Upscale Image with Automatic 1111: Tutorial for Beginners – Fast and Easy!

BlueSpork
11 Nov 202303:14

TLDRThis tutorial demonstrates an efficient method for upscaling images using the Automatic 1111 software. The process begins with generating a 512x512 resolution image and continues through a series of upscaling steps using the stable diffusion web UI, with each iteration resulting in a significantly larger image resolution. The upscaling is performed on an Nvidia RTX 3060 GPU with 12 GB of VRAM, showcasing the real-time process and its progression from 512x512 to 8192x8192 resolution. The tutorial emphasizes the increasing time required for each upscaling iteration, with the final upscale taking around 8 minutes. The video concludes with a comparison between the original and the final upscaled image, highlighting the impressive results achievable with this method.

Takeaways

  • 🖼️ The process starts by generating an image with a resolution of 512x512.
  • ⏱️ Image generation takes approximately 5 seconds to complete.
  • 📂 Navigate to the 'automatic 1111' folder, then to 'stable diffusion web UI', and 'outputs text to images' to find the created image.
  • 🔄 Use the 'imageo' tab to drag and drop the image for upscaling.
  • 🔍 Enter 'highly detailed' in the positive prompt for better results.
  • ⚙️ Adjust the CFG scale to 11 and set the denoising strength to 0.1 for the upscaling process.
  • 🔧 Choose 'SD upscale' from the scripts dropdown and select 'Eren 4X' for the upscaling method.
  • 💻 The upscaling is performed on an Nvidia RTX 3060 GPU with 12 GB of VRAM.
  • ⏳ The first upscale from 512x512 to 1024x1024 takes 12 seconds.
  • 📈 Each subsequent upscale takes progressively longer, with the second upscale to 2048x2048 taking 33 seconds.
  • 🕒 The upscale to 4096x4096 resolution takes over 2 minutes, and the final upscale to 8192x8192 takes around 8 minutes.
  • 🆚 The final upscaled image at 8192x8192 resolution is compared to the original 512x512 image, showing a significant increase in detail.
  • 📢 The video concludes with a call to action for viewers to subscribe, like, and share the content.

Q & A

  • What is the initial resolution of the image generated in the tutorial?

    -The initial resolution of the image generated is 512 by 512 pixels.

  • How long did it take to complete the image generation in the tutorial?

    -The image generation took 5 seconds to complete.

  • Where is the image created found after generation?

    -The image created is found in the 'automatic 1111' folder, then in the 'stable diffusion web UI', under the 'outputs text to images' and then in the 'current date' folder.

  • What is the term used for the process of making the image highly detailed?

    -The term used for making the image highly detailed is 'upscaling'.

  • What is the CFG scale set to in the tutorial?

    -The CFG scale is set to 11 in the tutorial.

  • What is the denoising strength set to in the tutorial?

    -The denoising strength is set to 0.1 in the tutorial.

  • Which script is chosen from the dropdown for upscaling?

    -The 'SD upscale' script is chosen from the dropdown for upscaling.

  • What resolution does the image upscale to after the first round of upscaling?

    -After the first round of upscaling, the image resolution increases to 1024 by 1024 pixels.

  • How long does the second round of upscaling to 2048 by 2048 pixels take?

    -The second round of upscaling to 2048 by 2048 pixels takes 33 seconds.

  • What is the total generation time for the second upscale?

    -The total generation time for the second upscale is 33 seconds.

  • How much longer does the third round of upscaling take compared to the second round?

    -The third round of upscaling takes almost four times longer than the second round, which took 33 seconds.

  • What is the final resolution of the image after the third and final round of upscaling?

    -The final resolution of the image after the third and final round of upscaling is 8192 by 8192 pixels.

  • What GPU and how much VRAM is used for the upscaling process in the tutorial?

    -An Nvidia RTX 3060 GPU with 12 GB of VRAM is used for the upscaling process in the tutorial.

Outlines

00:00

🖼️ Image Generation and Upscaling Process

The video script describes the process of generating an image with a resolution of 512x512, which took 5 seconds to complete. The image is then located in a specific folder and is subsequently upscaled through a series of steps using a Nvidia RTX 3060 GPU with 12 GB of VRAM. The upscaling process is shown in real-time, with the image's resolution doubling each time. The upscaling tasks are performed using the SD upscale script with Eren 4X selection, and the time taken for each upscaling increases significantly with each iteration. The final upscale results in an image of resolution 8192x8192, which is compared to the original 512x512 image, showcasing a significant increase in detail and size. The video concludes with a call to action for viewers to subscribe, like, and share the content.

