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# -*- coding: utf-8 -*-
"""Diffusion.ipynb
Automatically generated by Colaboratory.
Original file is located at
https://colab.research.google.com/drive/1bcJlVBYDIxhySq0b6YHyKsumLgIomNqf
#Diffusion
Setup
"""
!nvidia-smi
!pip install diffusers==0.11.1
!pip install transformers scipy ftfy accelerate
"""pipeline"""
import torch
from diffusers import StableDiffusionPipeline
pipe = StableDiffusionPipeline.from_pretrained("CompVis/stable-diffusion-v1-4")
# move pipeline to GPU
pipe = pipe.to("cuda")
# Let's Generate image
prompt = "cute panda eating pizza on bamboo tree "
image = pipe(prompt).images[0]
image.save(f"Happy_panda.png")
image
import torch
generator = torch.Generator("cuda").manual_seed(2048)
image = pipe(prompt, generator=generator).images[0]
image
# increase inference steps
import torch
generator = torch.Generator("cuda").manual_seed(2048)
image = pipe(prompt, num_inference_steps=70, generator=generator).images[0]
image
from PIL import Image
def image_grid(imgs, rows, cols):
assert len(imgs) == rows*cols
w, h = imgs[0].size
grid = Image.new('RGB', size=(cols*w, rows*h))
grid_w, grid_h = grid.size
for i, img in enumerate(imgs):
grid.paste(img, box=(i%cols*w, i//cols*h))
return grid
num_images = 3
prompt = ["cute panda eating pizza on bamboo tree "] * num_images
images = pipe(prompt).images
grid = image_grid(images, rows=1, cols=3)
grid
num_cols = 3
num_rows = 4
prompt = ["cute panda eating pizza on bamboo tree "] * num_cols
all_images = []
for i in range(num_rows):
images = pipe(prompt).images
all_images.extend(images)
grid = image_grid(all_images, rows=num_rows, cols=num_cols)
grid
# Generating rectangle image
prompt = "cute panda eating pizza on bamboo tree "
image = pipe(prompt, height=512, width=752).images[0]
image
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