodiment 2, this embodiment is further described in detail, such as figure 2 shown,
[0093] The user classification in Step 102 includes the following steps:
[0094]obtaining user information, forming image data of the target image, and determining at least one classification layer group according to the image data;
[0095] The initial layout image state is obtained according to the initial state of the classification layer group, and the initial layout image state is input to the deep neural network discriminator for image scoring.
[0096] like figure 2 As shown, in Step 104, a sample image is collected according to the usage frequency of the user, and a standard score of the sample image is obtained, which is used as the score label of the sample image to constitute the image layer.
[0097] like figure 2 As shown, in Step 105, a test image is acquired through the image layer, and the typesetting layer...
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