Which Should You Choose? Stable Diffusion 1.5 or SDXL?

Playground AI
1 Dec 202307:16

TLDRThe video discusses the differences between Stable Diffusion 1.5 and its XL variant, highlighting the XL's higher native resolution and better performance at larger sizes. It demonstrates how XL is less prone to deformities like double heads, while 1.5 requires more negative prompts for coherent results. The refiner model in XL enhances details, and filters significantly improve 1.5's output. The presenter recommends starting with XL for easier prompting but acknowledges that mastering 1.5 can yield impressive results.

Takeaways

  • 🌟 Stable Diffusion 1.5 and SDXL are two versions of a foundational model, with 1.5 being older and SDXL released more recently.
  • 📸 SDXL has a higher native resolution of 1024x1024 compared to 1.5's 512x512, allowing for higher quality images at optimal sizes.
  • 🚫 When using 1.5 beyond its optimal size, there's a higher chance of image deformities such as double heads or distorted features.
  • 📈 SDXL can handle larger image sizes, like 1536x640, with less likelihood of deformities, offering better results.
  • 🔍 In demonstrations, 1.5 produced less satisfactory results at higher resolutions without filters.
  • 🎨 Applying filters and negative prompts to 1.5 can significantly improve image quality and coherence.
  • 🌈 SDXL generally produces images with better dynamic range, contrast, and color, needing fewer negative prompts for quality results.
  • 🔧 SDXL includes a refiner model that can enhance details, providing an advantage for images requiring intricate details.
  • 📝 Filters can be identified by labels in the filter menu, with different filters available for SDXL and 1.5.
  • 📚 The speaker recommends starting with SDXL for easier prompting but acknowledges that mastering 1.5 can yield amazing results with SDXL.
  • 💡 The choice between SDXL and 1.5 depends on personal preference, with SDXL being more user-friendly for beginners.

Q & A

  • What are the two versions of Stable Diffusion discussed in the script?

    -The two versions of Stable Diffusion discussed in the script are Stable Diffusion 1.5 and Stable Diffusion XL (often referred to as SDXL or Excel).

  • What is the primary difference between Stable Diffusion 1.5 and SDXL in terms of native resolutions?

    -The primary difference between Stable Diffusion 1.5 and SDXL in terms of native resolutions is that 1.5 has a native resolution of 512x512, while SDXL has a native resolution of 1024x1024.

  • What are the potential deformities that may occur when using Stable Diffusion 1.5 at non-optimal sizes?

    -When using Stable Diffusion 1.5 at non-optimal sizes, such as 1024x768, the output may be prone to deformities like double heads, deformed faces, and hands, and other such issues.

  • How does the performance of SDXL compare to 1.5 when it comes to handling larger image sizes?

    -SDXL is capable of handling larger image sizes better than 1.5. For instance, it can go as big as 1536x640 without a significant increase in the likelihood of deformities, whereas 1.5 may struggle with larger dimensions beyond its optimal size.

  • What is the role of negative prompts in improving the results of Stable Diffusion 1.5?

    -Negative prompts play a crucial role in improving the results of Stable Diffusion 1.5. They help refine the output by excluding undesired features, leading to more coherent and compositionally acceptable images.

  • How do filters impact the quality of images produced by Stable Diffusion 1.5?

    -Filters can dramatically improve the quality of images produced by Stable Diffusion 1.5. They enhance the coherency and aesthetics of the images, making them look more pleasing even with simple prompts.

  • What is the refiner model in SDXL, and how does it enhance the images?

    -The refiner model in SDXL is an optional feature that helps enhance details in the generated images. By adjusting the refinement slider, users can make the details more defined, intricate, and detailed, which can be a significant advantage for images requiring fine details.

  • How can you identify which filters belong to SDXL or 1.5 in the filter menu?

    -In the filter menu, the labels at the top left corner indicate which model the available filters belong to. SDXL filters will be populated when SDXL is selected, and the menu changes to display filters for 1.5 when it is selected.

