Trending November 2023 # How To Use Stable Diffusion: The Best Stable Diffusion Gui For Windows. # Suggested December 2023 # Top 20 Popular

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Unlock the full potential of Stable Diffusion with a brand new, easy-to-use GUI (Graphical User Interface) for local implementation. Say goodbye to confusing and time-consuming manual installation steps and learn how to use Stable Diffusion with a user-friendly graphical user interface on Windows in this informative article.

Related: How to use Midjourney – A collection of guides.

Stable Diffusion is a deep-learning text-to-image AI (Artificial intelligence) that was introduced to the world in 2023. Primarily it is used to generate images using text descriptions and prompts, but can also be applied to other tasks such as inpainting, outpainting, and image-to-image translations with text prompts.

It is a latent diffusion model, which is a type of deep generative neural network. Surprisingly the code and model weights of Stable Diffusion are publicly available and can be run on most consumer hardware with a decent GPU and at least 8 GB of VRAM. This is entirely unique to Stable Diffusion as DALL-E and Midjourney both require cloud services. They are also locked behind paywalls for the most part.

Up until recently the only issue with Stable Diffusion has been its complicated local setup process. This requires tons of manual work and setup and for most people ends up being far to complicated for them to bother with. Thankfully a small team of developers have got together and released a GUI version of Stable Diffusion which is essentially “The Best Stable Diffusion GUI” currently available.

Top-rated Stable Diffusion GUI: Generate High-Quality Images with Ease.

Introducing the NMKD Stable Diffusion GUI! This tool is a brand new, user-friendly project that simplifies the process of getting Stable Diffusion working on a Windows PC. It comes in a single package that includes all the necessary dependencies. Which makes it a plug-and-play option.

The GUI is designed to be highly customizable, allowing users to create their own Stable Diffusion models and VAE models, as well as support for inpainting, HuggingFace concepts, upscaling, face restoration, and it is actively developed Something else that is interesting is that NMKD also AMD GPUs, although this feature is still experimental.

The features of the NMKD Stable Diffusion GUI include:

All dependencies included,

Support for text-to-image and image-to-image (image+text prompt)

Prompting features such as Attention/Emphasis, negative prompt

Ability to run multiple prompts at once

Built-in image viewer that displays information about generated images

Built-in upscaling (RealESRGAN) and face restoration (CodeFormer or GFPGAN)

Prompt Queue and Prompt History

Option to create seamless (tileable) images, e.g. for game textures

Support for loading custom concepts (Textual Inversion)

A variety of UX features

Performance that is as fast as your GPU (1.7 seconds per image on RTX 4090, 2.6 on RTX 3090)

Built-in safety measures that scan downloaded models for malware

So how do you use the NMKD Stable Diffusion GUI?

To start using the NMKD SD GUI, you’ll first need to download it. Which you can do using the link: Download NMKD Stable Diffusion GUI.

That’s all there is to it, now you can learn to use the interface to generate images. However, the most important thing you can do is learn how to utilize prompts to their maximum potential. Don’t be afraid to be really specific and detailed with prompts. If you want to really expand upon the results it’s a good idea to spend some time doing research in this area.

You're reading How To Use Stable Diffusion: The Best Stable Diffusion Gui For Windows.

4 Sites To Use Stable Diffusion Online

It’s one thing to know how to run Stable Diffusion on your computer to create AI generated images, but it’s another thing to have the hardware to run it. Luckily, if you don’t have the GPU power to rev up Stable Diffusion on your own computer, you can always use these sites to use Stable Diffusion right on your browser!

Tip: Check out these photo editors that use AI to enhance your images.

1. Prodia – Best for Prompt Practice

Pricing: Free / $4.99 (Pro) / $19.99 (Pro+)

Prodia might look basic, but it’s a reliable site that lets you generate images on the fly. It has everything you need to make an image from a prompt, then tweak your seed and prompt until you get the image you want. The best thing about this site is that you can generate images with a variety of Stable Diffusion models for free and without limit – making it a good tool to practice prompt writing.

