File size: 9,585 Bytes
34c7716
a6aa98d
 
 
 
 
34c7716
279a332
5e3d086
 
 
 
 
 
 
 
 
3827853
a6aa98d
 
 
140aeb5
 
 
 
 
 
a2ef80f
 
140aeb5
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
34c7716
140aeb5
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
f11b4d9
34c7716
a6aa98d
 
 
34c7716
 
 
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
import gradio as gr
from model import models
from multit2i import (load_models, infer_fn, infer_rand_fn, save_gallery,
    change_model, warm_model, get_model_info_md, loaded_models,
    get_positive_prefix, get_positive_suffix, get_negative_prefix, get_negative_suffix,
    get_recom_prompt_type, set_recom_prompt_preset, get_tag_type, randomize_seed, translate_to_en)


max_images = 8
MAX_SEED = 2**32-1
load_models(models)

css = """
.model_info { text-align: center; }
.output { width=112px; height=112px; max_width=112px; max_height=112px; !important; }
.gallery { min_width=512px; min_height=512px; max_height=1024px; !important; }
"""

with gr.Blocks(theme="NoCrypt/miku@>=1.2.2", fill_width=True, css=css) as demo:
    with gr.Tab("Image Generator"):
        with gr.Row():
            with gr.Column(scale=10): 
                with gr.Group():
                    prompt = gr.Text(label="Prompt", lines=2, max_lines=8, placeholder="1girl, solo, ...", show_copy_button=True)
                    with gr.Accordion("Advanced options", open=False):
                        neg_prompt = gr.Text(label="Negative Prompt", lines=1, max_lines=8, placeholder="")                      
                        with gr.Row():
                            width = gr.Slider(label="Width", info="If 0, the default value is used.", maximum=2048, step=32, value=0)
                            height = gr.Slider(label="Height", info="If 0, the default value is used.", maximum=2048, step=32, value=0)
                            steps = gr.Slider(label="Number of inference steps", info="If 0, the default value is used.", maximum=100, step=1, value=0)
                        with gr.Row():
                            cfg = gr.Slider(label="Guidance scale", info="If 0, the default value is used.", maximum=30.0, step=0.1, value=0)
                            seed = gr.Slider(label="Seed", info="Randomize Seed if -1.", minimum=-1, maximum=MAX_SEED, step=1, value=-1)
                            seed_rand = gr.Button("Randomize Seed 🎲", size="sm", variant="secondary")
                        recom_prompt_preset = gr.Radio(label="Set Presets", choices=get_recom_prompt_type(), value="Common")
                        with gr.Row():
                            positive_prefix = gr.CheckboxGroup(label="Use Positive Prefix", choices=get_positive_prefix(), value=[])
                            positive_suffix = gr.CheckboxGroup(label="Use Positive Suffix", choices=get_positive_suffix(), value=["Common"])
                            negative_prefix = gr.CheckboxGroup(label="Use Negative Prefix", choices=get_negative_prefix(), value=[])
                            negative_suffix = gr.CheckboxGroup(label="Use Negative Suffix", choices=get_negative_suffix(), value=["Common"])
                    with gr.Row():
                        image_num = gr.Slider(label="Number of images", minimum=1, maximum=max_images, value=1, step=1, interactive=True, scale=2)
                        trans_prompt = gr.Button(value="Translate πŸ“", variant="secondary", size="sm", scale=2)
                        clear_prompt = gr.Button(value="Clear πŸ—‘οΈ", variant="secondary", size="sm", scale=1)
                with gr.Row():
                    run_button = gr.Button("Generate Image", variant="primary", scale=8)
                    random_button = gr.Button("Random Model 🎲", variant="secondary", scale=3)
                    stop_button = gr.Button('Stop', interactive=False, variant="stop", scale=1)
                 