Mindmap

Keywords

💡Image Resolution

Image resolution refers to the number of pixels in an image, which determines its size and clarity. In the video, the process begins with generating an image with a resolution of 512 by 512 pixels, and the goal is to upscale this to a much higher resolution, such as 8,192 by 8,192 pixels.

💡Automatic 1111

This term likely refers to a specific folder or software tool used in the image upscaling process. It is mentioned as a step in the tutorial where the user navigates to this folder to find the image they created, indicating it is a part of the workflow.

💡Stable Diffusion Web UI

Stable Diffusion Web UI is a user interface for a stable diffusion model, which is a type of machine learning model used for generating images from text descriptions. In the context of the video, it is the platform where the user interacts with to upscale images.

💡Text to Images

Text to images is a process where a description in text form is used to generate a corresponding image. The video mentions navigating to a folder named 'text to images', suggesting that the initial image generation was based on a textual description.

💡Highly Detailed

This phrase is used in the context of the positive prompt when the user is instructing the upscaling tool to generate a highly detailed image. It indicates the desired level of intricacy and clarity in the upscaled image.

💡CFG Scale

CFG Scale likely stands for 'Configuration Scale' and is a parameter that the user adjusts in the upscaling process. In the video, it is set to 11, which suggests that it controls the level of detail or the aggressiveness of the upscaling algorithm.

💡Denoising Strength

Denoising strength is a parameter that controls the amount of noise reduction applied to the image during the upscaling process. A lower value, such as 0.1 used in the video, would result in less noise reduction, helping to preserve details in the image.

💡SD Upscale

SD Upscale refers to the specific upscaling method or script selected in the video, which is used to increase the resolution of the image. It is part of the steps taken to upscale the image from its original size to a higher resolution.

💡Eren 4X

Eren 4X is a selection made by the user to upscale the image by a factor of four times its original resolution. It is a specific setting or option within the upscaling tool used in the video.

💡Nvidia RTX 3060 GPU

Nvidia RTX 3060 GPU is a graphics processing unit (GPU) model by Nvidia, which is used for rendering images and videos. In the video, it is the hardware that facilitates the real-time upscale process, highlighting its role in providing the computational power needed for image upscaling.

💡VRAM

VRAM, or Video RAM, is a type of memory used by the GPU to store image data. The video mentions having 12 GB of VRAM, which is significant for handling high-resolution images and complex graphics processing tasks.

💡Upscale Process

The upscale process is the main theme of the video, where the original image's resolution is incrementally increased through a series of steps. Each upscale iteration takes progressively longer, demonstrating the increasing computational demand as the resolution grows.

Highlights

The process begins with generating an image with a resolution of 512 by 512.

Image generation takes approximately 5 seconds to complete.

Navigate to the 'automatic 1111' folder, then to 'stable diffusion web UI'.

Find the created image in the 'outputs text to images current date' folder.

Use the 'imageo' tab to drag and drop the image into the positive prompt.

Type 'highly detailed' in the positive prompt to enhance image quality.

Adjust the CFG scale to 11 for better image upscaling.

Set the denoising strength to 0.1 for a cleaner upscaled image.

Select 'SD upscale' from the scripts dropdown and choose 'Eren 4X' for the upscaling process.

The upscale from 512x512 to 1024x1024 takes 12 seconds on an Nvidia RTX 3060 GPU.

The upscaled image is saved in the 'image to image' folder with a subfolder named after the current date.

The second upscale to 2048x2048 takes longer than the first one.

The total generation time for the second upscale is 33 seconds.

Upscaling to 4096x4096 takes 2 minutes and 7 seconds, nearly four times longer than the previous upscale.

The final upscale to 8192x8192 resolution takes around 8 minutes, marking the third and final round.

The final upscaled image is compared to the original 512x512 image, showcasing significant enhancement.

The final image is displayed at 11% of its size for comparison.

The video concludes with a call to action for viewers to subscribe, like, and share.

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