Pros

Fast generations even while using the free tier

Has great anime models

Cons

Does not let you upload reference photos

Limited to up to only 30 generation steps

2. Dream Studio – Has a Little Bit of Everything

Pricing: $1 per 100 credits, minimum of $10

Pros

Lets you upload a reference photo

Free 100 credits

Lets you generate up to 150 steps

Cons

Has limited selection of AI models

Image editing is not intuitive

Tip: If what you need is a vector image, you can use these graphics editors to easily create vector images.

3. Hotpot – Best at Editing

Pricing: Free / $50 per month (5000 credits per month) / $500 per year (5000 credits per month) / $500 per year (5000 credits per month)

Unlike most of the other sites that run Stable Diffusion in this list, Hotpot focuses on pre-built AI editing tools that you can use to upscale, erase, or colorize photos. You can also use it to generate images based on reference photos. This way, you can finally make all the consistent cover images for your Evil Mario AI fanfic that hopefully doesn’t stray too far from the source material.

Pros

Lets you generate 500 images in one go

Pick a style without having to worry about models

Cons

Editor has no undo function

Does not let you pick models at all

4. Catbird – Best Selection of AI Models

Pricing: Free / $8 per month (Premium) / $24 per month (Pro)

If you thought Prodia had a lot of models already, take a look at Catbird. It’s got at least 58 models, all divided into 6 genres to give you an idea over what they do. Plus, it lets you save the prompt and settings you used for generating an image you’ve saved into your account.

Pros

Lets you generate unlimited times for free

Chill mode lets you save on credit

Cons

Mixing multiple models is almost impossible to use at free tier

Does not let you upload reference photos

Frequently Asked Questions Do I really need to buy a GPU to run Stable Diffusion?

The more important thing here is the VRAM. If your GPU doesn’t have enough VRAM, expect a terribly slow generation with Stable Diffusion.

Why don’t web apps that use Stable Diffusion allow importing of models?

The main reason why they don’t lets you upload custom models is that these models can get pretty big. A single model alone can take tens or hundreds of gigabytes of storage. Now imagine thousands of people logging in to generate a single image from some obscure model – that’s going to take up bandwidth and disk space pretty quick.

Why does Catbird take so long to generate images?

The first reason is that you might be mixing too many models. Try to reduce these, especially when you’re using it at Chill Mode. The other is that there just might be too many users generating things at the same time, so it might be best to take another go at another time.

What diffusion model should I use for generating anime characters on Prodia?

On Prodia, you can use Anything V3, V4.5, and V5 to generate anime-style characters. Of these, Anything V5 has the best anime-looking style with crisp colors and contrast. Anything V3, on the other hand, has a more dreamy characteristic. You’ll see more of that dreaminess on Anything V4.5.

Terenz Jomar Dela Cruz

Terenz is a hobbyist roboticist trying to build the most awesome robot the world has ever seen. He could have done that already if he wasn’t so busy burning through LEDs as a second hobby.

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How To Use Dreambooth To Put Anything In Stable Diffusion (Colab Notebook)

Dreambooth is a way to put anything — your loved one, your dog, your favorite toy — into a Stable Diffusion model. We will introduce what Dreambooth is, how it works, and how to perform the training.

This tutorial is aimed at people who have used Stable Diffusion but have not used Dreambooth before.

Do you know many custom models are trained using Dreambooth? After completing this tutorial, you will know how to make your own.

You will first learn about what Dreambooth is and how it works. But You can skip to the step-by-step guide if you are only interested in the training.

What is Dreambooth?

Published in 2023 by Google research team, Dreambooth is a technique to fine-tune diffusion models (like Stable Diffusion) by injecting a custom subject to the model.

Why does it call Dreambooth? According to the Google research team,

It’s like a photo booth, but once the subject is captured, it can be synthesized wherever your dreams take you.

Sounds great! But how well does it work? Below is an example in the research article. Using just 3 images of a particular dog (Let’s call her Devora) as input, the dreamboothed model can generate images of Devora in different context.

