two-way colorization method for animation images based on a U-shaped periodic consistent confrontation network
A colorization and network technology, applied in the field of image processing, can solve problems such as image quality loss, compositional imbalance, and image data difficulties, and achieve the effects of improving efficiency, reducing workload, and strengthening generalization capabilities
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Embodiment 1
[0050] refer to Figure 1-Figure 4 , Embodiment 1 of the present invention relates to a two-way colorization method for animation images based on a U-shaped periodical consistent confrontation network, specifically as follows:
[0051] Step 1. Collect data: use crawlers to obtain high-definition full-color animation illustration images and black-and-white line draft images;
[0052] Step 2, setting the pixels of the animation illustration image to a uniform size, such as adjusting the pixels to 256×256, and putting it into a database to construct a training data set and a testing data set;
[0053] Step 3. Construct a U-shaped periodic consistent deep learning confrontation network, use the training data set obtained in step 2 to cyclically train the U-shaped periodic consistent deep learning confrontation network, and use the test data set to verify the performance of the U-shaped periodic consistent deep learning confrontation network;
[0054] Step 4. Input the test image in...
Embodiment 2
[0056] refer to Figure 1-Figure 4 , Embodiment 2 of the present invention relates to a two-way colorization method for animation images based on a U-shaped periodical consistent confrontation network. On the basis of the above-mentioned Embodiment 1, Embodiment 2 of the present invention is described in detail as follows:
[0057] The U-shaped periodic consistent deep learning confrontation network includes a generator G, a generator F, and a discriminant network D X and discriminative network D Y ; Among them, the generator G generates the input black-and-white line draft image into a full-color image, the generator F generates the full-color image into a black-and-white line draft image, and the discriminant network D X Judging whether the input black and white line draft image conforms to the distribution of the real black and white line draft image, the discriminant network D Y Determine whether the input full-color image conforms to the distribution of real full-color ...
Embodiment 3
[0059] refer to Figure 1-Figure 4 , Embodiment 3 of the present invention relates to a two-way colorization method for animation images based on a U-shaped periodical consistent confrontation network. On the basis of Embodiment 1 and / or Embodiment 2 above, Embodiment 3 of the present invention is described in detail as follows:
[0060] Improve the generator G, generator F, and discriminant network D through the method of U-shaped cycle consistent cycle training X and discriminative network D Y ability; generally speaking, the method of loop training in step 3, that is, by constructing generator G, generator F and discriminant network D Y The sub-recurrent network of G, training generator G and discriminative network D Y Ability; by constructing generator F, generator G and discriminant network D X The sub-recurrent network of , training generator F and discriminative network D X Ability.
[0061] In detail, the specific steps of the method for loop training in step 3 ar...
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