pawlo2013 commited on
Commit
2489323
Β·
1 Parent(s): 00de93a

UI fix added example input

Browse files
app.py CHANGED
@@ -4,7 +4,10 @@ import numpy as np
4
  from torchvision import transforms
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  from load_model import sample
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  import torch
 
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  import random
 
 
8
 
9
  device = "cuda" if torch.cuda.is_available() else "cpu"
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  device = "mps" if torch.backends.mps.is_available() else device
@@ -12,6 +15,20 @@ device = "mps" if torch.backends.mps.is_available() else device
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  image_size = 128
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14
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  transform = transforms.Compose(
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  [
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  transforms.Resize((image_size, image_size)),
@@ -60,12 +77,6 @@ with gr.Blocks(theme=theme) as demo:
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  with gr.Column():
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  output = gr.Image(type="pil", label="Output")
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- upscale_info = gr.Markdown(
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- "<p style='text-align: center; font-size: 12px;'>"
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- f"If you want to stretch the downloadable output, check the box below, the default output of neural networks is {image_size}x{image_size} "
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- "</p>"
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- )
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- upscale_button = gr.Checkbox(label="Stretch", value=False)
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70
  with gr.Row():
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  with gr.Column():
@@ -74,6 +85,11 @@ with gr.Blocks(theme=theme) as demo:
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  value=random.randint(0, 10000),
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  )
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  with gr.Column():
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  sampling_slider = gr.Slider(
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  minimum=1,
@@ -82,9 +98,10 @@ with gr.Blocks(theme=theme) as demo:
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  label="DDPM Sampling Steps πŸ”„ (the higher the number of steps the higher the quality of the images)",
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  value=50,
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  )
 
85
 
86
  with gr.Row():
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- generate_button = gr.Button(value="Generate")
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  with gr.Row():
89
  generate_info = gr.Markdown(
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  "<p style='text-align: center; font-size: 16px;'>"
@@ -92,6 +109,14 @@ with gr.Blocks(theme=theme) as demo:
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  "</p>"
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  )
94
 
 
 
 
 
 
 
 
 
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  generate_button.click(
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  process_images,
97
  inputs=[
@@ -107,4 +132,4 @@ with gr.Blocks(theme=theme) as demo:
107
  )
108
 
109
  if __name__ == "__main__":
110
- demo.queue().launch(max_threads=1)
 
4
  from torchvision import transforms
5
  from load_model import sample
6
  import torch
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+ import glob
8
  import random
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+ import os
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+ import pathlib
11
 
12
  device = "cuda" if torch.cuda.is_available() else "cpu"
13
  device = "mps" if torch.backends.mps.is_available() else device
 
15
  image_size = 128
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17
 
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+ def show_example_fn():
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+ sketch = Image.open("examples/sketch.png")
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+ scribble_folder = "./examples/scribbles/"
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+
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+ png_files = [f for f in os.listdir(scribble_folder) if f.lower().endswith(".png")]
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+
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+ # get random scribble
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+ random_scribble = Image.open(
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+ os.path.join(scribble_folder, random.choice(png_files))
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+ )
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+
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+ return [sketch, random_scribble]
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+
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+
32
  transform = transforms.Compose(
33
  [
34
  transforms.Resize((image_size, image_size)),
 
77
 
78
  with gr.Column():
79
  output = gr.Image(type="pil", label="Output")
 
 
 
 
 
 
80
 
81
  with gr.Row():
82
  with gr.Column():
 
85
  value=random.randint(0, 10000),
86
  )
87
 
88
+ upscale_button = gr.Checkbox(
89
+ label=f"Stretch (If you want to stretch the downloadable output, check the box below, the default output of neural networks is {image_size}x{image_size} )",
90
+ value=False,
91
+ )
92
+
93
  with gr.Column():
94
  sampling_slider = gr.Slider(
95
  minimum=1,
 
98
  label="DDPM Sampling Steps πŸ”„ (the higher the number of steps the higher the quality of the images)",
99
  value=50,
100
  )
101
+ show_example = gr.Button(value="Show Example Input ")
102
 
103
  with gr.Row():
104
+ generate_button = gr.Button(value="Paint 🎨 ")
105
  with gr.Row():
106
  generate_info = gr.Markdown(
107
  "<p style='text-align: center; font-size: 16px;'>"
 
109
  "</p>"
110
  )
111
 
112
+ show_example.click(
113
+ show_example_fn,
114
+ inputs=[],
115
+ outputs=[sketch_input, scribbles_input],
116
+ concurrency_limit=1,
117
+ trigger_mode="once",
118
+ )
119
+
120
  generate_button.click(
121
  process_images,
122
  inputs=[
 
132
  )
133
 
134
  if __name__ == "__main__":
135
+ demo.launch()
examples/scribbles/detailed.png ADDED
examples/scribbles/test_purple_scarf.png ADDED
examples/scribbles/test_red_scarf.png ADDED
examples/sketch.png ADDED