With as few as 3 training images, Dreambooth injects a custom subject to a diffusion model seamlessly.

How does Dreambooth work?

You may ask, why can’t you simply train the model with additional steps with those images? The issue is that doing so is known to cause catastrophic failure due to overfitting (since the dataset is quite small) and language drift.

Dreambooth resolves these problems by

Using a rare word for the new subject (Notice I used a rare name Devora for the dog) so that it does not have a lot of meaning in the model in the first place.

Prior preservation on class: In order to preserve the meaning of the class (dog in the above case), the model is fine-tuned in a way that the subject (Devora) is injected while the image generation of the class (dog) is preserved.

There’s another similar technique called textual inversion. The difference is that Dreambooth fine-tunes the whole model, while textual inversion injects a new word, instead of reusing a rare one, and fine-tunes only the text embedding part of the model.

What you need to train Dreambooth

You will need three things

A few custom images

An unique identifier

A class name

In the above example. The unique identifier is Devora. The class name is dog.

Then you will need to construct your instance prompt:

a photo of [unique identifier] [class name]

And a class prompt:

a photo of [class name]

In the above example, instance prompt is

a photo of Devora dog

Since Devora is a dog, the class prompt is

a photo of a dog

Now you understand what you need, let’s dive into the training!

Step-by-step guide

Get training images

As in any machine learning tasks, high-quality training data is the single most important factor to your success.

Take 3-10 picture of your custom subject. The picture should be taken from different angles.

The subject should also be in a variety of background so that the model can differentiate the subject against the background.

I will use this toy in the tutorial.

Images of the subject.

Resize your images

In order to use the images in training, you will first need to resize them to 512×512 pixels for training with v1 models.

BIRME is a convenient site for resizing images.

Drop your images to the BIRME page.

Adjust the canvas of each image so that it shows the subject adequately.

Make sure the width and height are both 512 px.

Press SAVE FILES to save the resized images to your computer.

Alternatively, you can download my resized images if you just want to go through the tutorial.

Training

I recommend using Google Colab for training because it saves you the trouble of setting up. The following notebook is modified from Shivam Shrirao’s repository but is made more user-friendly. Follow the repository’s instructions if you prefer other setups.

The whole training takes about 30 minutes. If you don’t use Google Colab much, you can probably complete the training without getting disconnected. Purchase some compute credits to avoid the frustration of getting disconnected. As of Dec 2023, $10 USD will get you 50 hours, so its not much of a cost.

The notebook will save the model to your Google Drive. Make sure you have at least 2GB if you choose fp16 (recommended) and 4GB if you don’t.

Get this Dreambooth Guide and open the Colab notebook.

You don’t need to change MODEL_NAME if you want to train from Stable Diffusion v1.5 model (Recommended).

Put in instance prompt and class prompt. For my images, I name my toy rabbit zwx so my instance prompt is “photo of zwx toy” and my class prompt is “photo of a toy”.

5. Grant permission to access Google Drive. Currently, there’s no easy way to download the model file except by saving it to Google Drive.

6. Press Choose Files to upload the resized images.

7. It should take about 30 minutes to complete the training. When it is done, you should see a few sample images generated from the new model.

8. Your custom model will be saved in your Google Drive, under the folder Dreambooth_model. Download the model checkpoint file and install it in your favorite GUI.

That’s it!

Testing the model

You can also use the second cell of the notebook to test using the model.

Using the prompt

oil painting of zwx in style of van gogh

with my newly trained model, I am happy with what I got:

Images from dreambooth model.

Using the model

You can use the model checkpoint file in AUTOMATIC1111 GUI. It is a free and full-featured GUI you can install on Windows, and Mac, or run on Google Colab.

If you have not used the GUI and the model file has been saved in your Google Drive, the easiest way is the Google Colab option. All you need to do is to put the path to the model in Google Drive to use it. See the step-by-step tutorial for more details.

How to train from a different model

You will need to change the MODEL_NAME and BRANCH.

