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import gradio as gr
import random, os
from PIL import Image
def open_ims(choice):
dirname='images/'+choice.replace(' ','_')+'/Seed_'+ str(seed_choice)+'/'
imnames= os.listdir(dirname)
images = [(Image.open(dirname+name)) for name in imnames]
return images[:9]
def random_image():
cat = random.choice(categories)
dirname = 'images/'+cat.replace(' ','_')+'/Seed_'+str(seed_choice)+'/'
imnames = os.listdir(dirname)
images = [(Image.open(dirname+name)) for name in imnames]
return images[:9]
categories=os.listdir('images/')
categories = [c.replace('_',' ') for c in categories]
seeds = [46267, 48040, 51237, 54325, 60884, 64830, 67031, 72935, 92118, 93109]
with gr.Blocks() as demo:
gr.Markdown("# Stable Diffusion Explorer")
gr.Markdown("## Choose from the prompts below to explore the way in which the Stable Diffusion model encodes societal biases")
seed_choice = gr.State(0)
seed_choice = random.choice(seeds)
print("Seed choice is: " + str(seed_choice))
with gr.Row():
with gr.Column():
choice1 = gr.Dropdown(categories, label = "Choose a first category", interactive=True)
images1 = gr.Gallery(label="Images").style(grid=[3], height="auto")
with gr.Column():
choice2 = gr.Dropdown(categories, label = "Choose a second category", interactive=True)
images2 = gr.Gallery(label="Images").style(grid=[3], height="auto")
#demo.load(random_image, None, [images])
choice1.change(open_ims, [choice1], [images1])
choice2.change(open_ims, [choice2], [images2])
demo.launch()
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