lixiang46 commited on
Commit
f69cd15
1 Parent(s): fe70090
.gitattributes CHANGED
@@ -33,3 +33,6 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
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  *.zip filter=lfs diff=lfs merge=lfs -text
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  *.zst filter=lfs diff=lfs merge=lfs -text
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  *tfevents* filter=lfs diff=lfs merge=lfs -text
 
 
 
 
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  *.zip filter=lfs diff=lfs merge=lfs -text
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  *.zst filter=lfs diff=lfs merge=lfs -text
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  *tfevents* filter=lfs diff=lfs merge=lfs -text
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+ assets/cloth filter=lfs diff=lfs merge=lfs -text
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+ assets/human filter=lfs diff=lfs merge=lfs -text
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+ assets/title.md filter=lfs diff=lfs merge=lfs -text
README.md CHANGED
@@ -2,9 +2,9 @@
2
  title: Kolors Tryon
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  emoji: 🖼
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  colorFrom: purple
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- colorTo: red
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  sdk: gradio
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- sdk_version: 4.26.0
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  app_file: app.py
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  pinned: false
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  license: apache-2.0
 
2
  title: Kolors Tryon
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  emoji: 🖼
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  colorFrom: purple
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+ colorTo: gray
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  sdk: gradio
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+ sdk_version: 4.38.1
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  app_file: app.py
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  pinned: false
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  license: apache-2.0
app.py CHANGED
@@ -1,146 +1,71 @@
 
 
 
 
1
  import gradio as gr
2
  import numpy as np
3
  import random
4
- from diffusers import DiffusionPipeline
5
- import torch
6
 
7
- device = "cuda" if torch.cuda.is_available() else "cpu"
8
 
9
- if torch.cuda.is_available():
10
- torch.cuda.max_memory_allocated(device=device)
11
- pipe = DiffusionPipeline.from_pretrained("stabilityai/sdxl-turbo", torch_dtype=torch.float16, variant="fp16", use_safetensors=True)
12
- pipe.enable_xformers_memory_efficient_attention()
13
- pipe = pipe.to(device)
14
- else:
15
- pipe = DiffusionPipeline.from_pretrained("stabilityai/sdxl-turbo", use_safetensors=True)
16
- pipe = pipe.to(device)
17
 
18
- MAX_SEED = np.iinfo(np.int32).max
19
- MAX_IMAGE_SIZE = 1024
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-
21
- def infer(prompt, negative_prompt, seed, randomize_seed, width, height, guidance_scale, num_inference_steps):
22
-
23
- if randomize_seed:
24
- seed = random.randint(0, MAX_SEED)
25
-
26
- generator = torch.Generator().manual_seed(seed)
27
-
28
- image = pipe(
29
- prompt = prompt,
30
- negative_prompt = negative_prompt,
31
- guidance_scale = guidance_scale,
32
- num_inference_steps = num_inference_steps,
33
- width = width,
34
- height = height,
35
- generator = generator
36
- ).images[0]
37
 
38
- return image
39
 
40
- examples = [
41
- "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k",
42
- "An astronaut riding a green horse",
43
- "A delicious ceviche cheesecake slice",
44
- ]
45
 
46
  css="""
47
- #col-container {
 
 
 
 
48
  margin: 0 auto;
49
- max-width: 520px;
 
 
 
50
  }
51
  """
52
 
53
- if torch.cuda.is_available():
54
- power_device = "GPU"
55
- else:
56
- power_device = "CPU"
57
 
58
- with gr.Blocks(css=css) as demo:
59
-
60
- with gr.Column(elem_id="col-container"):
61
- gr.Markdown(f"""
62
- # Text-to-Image Gradio Template
63
- Currently running on {power_device}.
64
- """)
65
-
66
- with gr.Row():
67
-
68
- prompt = gr.Text(
69
- label="Prompt",
70
- show_label=False,
71
- max_lines=1,
72
- placeholder="Enter your prompt",
73
- container=False,
74
  )
75
-
76
- run_button = gr.Button("Run", scale=0)
77
-
78
- result = gr.Image(label="Result", show_label=False)
 
 
 
 
 