Currently, the notebook only supports training half-precision v1 and v2 models. You can tell by looking at the model size. It should be about 2GB for v1 models.

You can find the model name and the branch name below on a Huggingface page. The page shown below is here.

Further readings

I recommend the following articles if you want to dive deeper into Dreambooth.

Making The Grade: Is Macos Really Less Stable Than It Used To Be?

I’ve been managing macOS in an enterprise environment since 2009, so I was around during the “stable” periods of Snow Leopard, as well as what others would call unstable periods. One of the common themes I’ve heard in my technology circles over the past few years is that macOS has become less stable. I manage 100s of Mac laptops at the moment, and I would estimate I’ve been responsible for 1,000+ devices over the past ten years. So, I think I’m qualified to discuss the current state of macOS stability.

Apple has been on the yearly upgrade cycle for macOS for a few years now, so it feels like by the time we get the X.4 revision of a new version of macOS, we are getting ready to kick off a summer of running betas (for IT to prepare for compatibility) and then kick off a fall season of updates and 1.0 bugs.

What’s the current state of macOS stability?

While I don’t have data to quantify it internally, I do know that I spend a lot less time on laptop support than I used to. A lot of my time is spent managing SaaS products instead. Some of it could be that our users are savvier than they used to be, but I generally think macOS is as stable today as it was back in the Snow Leopard days. I know that is not the common perception, though. If you stop and think about how our technology world was in the “stable” days of macOS, there was no iPad, no iCloud, no iMessage, no iCloud Photos, no Apple Music, and no Apple Watch. We had an iPhone, a laptop, and we used a cable to sync them together. Our world was a lot less in flux. Now, we’ve got 4K videos we are syncing over iCloud Photos while countless GIFs transfer over iMessage. We are more complex, and that creates a lot of opportunities for things to be out of sync.

In my opinion, it’s not that the stability of macOS has changed, but rather that we expect so much more from our software than we ever have. If we went back to only features and services available in 2009, I think we’d find that all modern computing platforms are “stable” by those measurements.

Why does restarting a computer fix most things?

I had not thought about this before a recent episode of Reconcilable Differences. Merlin Mann made a great point: restarting a computer puts everything back to a known state. The problem with our current technology stack is there is no way to reboot “the cloud”. A lot of people have 4+ devices that access the same amount of data, and there are countless ways for things to not work. In fact, when I realize how many devices I have accessing my Wi-Fi and/or iCloud Data, I am surprised it even works half the time.

Wrap-up

Stability was a key feature in iOS 12 and macOS Mojave. Both operating systems launched to much fanfare among people who were craving a year with fewer features and more bug fixes. It would be wise for Apple to repeat that process every couple of years. It would give their engineering teams time to breathe and work on long-range plans.

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How To Draw A Polygon Using Gui In Java

How to draw a polygon using GUI in Java

Problem Description

How to draw a polygon using GUI?

Solution

Following example demonstrates how to draw a polygon by creating Polygon() object. addPoint() & drawPolygon() method is used to draw the Polygon.

import java.awt.*; import java.awt.event.*; import javax.swing.*; public class Main extends JPanel { public void paintComponent(Graphics g) { super.paintComponent(g); Polygon p = new Polygon(); for (int i = 0; i < 5; i++) p.addPoint((int) ( 100 + 50 * Math.cos(i * 2 * chúng tôi / 5)),(int) (100 + 50 * Math.sin( i * 2 * chúng tôi / 5))); g.drawPolygon(p); } public static void main(String[] args) { JFrame frame = new JFrame(); frame.setTitle("Polygon"); frame.setSize(350, 250); frame.addWindowListener(new WindowAdapter() { public void windowClosing(WindowEvent e) { System.exit(0); } }); Container contentPane = frame.getContentPane(); contentPane.add(new Main()); frame.setVisible(true); } } Result

The above code sample will produce the following result.

Polygon is displayed in a frame.

