Joke Collection Website - Cold jokes - Detailed explanation of the underlying logic of Ai painting mats
Detailed explanation of the underlying logic of Ai painting mats
Detailed explanation of the underlying logic of the pad map
Let’s talk about the pad map first
Sometimes when you are performing the pad map operation, you will find that after the pad map is actually It is not easy to generate the content you want. In fact, the main reason is that there are many styles when padding pictures. You may have selected various pictures to pad, and then the generated style does not meet your expectations. Let’s take a preliminary look at the picture below. Principle of Cushion Picture
Based on a basic principle of the above picture, we start a practical explanation of the principle of Cushion Picture. For example, if we want to generate clown makeup for girls, how to generate it through Cushion Picture, first enter the descriptor to confirm Output content
Start padding!
After confirming that the content is correct, we start to add a picture of a clown for generation. We can see that it is already a basic, somewhat prototype of a clown. But it still lacks the makeup effect, which means that we don’t have enough cushion pictures (if the generated content generates pictures of real people, it is also recommended to choose real people for the cushion pictures)
Increase the stable style of the cushion pictures
At this time, we can try to pad two pictures to generate content. Now you can see that we are getting closer to the finished product. Then the basic padding operation has been completed. At this time, we only need to do it on the keywords. By optimizing, you can basically create the content you want
If you want to generate content that meets your expectations, remember to choose pictures of the same style
Optimize keywords< /p>
Then we can start optimizing keywords and gradually reach the content that is most suitable for us!
A little expansion
First of all, let’s talk about the generation of the medal map. method, and then let’s see what the results will be if we use different styles of content generation~
Descriptor:
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