Neural networks for drawing: how to become an artist in two clicks

Neural networks for drawing are, most often, online services that allow you to create and process images. They work based on machine learning algorithms. With their help, you can generate simple drawings and real works of art.

The recipe is simple – choose the neural network you like, go to the service page, and follow the instructions. Almost every application has a free trial period with certain limitations.

The principle of operation of the neural network for drawing

A neural network is a term that has appeared within the biology framework. The neural network is arranged in much the same way as the human brain: certain connections are established between neurons. Information is processed and issued by neurons and then transmitted by connections.

And yet there is a significant difference: the brain’s neurons in the learning process are automatically involved in the formation of new stable connections. A computer network cannot learn on its own. Its neurons receive, process, and issue information on command without forming new connections.

For the neural network to work, you need to spend time training it. This process is similar to explaining a new baby. First, we show the baby a picture of a cow and name it, then a cat, a dog, a camel … The next step is to ask the child to show a picture of a dog. Remembering the names, the child will point to the desired image.

Neural networks work similarly. A complex internal process accompanies information processing. However, the very principle by which training takes place and the subsequent execution of commands will be the same.

There is a popular myth that a neural network can learn itself. For example, in the Marvel universe, the character Ultron gained access to information, went online, and became a powerful intellect. This leads him to acquire a physical shell and tremendous strength. Ultron’s ability to self-study is a work of fiction. Today, people have engaged in training neural networks. And they also write work algorithms.

Each neural network is endowed with its task and its algorithm. For example, the ability to search by image on Google is the work of a neural network. The user uploads an image and clicks the “find” button. The neural network receives a command: “find the same or everything that looks like it.” Google already has a database of images in its memory.

The neural network takes yours and compares it with its entire base. Everything that seemed similar to the system shows the user. For the neural network to run the image through the base and draw parallels, a person taught it to do this in advance.

In the DALL-E network, images are generated using a verbal description from known elements. The user writes: “cowboy flies on a rocket, pencil drawing.” Next, the network searches for suitable images, connect them, formats them to match the specified style, and produces the final image.

So far, the work of neural networks can be called imperfect: the picture sometimes turns out to be meaningless or frightening. And the search for similar images leads to something very far from the source. The reason for this is the complexity of training the neural network. This is good news for artists: today, neural networks cannot replace a person in creating drawings. And yet, if you work with images, it will be useful to understand how to use neural networks for drawing.

Top 7 Neural Networks for Drawing

GauGAN

GauGAN is a generative adversarial neural network. It was developed by NVIDIA, named after the French painter Paul Gauguin and is one of the most popular neural networks for drawing.

Fans of strange and funny pictures in Paint actively use this interactive application. The main tools of creativity here are the well-known “Brush,” “Pencil,” and “Fill.” The left side of the screen is dedicated to creating a sketch of a future masterpiece, and the right side is for parallel translation of your “doodles” into a real landscape.

NVIDIA’s description says, “Users can even upload their filters to overlay on their masterpieces or upload custom landscape images as the basis for paintings.”

GauGAN works based on a special normalization technique that improves data quality. Handwritten drawings are perceived by the neural network and generated into photorealistic images. Pictures can be generated in different styles: multimodal image synthesis makes this possible.

Advantages of GauGAN:

• easy and fast creation of landscapes;
• photorealistic drawings.

Cons of GauGAN:

• The network is hard to learn.

Disco Diffusion

Disco Diffusion is a neural network developed by Google that generates unexpected drawings from textual descriptions. Sometimes the results are quite abstract, but some images look amazing.

This neural network is equipped with a simple interface: in front of you is a working notebook containing a query field. You can describe the future image as you like: in one word or a whole sentence. You can also use the settings, choosing various styles and variations. One drawing is created for quite a long time – from 20 to 90 minutes.

Pros of Disco Diffusion:

• high-quality rendering of landscapes;
• an exact accounting of the request.

Cons of Disco Diffusion:

• all created images are automatically uploaded to Google Drive, taking up a lot of space there;
• long generation of images in comparison with the work of other neural networks.

Different Dimension Me

Different Dimension Me is a website with a neural network that generates anime versions of uploaded pictures. The site has been in existence since November 2022. Built on the Tencent QQ platform, the site quickly became popular, with Chinese social media quickly flooding with anime pictures created from photos of users and their idols.

Different Dimension Me allows users to set different settings, select styles and create unique images from standard sources. User reviews show this is the best neural network for drawing anime-style paintings.

An unconfirmed hypothesis is that Different Dimension Me works using the Stable Diffusion AI model, namely its img2img sampling script.

Pros of Different Dimension Me:

• this neural network for drawing is available online;
• creating original images in anime style.

Cons of Different Dimension Me:

• Chinese language-based interface.

dreamlike

Dreamlike is a shareware drawing neural network powered by the Stable Diffusion AI artist. The user creates a text description, and the network creates an image as a portrait, landscape, or abstraction.

This neural network uses a shareware subscription model. You register and then pay for each image generation with “credits.” The cost of one picture depends on the settings that you set. On average, you give away from 5 to 10 credits per generation. The site contains various options for selecting the aspect ratio or style you need.