The following is an another sample example to draw a polygon using GUI.

import java.awt.Color; import java.awt.Container; import java.awt.Graphics; import java.awt.Polygon; import java.awt.event.WindowAdapter; import java.awt.event.WindowEvent; import javax.swing.JFrame; import javax.swing.JPanel; public class Panel extends JPanel { public void paintComponent(Graphics g) { super.paintComponent(g); Polygon p = new Polygon(); for (int i = 0; i < 5; i++) p.addPoint((int) ( 100 + 50 * Math.cos(i * 2 * chúng tôi / 5)),(int) ( 100 + 50 * Math.sin(i * 2 * chúng tôi / 5))); g.drawPolygon(p); } public static void main(String[] args) { JFrame frame = new JFrame(); frame.getContentPane().setBackground(Color.YELLOW); frame.setTitle("DrawPoly"); frame.setSize(350, 250); frame.addWindowListener(new WindowAdapter() { public void windowClosing(WindowEvent e) { System.exit(0); } }); Container contentPane = frame.getContentPane(); contentPane.add(new Panel()); frame.show(); } }

The above code sample will produce the following result.

Polygon is displayed in a frame.

java_simple_gui.htm

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How To Use Quick Assist For Remote Assistance On Windows 11

On Windows 11, you can use the Quick Assist app to give or get help remotely, and in this guide, you will learn the steps to use it. The app has been designed to replace the legacy “Windows Remote Assistance” app. It’s technically a remote desktop app, but this solution is more secure and easier to use. 

For example, when using Quick Assist, you don’t need to turn on the “Remote Desktop,” “Remote Assistance,” or any other feature or configure the firewall. However, you cannot initiate a connection without another person present on the other end since someone on the receiving side has to confirm the connection code and allow control. 

The app will usually come in handy to help to resolve a problem remotely or guide someone through the steps to complete a specific task or teach them something.

In this guide, you’ll learn the steps to get started using the Quick Assist app on Windows 11.

Remote assistance with Quick Assist on Windows 11

To use Quick Assist on Windows 11 for remote assistance, use these steps:

Quick tip: You can launch the app directly with the “Ctrl + Windows key + Q” keyboard shortcut.

Sign in with your Microsoft account.

Send the security code to the other person who will receive the remote assistance.

On the computer getting help, open the Quick Assist app.

Under the “Get assistance” section, confirm the security code.

Once the remote connection is established, the person offering assistance will be able to take control of the computer that is getting the help to resolve a problem or guide someone through the steps to complete a specific task.

When using the Quick Assist app, if you are not already on the phone with the person, you can open the “Chat” interface to text back and forth.

The “Pause” button will stop the remote assistance without terminating the connection. Anyone can use the pause option, but only the person receiving the help can resume the connection.

The “Leave” button will terminate the connection. If you need to reconnect, you will have to perform the same steps to create a new remote connection.

In the device giving the help, the Quick Assist app will also offer some additional tools, including a laser pointer, animation, monitor selection (if the device has multiple displays), an actual screen, and more.

FAQ What’s Quick Assist on Windows 11?

Quick Assist is a remote assistance solution that Microsoft offers for free, and you can use it to give help to another person you trust. You can use it to solve problems remotely or guide someone through the steps to complete a specific task.

What version of Windows includes Quick Assist?

The Quick Assist app is available for the “Home” and “Pro” editions of Windows 11 and 10.

How to install Quick Assist on Windows 11? What’s the difference between Quick Assist and Remote Desktop?

Quick Assist allows you to offer remote assistance to another person through the internet or within the local network without complicated configurations. When using this solution, the person offering the help must generate and send a security code that the person receiving the assistance must confirm in the Quick Assist app to allow someone else to access the device remotely. Remote Desktop also allows you to access a device remotely, but it requires more configuration, including setting up the firewall and router if you plan to access the computer through the internet. Furthermore, you must know the login information from the remote computer. 

Usually, Remote Desktop works best for remoting into your computer to retrieve files or work remotely with certain applications. Or for a network administrator to offer assistance within the local network. Quick Assist is best to offer help to another person (such as family members or friends) over the internet.

Quick Assist isn’t working?

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