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git clone https://github.com/openai/CLIP
# !pip install taming-transformers
git clone https://github.com/CompVis/taming-transformers.git
rm -Rf pixray
git clone https://github.com/dribnet/pixray
mkdir steps
mkdir models
import sys
sys.path.append("pixray")
import gradio as gr
import torch
import pixray
# Define the main function
def generate(prompt, quality, style, aspect):
torch.cuda.empty_cache()
pixray.reset_settings()
# use_pixeldraw = (style == 'pixel art')
# use_clipdraw = (style == 'painting')
pixray.add_settings(prompts=prompt,
aspect=aspect,
quality=quality,
make_video=True)
settings = pixray.apply_settings()
pixray.do_init(settings)
pixray.do_run(settings)
return 'output.png', 'output.mp4'
# Create the UI
prompt = gr.inputs.Textbox(default="Underwater city", label="Text Prompt")
quality = gr.inputs.Radio(choices=['draft', 'normal', 'better'], label="Quality")
# style = gr.inputs.Radio(choices=['image', 'painting','pixel art'], label="Type")
aspect = gr.inputs.Radio(choices=['square', 'widescreen','portrait'], label="Size")
# Launch the demo
iface = gr.Interface(generate, inputs=[prompt, quality, aspect], outputs=['image', 'video'], enable_queue=True, live=False)
iface.launch(debug=True) |