Delete app.ipynb

app.ipynb

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-!pip install torch==1.9.0+cu111 torchtext==0.10.0 torchvision==0.10.0+cu111 -f https://download.pytorch.org/whl/torch/ -f https://download.pytorch.org/whl/torchvision/
-
-!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
-!pip install ftfy regex tqdm omegaconf pytorch-lightning
-!pip install kornia==0.6.1
-!pip install imageio-ffmpeg   
-!pip install einops
-!pip install torch-optimizer
-!pip install easydict
-!pip install braceexpand
-!pip install git+https://github.com/pvigier/perlin-numpy
-!mkdir steps
-!mkdir models
-!wget https://user-images.githubusercontent.com/945979/126260797-adc60317-9518-40de-8700-b1f93e81e0ec.png -O this_is_fine.png
-!wget https://user-images.githubusercontent.com/945979/126415385-d70ff2b0-f021-4238-9621-6180d33b242c.jpg -O perfume.jpg
-!pip install gradio==2.5.1
-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)