diffusers/models/vision/glide/run_glide.py

25 lines
571 B
Python

import torch
import PIL.Image
from diffusers import DiffusionPipeline
generator = torch.Generator()
generator = generator.manual_seed(0)
model_id = "fusing/glide-base"
# load model and scheduler
pipeline = DiffusionPipeline.from_pretrained(model_id)
# run inference (text-conditioned denoising + upscaling)
img = pipeline("a crayon drawing of a corgi", generator)
# process image to PIL
img = img.squeeze(0)
img = ((img + 1) * 127.5).round().clamp(0, 255).to(torch.uint8).cpu().numpy()
image_pil = PIL.Image.fromarray(img)
# save image
image_pil.save("test.png")