  • What is the speaker's recommendation for beginners learning to prompt Stable Diffusion?

    -The speaker recommends that beginners start with SDXL as it is easier to prompt. However, achieving great results with 1.5 can lead to amazing images in SDXL, making it a worthwhile challenge.

  • What is the speaker's approach to addressing viewer questions in future videos?

    -The speaker plans to answer viewer questions more frequently in future videos and is considering doing so on a monthly basis, drawing questions from the comments section and support inquiries.

  • How does the script demonstrate the importance of aspect ratio when using SDXL?

    -The script demonstrates the importance of aspect ratio with SDXL by showing that it works better with larger aspect ratios, even without the use of filters. The speaker illustrates this by comparing the quality of images at different dimensions and highlighting the benefits of higher resolutions.

  • What are the general color and contrast advantages of SDXL over 1.5?

    -SDXL tends to have better contrast in blacks and a wider overall dynamic range of color, making it easier to prompt and yielding images with more visually pleasing aesthetics compared to 1.5.

Outlines

00:00

🖼️ Comparing Stable Diffusion Models: 1.5 vs. SDXL

This segment introduces the audience to the differences between Stable Diffusion 1.5 and SDXL, two versions of foundational models available on Playground. Stable Diffusion 1.5, the older model, operates at a native resolution of 512x512, while SDXL supports a higher resolution of 1024x1024. When pushed beyond their optimal sizes, 1.5 can produce images with deformities such as double heads, whereas SDXL can handle larger dimensions like 1536x640 with fewer issues. Through examples using a simple prompt, the narrator demonstrates that while 1.5 struggles with higher resolutions, producing deformed or cropped images, SDXL maintains better image quality across various dimensions without the need for negative prompts. The discussion includes the effect of using negative prompts and filters to improve image quality with 1.5, contrasting with SDXL's inherent ability to generate higher quality images without such aids.

05:01

🔍 Enhancing Image Details with Refiners and Filters

In this part, the focus shifts to the 'refiner model' feature exclusive to SDXL, illustrating its capability to enhance image details. By adjusting the refinement slider, users can significantly improve the intricacy and definition of details in images, such as on the forehead and jewelry in a given example. However, the narrator cautions against overuse, which can lead to messy outcomes. The discussion extends to filters, explaining how the available filters automatically adjust based on the selected model (1.5 or SDXL). This segment also provides guidance on how users can identify which filters are applicable to each model via labels in the filter menu. The narrator suggests starting with SDXL for its ease of use and better initial quality but also encourages mastering Stable Diffusion 1.5 to enhance SDXL results further. Finally, the video promises future sessions to answer viewer questions, fostering a learning community around the Playground platform.

Mindmap

Keywords

💡Stable Diffusion 1.5

Stable Diffusion 1.5 is an older foundational AI model discussed in the video. It is characterized by a native resolution of 512x512, which means it is optimized for images of this size. The video illustrates that when using this model beyond its optimal size, such as 1024x768, the images may become prone to deformities like double heads. However, with the use of negative prompts and filters, better results can be achieved, and the model can produce more coherent images, especially at its native resolution.

💡Stable Diffusion XL

Stable Diffusion XL, also referred to as SDXL, is a more recent model introduced in the past summer according to the video. It has a higher native resolution of 1024x1024, allowing for the generation of images with more detail and less likelihood of deformities when scaled up. The video demonstrates that SDXL can handle larger aspect ratios like 1536x640 without significant issues, and it generally produces images with better contrast, dynamic range, and color compared to the 1.5 version.

💡Native Resolution

Native resolution refers to the dimension at which a model is optimized to generate images. In the context of the video, Stable Diffusion 1.5 has a native resolution of 512x512, while Stable Diffusion XL has a native resolution of 1024x1024. The video emphasizes that working within the native resolution of a model results in better image quality and fewer artifacts or deformities.