79
 
80
- with gr.Accordion("Advanced Settings", open=False):
81
-
82
- negative_prompt = gr.Text(
83
- label="Negative prompt",
84
- max_lines=1,
85
- placeholder="Enter a negative prompt",
86
- visible=False,
87
- )
88
-
89
- seed = gr.Slider(
90
- label="Seed",
91
- minimum=0,
92
- maximum=MAX_SEED,
93
- step=1,
94
- value=0,
95
- )
96
-
97
- randomize_seed = gr.Checkbox(label="Randomize seed", value=True)
98
-
99
- with gr.Row():
100
-
101
- width = gr.Slider(
102
- label="Width",
103
- minimum=256,
104
- maximum=MAX_IMAGE_SIZE,
105
- step=32,
106
- value=512,
107
- )
108
-
109
- height = gr.Slider(
110
- label="Height",
111
- minimum=256,
112
- maximum=MAX_IMAGE_SIZE,
113
- step=32,
114
- value=512,
115
- )
116
-
117
  with gr.Row():
118
-
119
- guidance_scale = gr.Slider(
120
- label="Guidance scale",
121
- minimum=0.0,
122
- maximum=10.0,
123
- step=0.1,
124
- value=0.0,
125
- )
126
-
127
- num_inference_steps = gr.Slider(
128
- label="Number of inference steps",
129
- minimum=1,
130
- maximum=12,
131
- step=1,
132
- value=2,
133
- )
134
-
135
- gr.Examples(
136
- examples = examples,
137
- inputs = [prompt]
138
- )
139
 
140
- run_button.click(
141
- fn = infer,
142
- inputs = [prompt, negative_prompt, seed, randomize_seed, width, height, guidance_scale, num_inference_steps],
143
- outputs = [result]
144
- )
145
 
146
- demo.queue().launch()
 
1
+ import sys
2
+ import os
3
+ import io
4
+ from PIL import Image
5
  import gradio as gr
6
  import numpy as np
7
  import random
 
 
8
 
9
+ example_path = os.path.join(os.path.dirname(__file__), 'assets')
10
 
11
+ MAX_SEED = 999999
 
 
 
 
 
 
 
12
 
13
+ def start_tryon(imgs, garm_img, garment_des, seed):
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
14
 
15
+ return None
16
 
17
+ garm_list = os.listdir(os.path.join(example_path,"cloth"))
18
+ garm_list_path = [os.path.join(example_path,"cloth",garm) for garm in garm_list]
19
+
20
+ human_list = os.listdir(os.path.join(example_path,"human"))
21
+ human_list_path = [os.path.join(example_path,"human",human) for human in human_list]
22
 
23
  css="""
24
+ #col-left {
25
+ margin: 0 auto;
26
+ max-width: 600px;
27
+ }
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+ #col-right {
29
  margin: 0 auto;
30
+ max-width: 750px;
31
+ }
32
+ #button {
33
+ color: blue;
34
  }
35
  """
36
 
37
+ def load_description(fp):
38
+ with open(fp, 'r', encoding='utf-8') as f:
39
+ content = f.read()
40
+ return content
41
 
42
+ with gr.Blocks(css=css) as Tryon:
43
+ gr.HTML(load_description("assets/title.md"))
44
+ with gr.Row():
45
+ with gr.Column():
46
+ imgs = gr.Image(label="Person image", sources='upload', type="pil")
47
+ # category = gr.Dropdown(label="Garment category", choices=['upper_body', 'lower_body', 'dresses'], value="upper_body")
48
+ example = gr.Examples(
49
+ inputs=imgs,
50
+ examples_per_page=10,
51
+ examples=human_list_path
 
 
 
 
 
 
52
  )
53
+ with gr.Column():
54
+ garm_img = gr.Image(label="Garment image", sources='upload', type="pil")
55
+ example = gr.Examples(
56
+ inputs=garm_img,
57
+ examples_per_page=8,
58
+ examples=garm_list_path)
59
+ with gr.Column():
60
+ image_out = gr.Image(label="Output", elem_id="output-img",show_share_button=False)
61
+ try_button = gr.Button(value="Try-on")
62
 
63
+
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+ with gr.Column():
65
+ with gr.Accordion(label="Advanced Settings", open=False):
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
66
  with gr.Row():
67
+ seed = gr.Number(label="Seed", minimum=-1, maximum=2147483647, step=1, value=None)
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
68
 
69
+ try_button.click(fn=start_tryon, inputs=[imgs, garm_img, seed], outputs=[image_out], api_name='tryon')
 
 
 
 
70
 
71
+ Tryon.queue(max_size=10).launch()
assets/cloth/04469_00.jpg ADDED
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assets/human/00034_00.jpg ADDED
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assets/human/Jensen.jpeg ADDED
assets/human/sam1 (1).jpg ADDED
assets/human/taylor-.jpg ADDED
assets/human/will1 (1).jpg ADDED
assets/title.md ADDED
@@ -0,0 +1,3 @@
 
 
 
 
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+ version https://git-lfs.github.com/spec/v1
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+ oid sha256:ee7fff5b3874ec80927627cdec9b2e5773cf257952b81fd280c4458993dc1894
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+ size 598