| import torch |
| from diffusers import StableDiffusionPipeline |
| import matplotlib.pyplot as plt |
|
|
| |
| device = "cuda" if torch.cuda.is_available() else "cpu" |
|
|
| |
| model_id = "CompVis/stable-diffusion-v1-4" |
| pipe = StableDiffusionPipeline.from_pretrained(model_id).to(device) |
|
|
| |
| def generate_image(prompt, num_images=1): |
| images = [] |
| for _ in range(num_images): |
| with torch.no_grad(): |
| image = pipe(prompt).images[0] |
| images.append(image) |
| return images |
|
|
| |
| prompt = "a fantasy landscape with mountains and a river" |
| generated_images = generate_image(prompt, num_images=1) |
|
|
| |
| for img in generated_images: |
| plt.imshow(img) |
| plt.axis('off') |
| plt.show() |
|
|