Upload diffusion.py

diffusion.py

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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
+