DiffusionLens / app.py
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import gradio as gr
import sys
# sys.path.append("LaVi-Bridge/test")
# from llama2_unet_diffusion_lens import call_diffusion_lens
from diffusion_lens import get_images
import gradio as gr
import os
import subprocess
def display_images(images):
# Prepare images for display
return [gr.Image(image) for image in images]
# def get_prompt(prompt):
# print('prompt:', prompt)
# print('calling diffusion lens')
# image = get_images(prompt, skip_layers=0)
# return image
#
# if __name__ == '__main__':
# with gr.Blocks() as demo:
# gallery = gr.Gallery(
# label="Generated images", show_label=False, elem_id="gallery",
# columns=[1], rows=[1], object_fit="contain", height="auto")
# btn = gr.Button("Generate images", scale=0)
#
# btn.click(get_prompt, 'text', gallery)
#
# demo.launch()
def get_prompt(prompt):
print('prompt:', prompt)
print('calling diffusion lens')
for skip_layers in range(24): # loop from 0 to 23
image = get_images(prompt, skip_layers=skip_layers)
gallery.update(image) # update the gallery with the new image
return "Images generated"
if __name__ == '__main__':
with gr.Blocks() as demo:
gallery = gr.Gallery(
label="Generated images", show_label=False, elem_id="gallery",
columns=[6], rows=[4], object_fit="contain", height="auto") # set rows to 24 to accommodate all images
btn = gr.Button("Generate images", scale=0)
text_input = gr.Interface(fn=get_prompt, inputs="text", outputs='Gallery', label='Intermediate images')
btn.click(get_prompt, text_input, gallery) # pass the text input interface to btn.click()
demo.launch()