                with gr.Group():
                    model_name = gr.Dropdown(label="Select Model", choices=list(loaded_models.keys()), value=list(loaded_models.keys())[0], allow_custom_value=True)
                    model_info = gr.Markdown(value=get_model_info_md(list(loaded_models.keys())[0]), elem_classes="model_info")
            with gr.Column(scale=10): 
                with gr.Group():
                    with gr.Row():
                        output = [gr.Image(label='', elem_classes="output", type="filepath", format="png",
                                show_download_button=True, show_share_button=False, show_label=False,
                                interactive=False, min_width=80, visible=True, width=112, height=112) for _ in range(max_images)]
                with gr.Group():
                    results = gr.Gallery(label="Gallery", elem_classes="gallery", interactive=False, show_download_button=True, show_share_button=False,
                                        container=True, format="png", object_fit="cover", columns=2, rows=2)
                    image_files = gr.Files(label="Download", interactive=False)
                    clear_results = gr.Button("Clear Gallery / Download πŸ—‘οΈ", variant="secondary")
        with gr.Column():
            examples = gr.Examples(
                examples = [
                    ["souryuu asuka langley, 1girl, neon genesis evangelion, plugsuit, pilot suit, red bodysuit, sitting, crossing legs, black eye patch, cat hat, throne, symmetrical, looking down, from bottom, looking at viewer, outdoors"],
                    ["sailor moon, magical girl transformation, sparkles and ribbons, soft pastel colors, crescent moon motif, starry night sky background, shoujo manga style"],
                    ["kafuu chino, 1girl, solo"],
                    ["1girl"],
                    ["beautiful sunset"],
                ],
                inputs=[prompt],
                cache_examples=False,
            )
    with gr.Tab("PNG Info"):
        def extract_exif_data(image):
            if image is None: return ""
            try:
                metadata_keys = ['parameters', 'metadata', 'prompt', 'Comment']
                for key in metadata_keys:
                    if key in image.info:
                        return image.info[key]
                return str(image.info)
            except Exception as e:
                return f"Error extracting metadata: {str(e)}"
        with gr.Row():
            with gr.Column():
                image_metadata = gr.Image(label="Image with metadata", type="pil", sources=["upload"])
            with gr.Column():
                result_metadata = gr.Textbox(label="Metadata", show_label=True, show_copy_button=True, interactive=False, container=True, max_lines=99)

                image_metadata.change(
                    fn=extract_exif_data,
                    inputs=[image_metadata],
                    outputs=[result_metadata],
                )
    gr.Markdown(
        f"""This demo was created in reference to the following demos.<br>
[Nymbo/Flood](https://huggingface.co/spaces/Nymbo/Flood), 
[Yntec/ToyWorldXL](https://huggingface.co/spaces/Yntec/ToyWorldXL), 
[Yntec/Diffusion80XX](https://huggingface.co/spaces/Yntec/Diffusion80XX).
            """
    )
    gr.DuplicateButton(value="Duplicate Space")
    gr.Markdown(f"Just a few edits to *model.py* are all it takes to complete your own collection.")

    gr.on(triggers=[run_button.click, prompt.submit, random_button.click], fn=lambda: gr.update(interactive=True), inputs=None, outputs=stop_button, show_api=False)
    model_name.change(change_model, [model_name], [model_info], queue=True, show_api=True)\
    .success(warm_model, [model_name], None, queue=True, show_api=True)
    for i, o in enumerate(output):
        img_i = gr.Number(i, visible=False)
        image_num.change(lambda i, n: gr.update(visible = (i < n)), [img_i, image_num], o, show_api=True)
        gen_event = gr.on(triggers=[run_button.click, prompt.submit],
         fn=lambda i, n, m, t1, t2, n1, n2, n3, n4, n5, l1, l2, l3, l4: infer_fn(m, t1, t2, n1, n2, n3, n4, n5, l1, l2, l3, l4) if (i < n) else None,
         inputs=[img_i, image_num, model_name, prompt, neg_prompt, height, width, steps, cfg, seed,
                  positive_prefix, positive_suffix, negative_prefix, negative_suffix],
         outputs=[o], queue=True, show_api=False) # Be sure to delete ", queue=False" when activating the stop button
        gen_event2 = gr.on(triggers=[random_button.click],
         fn=lambda i, n, m, t1, t2, n1, n2, n3, n4, n5, l1, l2, l3, l4: infer_rand_fn(m, t1, t2, n1, n2, n3, n4, n5, l1, l2, l3, l4) if (i < n) else None,
         inputs=[img_i, image_num, model_name, prompt, neg_prompt, height, width, steps, cfg, seed,
                  positive_prefix, positive_suffix, negative_prefix, negative_suffix],
         outputs=[o], queue=True, show_api=False) # Be sure to delete ", queue=False" when activating the stop button
        o.change(save_gallery, [o, results], [results, image_files], show_api=False)
        stop_button.click(lambda: gr.update(interactive=False), None, stop_button, cancels=[gen_event, gen_event2], show_api=False)

    clear_prompt.click(lambda: (None, None), None, [prompt, neg_prompt], queue=True, show_api=True)
    clear_results.click(lambda: (None, None), None, [results, image_files], queue=True, show_api=True)
    recom_prompt_preset.change(set_recom_prompt_preset, [recom_prompt_preset],
     [positive_prefix, positive_suffix, negative_prefix, negative_suffix], queue=True, show_api=True)
    seed_rand.click(randomize_seed, None, [seed], queue=True, show_api=True)
    trans_prompt.click(translate_to_en, [prompt], [prompt], queue=True, show_api=True)\
    .then(translate_to_en, [neg_prompt], [neg_prompt], queue=True, show_api=True)




demo.queue(default_concurrency_limit=240, max_size=240)
demo.launch(max_threads=400, ssr_mode=True)
# https://github.com/gradio-app/gradio/issues/6339

demo.queue(concurrency_count=50)
demo.launch()