‘R6025 pure virtual function call’ is a runtime error that occurs suddenly on the screen and disrupts the program being run prior to it. This error display indicates that the program has been corrupted. R6025 runtime error usually occurs with the Visual C++ framework.
This error occurs when the C++ program crashes which is usually because of the malfunctioning or missing of the device driver or incomplete device driver files.
It happens because your application indirectly calls a pure virtual member function in a context where a call to the function is invalid. Most of the time, the compiler detects it and reports it as an error when building the application. R6025 error is usually detected at run time.
To fix the R6025 pure virtual function call error, you need to find the call to the pure virtual function. After you find the call, you need to rewrite the code so that it is not called again.
There are 2 ways to do this:
One way to fix the R6025 pure virtual function call is to replace the function with an implementation that calls the Windows API function DebugBreak. The DebugBreak causes a hard-coded breakpoint.
Once the code stops running at this breakpoint, it is easy for you to view the call stack. By viewing the call stack you can identify the place where the function was actually called.
Another quick way to find a call to a pure virtual function to fix the R6025 error is to set a breakpoint on the _purecall function that is usually found in PureVirt.c.
By breaking this function you can trace the problem occurring and rewrite the call to ensure the error does not occur and the program you are trying to develop on the Visual C++ framework is easily developed.
If R6025 Error is related to Windows Registry Problem Then here’s how you can fix the problem:
To fix the runtime error R6025, run registry cleaner software to scan and fix all errors. This alternative is suitable if the R6025 error is related to the Windows registry problem and where the error has occurred due to corrupted or malicious registry entries.
You can download the registry cleaner repair tool for free. Run it to scan errors and then click the fix error button to repair the problem immediately.
“We’re having trouble restarting to finish the install, Error 0x8024a11a, 0x8024a112, 0x80070005 or 0x80070032”And so to fix this problem, this post will give you a couple of possible solutions. Refer to the options given below to get started.
SC config trustedinstaller start=auto
Stable Diffusion is a machine learning model developed by Stability AI to generate digital images from natural language descriptions. The model can be used for different tasks like generating image-to-image translations guided by text prompts and upscaling images.
Unlike competing models like DALL-E, Stable Diffusion is open source and does not artificially limit the images it produces. Stable diffusion was trained on a subset of the LAION-Aesthetics V2 data set. It can run on most consumer hardware equipped with a modest GPU and was hailed by PC World as "the next killer app for your PC".
Since Stable Diffusion is run locally and not in the cloud, as mentioned there is no limit to the number of images that you can produce but in order to use it you will have to get down a little dirty with setting your PC environment for it since it is not really an application, it is a command line text based descriptor that will use python to generate your images, so there is no install nor GUI.
In this guide, we will show you how to both install and run Stable Diffusion on your local PC so you can start producing some cool images all by yourself.
Make no mistake, Stable Diffusion will not run on a potato PC, in order to harvest the power of AI-generated imagery this is what you will need:
For this tutorial, we are covering the installation and running of Stable Diffusion on Windows PC. The steps presented here are presented in a way that installation can be performed on any operating system but precise instructions will be for Windows OS.
The first thing to do is to install GIT. It is a tool that will let you easily maintain and install repos from the internet. to install it go to: https://git-scm.com/ and click on download. Follow the instructions for your version of the operating system. If you are a developer you are familiar with GIT and if you already have it installed you can skip this step.
One thing that is important when installing GIT locally is to select to use it via the command line (the second option that says "Git from the command line and also from 3rd-party software").
Now when we have GIT installed, next thing is to use Miniconda3 to install python and all required libraries that are needed. Get the installer at: https://docs.conda.io/en/latest/miniconda.html
Miniconda3 is basically an easy installer so you do not have to install tons of stuff manually from different websites and sources, it is nicely packaged in the installer that will take care of everything.
After the previous two steps, we are ready now to actually install Stable Diffusion. Go to https://huggingface.co/CompVis/stable-diffusion#model-access and install the latest library (as of the writing of this article currently it is stable-diffusion-v1-4-original, the last one on the right), the library is almost 5GB in size so be prepared for big download.
After installing stable diffusion's latest library it is time to update it to the newest version. You can download ZIP from GIT HUB https://github.com/CompVis/stable-diffusion
Once downloaded click on the Windows start button and type in Miniconda3 and click on open. Create a folder and name it how you want on a drive of your choice. For this example, we will install it all in disk C under folder AI_art, follow the instructions below but use your own names and destination instead. Do not close Minicoda3 after typing commands!!!
cd c:/
mkdir AI_art
cd AI_art
Extract GitHub files that you have downloaded into your new folder and get back to Minicoda3 and type the next commands:
cd C:\AI_art\stable-diffusion-main
conda env create -f environment.yaml
conda activate ldm
mkdir models\ldm\stable-diffusion-v1
Let the whole process finish, some files are large and it might take a while. After the whole process is finished and completed, copy the checkpoint file that you have downloaded into: C:\AI_art\stable-diffusion-main\models\ldm\stable-diffusion-v1
After the file is copied rename it to model.ckpt and you are finished.
The created environment is needed in order to actually use Stable Diffusion to create images. Each time you want to use it you will have to run it, so go into Miniconda3, and inside it type:
conda activate ldm
cd C:\AI_art\stable-diffusion-main
after we are inside the folder call the script with the parameters:
python scripts/txt2img.py --prompt "TXT DESCRIPTION OF IMAGE THAT YOU WANT TO CREATE" --plms --n_iter 5 --n_samples 1
and that's it, your image is created and it is located in C:\AI_art\stable-diffusion-main\outputs\txt2img-samples\samples