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app.ipynb

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+%%capture
+!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)