Improving Image Generations

If your images generation results are not as you expected, here are a few things you can do to improve the quality of your generations: 

• Fine tune your prompt - the more specific you are, the closer the image will turn out to what is in your head! Adding more details in the Positive Prompt or Negative Prompt can help add / remove pieces of your image to improve it - You can also use advanced techniques like upweighting and downweighting to control the influence of certain words. Learn more here.
  
• Explore different models - Other models can produce different results due to the data they’ve been trained on. Each model has specific language and settings it works best with. Play around with some and see what works best for you!
• Ensure you're creating images with the ideal resolution for the model type in use - You can use the "Optimize" button in your Image settings to ensure that you're using this ideal size; 512x512 for SD1.5,  768x768 for SD2.1 and 1024x1024 for SDXL
  
• Increasing Steps - The number of steps used controls how much time the model is given to produce an image, and depends on the “Scheduler” used. The schedule controls how each step is processed by the model. More steps tends to mean better results, but will take longer - We recommend at least 30 steps for most
• Tweak and Iterate - Remember, it’s best to change one thing at a time so you know what is working and what isn't. Sometimes you just need to try a new image, and other times using a new prompt might be the ticket. For testing, consider turning off the “random” Seed - Using the same seed with the same settings will produce the same image, which makes it the perfect way to learn exactly what your changes are doing.
• Utilize ControlNets - ControlNets help guide the model during the image generation process. Applying a ControlNet during the early steps of the denoising process will help provide structure to the composition of the image, while ControlNets applied to the later steps will provide control over the details in the final image.