Getting loans is available both for money and for free. To generate images for free, you can:

• visit the site daily and receive one credit per day;
• participate in competitions on the platform, winning up to 3000 credits.

You can get up to 100 units for free.

Dreamlike pros:

• this is a free neural network for drawing by description;
• generation of six variants of the image at the same time;
• correction of faces in portraits (unfortunately, this feature is not yet stable);
• settings with a user-friendly interface.

Dreamlike cons:

• The free mode implies a large number of restrictions (for example, the NightCafe neural network has a much more loyal trial period);
• Improving images sometimes backfires.

night cafe

NightCafe is a neural network website operating on a shareware basis. Mostly, he is engaged in generating abstract or portrait images. NightCafe is not a specialized neural network for drawing portraits but is often used for this.

NightCafe allows you to create pictures with various preset effects: oil painting, watercolor, graphics, and more. NightCafe creates ready-made images within minutes. Using the neural network is free, but there are certain conditions: by completing tasks daily, you get credits for which you “buy” the right to generate drawings.

This neural network is useful for creating atmospheric abstract images. You can experiment with different color palettes.

Pros of NightCafe:

• This is a neural network for drawing full-fledged pictures;
• You can generate free images;
• Creation of high-quality landscapes, surreal paintings, and space images.

Cons of NightCafe:

• slight vagueness and lack of clarity of images;
• Settings and options for generating images need to be more precise.

AutoDraw

This neural network is close to a graphics editor. Google has created the ability to generate quality illustrations for those who do not have drawing skills. This service became known in the context of the AI ​​Experiments project launched in November 2016.

So, here is what is available within the service:

• choice of three image formats – one horizontal and two vertical;
• freehand drawing (similar to the work of a pencil in Paint);
• creating shapes – circles, triangles, quadrilaterals;
• Writing text (there are 14 fonts to choose from, and the size of the letters can be from 8 to 96);
• filling shapes with the selected color, the ability to change the color of the background, picture, or their elements;
• Moving and scaling objects in the image.

The service is best known for the function of creating a neat, beautiful drawing from the original scribbles.

The user casually draws a rough outline of the object, and the web shows small image icons above the drawing. Next, select one and click on it. After that, the former doodles turn into full-fledged drawings.

The neural network allows you to make simple drawings automatically and fast. If your social networks are minimalist, the neural network can illustrate your posts in a few seconds.

Of course, sometimes AutoDraw peculiarly perceives doodles. If it is impossible to determine the image’s content, the proposed illustrations may be unexpected and not at all suitable for the request.

Looka

As part of this service, you can generate a logo based on information about the proposed company. This is possible thanks to Google’s TensorFlow algorithms.

Looka is not just a neural network for drawing by words. To get several variants of logos, you fully train the neural network, telling it about your company, its field of activity, and its mission. What will help to get the actual logo:

• indication of the scope of activity;
• an indication of five or more logos that you like from those offered by the system;
• choice of two sets of colors;
• choice of three specific colors for the future logo;
• an indication of the name of the company, its slogan, or unique selling proposition;
• selection of a maximum of five characters that characterize the company.

Next, considering your provided information and real-life logos, the neural network generates options.

As a rule, the logos created by the neural network differ from the references and are perceived as outdated. But the value is in the ideas the system provides. These ideas are used by logo designers working with the company.

An example of drawing according to the description by the Midjourney neural network

In 2022, the popularity of this trendy neural network has become all-encompassing! DFT user CR0C0D1L gives the best description: “Artists – oops with this generation level.” It sounds harsh, but very close to the truth: the art is simply unrealistic.

 Each user has available free 25 conditional gpu-minutes of Midjourney monthly. During this time, approximately 25 images can be generated.

By paying $10, you get 200 minutes of network operation (about two hundred arts) and a dedicated channel instead of a public one. After buying a subscription for $30, you can no longer keep track of the time: 15 gpu-hours to generate images do not end: you can continue to work, just a little slower.

Midjourney users from all over the world leave rave reviews, calling Midjourney the best neural network for drawing, so Russian users are looking for solutions, but so far, only “crutches” have been found.

So how does Midjourney work?

Let’s take a quick look at how to register and get started.

1. Open Discord and go to the network channel.
2. Subscribe to one of the #newbies channels. AvelNobel – one of the users of Pikabu – called it the need to “break through” due to the high load. Please wait or restart Discord if necessary.
3. Enter the chat and write a request to /imagine.
4. Next, the system offers to add the promt option to the request. Accept the offer. Delete the request and print /imagine again in case of an accidental failure.
5. Enter a description in English. Let’s say your description is dog or cow. The final request will look like this: /imagineprompt:dog or /imagineprompt:cow, respectively.

A neural network cannot become a full-fledged replacement for a person. Still, on this basis, excellent assistants are created for artists, designers, marketers, affiliates, and other graphics-related people.

Drawing with a neural network can be fun and help your work. Services with artificial intelligence at their core already perform many complex tasks. Convenient tools speed up and simplify the routine, as well as search for new ideas and creative approaches.