Second Quadrant: photo sds
Collection
6 items
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Updated
MykosX/isabela-photo-sd is a Stable Diffusion model that can be used both for:
| (seed=300)** | (seed=400)** | (seed=500)** | |
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| text-to-image |
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| image-to-image |
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| (seed=300)** | (seed=400)** | (seed=500)** | |
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| text-to-image |
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| image-to-image |
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| Base image (from another model) | image-to-image (seed=300)** | image-to-image (seed=400)** | image-to-image (seed=500)** |
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| Base image (from another model) | image-to-image (seed=300)* | image-to-image (seed=400)* | image-to-image (seed=500)* |
** using these defaults unless specified:
| Setting | Default value |
|---|---|
| prompt (landscape) | landscape image, a boy and girl having fun on the beach |
| prompt (portrait) | portrait image, a girl in a nice dress posing for a photo |
| negative prompt | deformed iris, deformed pupils, bad anatomy, cloned face, extra arms, extra legs, missing fingers, too many fingers |
| size (landscape) | 1024 x 768 |
| size (portrait) | 768 x 1024 |
| seed | 300 |
| guidance scale | 12.0 |
| strength | 0.5 |
| inference steps | 30 |
For more general information on how to run text-to-image models with 🧨 Diffusers, see the docs.
pip install diffusers transformers accelerate
import torch
from diffusers import AutoPipelineForText2Image
pipe = AutoPipelineForText2Image.from_pretrained('MykosX/isabela-photo-sd', torch_dtype=torch.float32)
pipe = pipe.to("cpu")
prompt = "portrait image, a girl in a nice dress posing for a photo"
image = pipe(prompt).images[0]
image.save("./images/text-to-image.png")
import torch
from diffusers import AutoPipelineForImage2Image
from PIL import Image
pipe = AutoPipelineForImage2Image.from_pretrained('MykosX/isabela-photo-sd', torch_dtype=torch.float32)
pipe = pipe.to("cpu")
base_image = Image.open("./images/girl-posing-photo-(original).jpg")
prompt = "portrait image, a girl in a nice dress posing for a photo"
image = pipe(prompt, image=base_image).images[0]
image.save("./images/image-to-image.png")
Play with the model and don't hesitate to show off