💡Deformities

Deformities in the context of the video refer to the visual anomalies or distortions that can occur in the generated images when the AI models are pushed beyond their optimal performance limits. This can include issues like extra heads, distorted limbs, or other irregularities that detract from the overall quality and coherence of the image.

💡Negative Prompts

Negative prompts are additional instructions provided to the AI model to exclude certain elements or features from the generated images. They are used to guide the AI towards a more desired output by specifying what should not be present in the image. The video suggests that Stable Diffusion 1.5 requires more negative prompts to achieve better results compared to Stable Diffusion XL, which can produce more favorable images with fewer prompts.

💡Refiner Model

The Refiner Model is a feature available in Stable Diffusion XL that allows users to enhance the details of the generated images. By using a refinement slider, users can exaggerate or define certain aspects of the image, making the details more intricate and clear. This tool is particularly useful for images that require fine details, but it should be used cautiously to avoid making the image too messy.

💡Dynamic Range

Dynamic range in the context of the video refers to the extent of tonal values from the darkest black to the brightest white that the AI models can represent in the generated images. A higher dynamic range indicates better contrast and a wider range of colors, which contributes to a more visually appealing and realistic image. The video suggests that Stable Diffusion XL has an overall better dynamic range compared to version 1.5.

💡Filters

Filters in the context of the video are tools that can be applied to the AI-generated images to enhance or alter their appearance. They can improve the coherency and aesthetics of the images by emphasizing certain features or styles. The video explains that different filters are available for Stable Diffusion 1.5 and XL, and their effectiveness can be seen in the improved results when applied to the images.

💡Prompting

Prompting is the process of providing textual instructions or descriptions to the AI model to guide the generation of specific images. The video discusses the ease or difficulty of prompting for each model, suggesting that Stable Diffusion XL is easier to prompt and requires fewer negative prompts compared to version 1.5. Effective prompting can lead to better image quality and adherence to the user's desired output.

💡Image Quality

Image quality refers to the overall visual fidelity and detail of the generated images. It encompasses aspects such as resolution, color accuracy, contrast, and the absence of deformities. The video compares the image quality of Stable Diffusion 1.5 and XL, highlighting that XL generally produces higher quality images with better detail and less likelihood of deformities, especially at larger sizes.

Highlights

Stable Diffusion 1.5 and SDXL are two versions of a foundational model on the playground, with 1.5 being an older model and SDXL introduced in the past summer.

The native resolution of Stable Diffusion 1.5 is 512x512, while SDXL has a higher resolution of 1024x1024, allowing for higher quality images.

When using Stable Diffusion 1.5, going beyond the optimal size, like 1024x768, may result in deformities such as double heads.

SDXL can handle larger image sizes, for example, up to 1536x640, with less likelihood of deformities.

The presenter demonstrates the use of the models by generating images of Brian Kenston with different prompts and resolutions.

Increasing the resolution to 1024x768 with Stable Diffusion 1.5 results in images that are out of whack and deformed.

SDXL produces better image quality overall, with a more favorable dynamic range and aesthetics, even without negative prompts.

Stable Diffusion 1.5 requires more negative prompts to achieve decent results, unlike SDXL.

Using filters with SD 1.5 can dramatically improve image coherency and aesthetics, as demonstrated with the Realistic Vision filter.

SDXL benefits from higher image sizes without the need for filters, maintaining better contrast and color dynamic range.

SDXL has a refiner model that enhances details, making it advantageous for images requiring fine details.

The refiner should be used sparingly to avoid making the image messy.

Filters for SDXL and 1.5 can be identified by labels in the filter menu, with different sets available for each model.

Starting with SDXL is recommended for beginners due to its easier prompting, but achieving great results with 1.5 can also lead to amazing SDXL images.

The presenter plans to answer more questions in upcoming videos, considering doing them monthly.