Today, I started messing around with Stable Diffusion, and the first thing I wanted to do was generate some cool images of roses. I figured, “Hey, roses are pretty standard, should be easy, right?” Boy, was I in for a surprise.
First Attempts
I jumped right in, typed “a beautiful red rose” into the prompt box, and hit generate. What I got back? Well, let’s just say they weren’t exactly ready for a florist’s window. Some looked like red blobs, others like… well, I’m not even sure what they looked like. Definitely not roses.
Tweaking the Prompts
Okay, so clearly “a beautiful red rose” wasn’t cutting it. I started to get more specific. I tried things like:
- “a single, perfect red rose, photorealistic”
- “a red rose with water droplets, close-up”
- “a bouquet of red roses, vibrant colors”
I played around with different styles too – “oil painting,” “digital art,” “watercolor.” Some of these helped, a little. The “photorealistic” tag seemed to make a difference, but the roses still weren’t quite right. They were often distorted, or the colors were off, or they just looked… fake.
Negative Prompts – A Game Changer
Then I remembered reading something about “negative prompts.” These are basically things you don’t want to see in the image. This is where things started to get interesting.
I added negative prompts like:
- “blurry”
- “deformed”
- “disfigured”
- “mutated”
- “ugly”
- “bad art”
The results were immediately better! The roses started to look more like, well, roses! It seemed like telling the AI what not to do was just as important as telling it what to do.
The Cost of Experimentation
Each time generate a image cost some credits, I was running my own local Stable Diffusion. I soon realized that it needs good GPU to get the satisfied image quality. By “cost,” I mean the time, the resources, the electricity… and maybe a little bit of my sanity! I spent hours tweaking prompts, adjusting settings, and generating image after image.
Finally, Some Success!
After a lot of trial and error, I finally started getting some images that I was happy with. It wasn’t just one magic prompt, but a combination of things: a detailed positive prompt, a good set of negative prompts, the right style, and a bit of luck. And using a good model.
So, yeah, “roses cost” – they cost time, effort, and a whole lot of experimentation. But it was also a lot of fun, and I learned a ton about how to work with Stable Diffusion. And to get one good image, it may costs you hundreads of bad ones.
