When Fang Lin bought a new smart phone, he found out the phone app gave him a special social network with the immortals. In a dog eat dog world, Lin is taking a stairway to heaven with this special social network.
PZcolo Sep 9, 2019 3 Similar to My amazing We chat and almost as bad. The story is a mess, stuff happen randomly and there are many things that just make no sense and lots of instant gratification crap with no effort whatsoever, skills, phisical proficiency, knowledge, it just instantly happens, with him not needing to study, train, read, work, meditate or whatever. MC is an idiot on many levels, for example, who in his right mind would tell a woman that he wants to get rid off, that you can forsee the future with his phone and further prove it to her? is he looking to get sacked?And who the hell would just go ahead and drink a weird liquid he finds buried somewhere? Oh it's from this mistery chat I know nothing about, let's drink it yeah right. Comedy is also quite bad, it's the humor of the ridiculous, that kind off comedy but not very well done, didn't even laugh once in 30 ch., definitely not my thing. Last, the drawings are somewhat good, kinda simple with not many details but not bad. Overall, not very interesting nor funny, I'd recommend anyone into this theme to read Cultivation chatroom, it's pretty much the same thing but it's done with less bad humor, art is better and the MC and story take themselves more seriously.
MonarqueCeleste Aug 8, 2020 1 This is such an amazing concept but thrown into the pit because of the author. Imagine having an app that gives you the news of the next day beforehand. You see how amazing this is and how you could develop a good plot. Something like past life regressor with him creating a company and slowly taking over the country or making his village prosper. But because its Chinese and I hate say it but they (most authors) have a weird way of doing their world building. It will either be something with plenty of canon fodder villains or a harem or a combination of both. Here we have the mc who randomly tells a woman he has the capability of telling the future, he sometimes acts arrogant, meddles in any and every situation saving and collecting harem girls. All of this under the guise of networking but you clearly see the stupid blushes and nosebleed. All in all manhua have mcs with the brain of 12 yo horny boys which is the huge difference between them and manwha.
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Manthika Oct 18, 2019 2 In my opinion, even worse than 'my amazing wechat' with inconsistent art, a confusing intro, and nothing going for it, I wouldn't recommend it to absolutely anyone.I’ve always been amazed by vivid animations, especially Manga and their bold looks and strokes. Wouldn’t it be awesome to be able to draw a few ourselves, to experience the thrill of creating them with the help of a self-developed neural network?!
The best way to master a skill is to practice and improvise it until you’re satisfied with yourself and your efforts. For a machine or a neural network, the best output it can generate is the one that matches human-generated outputs—or even fool a human to believe that a human
Generative adversarial networks have lately been a hot topic in deep learning. Introduced by Ian Goodfellow et al., they have the ability to generate outputs from scratch.
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In generative adversarial networks, two networks train and compete against each other, resulting in mutual improvisation. The generator misleads the discriminator by creating compelling fake inputs and tries to fool the discriminator into thinking of these as real inputs . The discriminator tells if an input is real or fake.
The reason for combining both networks is that there is no feedback on the generator’s outputs. The ONLY guide is if the discriminator accepts the generator’s output.
You can say that they are rivals destined for each other. The main character is the generator who strives to be better and better to make our purpose realized by learning from the fight with its rival, the discriminator.
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The dataset for anime faces can be generated by curling through various manga websites and downloading images, cropping faces out of them, and resizing them to a standard size. Given below is the link for A Python code depicting the same:
The generator consists of convolution transpose layers followed by batch normlization and a leaky ReLU activation function for upsampling. We’ll use a strides parameter in the convolution layer. This is done to avoid unstable training. Leaky ReLUs are one attempt to fix the “dying ReLU” problem. Instead of the function being zero when x < 0, a leaky ReLU will instead have a small negative slope (of 0.01, or so).
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To conduct back propagation for the generator, in order to keep a check on it’s outputs, we compile a network in Keras—generator followed by discriminator.
In this network, the input is the random noise for the generator, and the output would is the generator’s output fed to the discriminator, keeping the discriminator’s weights frozen to avoid the adversarial collapse. Sounds cool, right? Look it up!
I trained this code on my Acer-Predator helios 300, which took almost half an hour for 10, 000 steps and around 32, 000 images, with an Nvidia GTX GeForce 1050Ti GPU.
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In terms of improving the model, I think training for a longer duration and on a bigger dataset would improve the results further (Some of the faces were scary weird! Not the conventional Manga, I must say :D)
But there is still quite a bit of room for improvement with better training, models, and dataset. Our model cannot make a human wonder if these faces generated were real of fake; even so, it does an appreciably good job of generating manga-style images. Go ahead and try this with complete manga postures, too.
Here is the link to my GitHub repository. Feel free to have a look, clone, or improvise it. All kinds of suggestions and criticisms are welcome. Please upvote if you like the content and implementation.
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I hope you enjoyed my first article on generative adversarial networks for manga-face generation! Don’t forget to hit the upvote and follow button!
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