File size: 5,986 Bytes
c30a8f6
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
93c0f46
 
 
 
 
 
 
e19cee7
 
 
 
 
93c0f46
 
 
 
 
c30a8f6
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
e19cee7
c30a8f6
 
 
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
144
145
146
147
148
149
150
151
152
153
154
import gradio as gr
import numpy as np
import config

from feifeilib.feifeichat import feifeichat
from feifeilib.feifeitexttoimg import feifeitexttoimg
from feifeilib.feifeiflorence import feifeiflorence

MAX_SEED = np.iinfo(np.int32).max
MAX_IMAGE_SIZE = 4096

css = """

#col-container {

    width: auto;

    height: 750px;

}

"""


def create_ui():
    with gr.Blocks(css=css) as FeiFei:
        with gr.Row():
            with gr.Column(scale=1):
                with gr.Tab("Generator"):
                    prompt = gr.Text(
                        label="Prompt",
                        show_label=False,
                        placeholder="Enter your prompt",
                        max_lines=12,
                        container=False,
                    )
                    run_button = gr.Button("Run")
                    result = gr.Image(label="Result",
                                      show_label=False,
                                      interactive=False)

                    with gr.Accordion("Advanced Settings", open=False):
                        seed = gr.Slider(
                            label="Seed",
                            minimum=0,
                            maximum=MAX_SEED,
                            step=1,
                            value=0,
                        )

                        randomize_seed = gr.Checkbox(label="Randomize seed",
                                                     value=True)

                        with gr.Row():
                            width = gr.Slider(
                                label="Width",
                                minimum=256,
                                maximum=MAX_IMAGE_SIZE,
                                step=64,
                                value=896,
                            )

                            height = gr.Slider(
                                label="Height",
                                minimum=256,
                                maximum=MAX_IMAGE_SIZE,
                                step=64,
                                value=1152,
                            )

                        with gr.Row():
                            num_inference_steps = gr.Slider(
                                label="Number of inference steps",
                                minimum=1,
                                maximum=50,
                                step=1,
                                value=4,
                            )
                            guidancescale = gr.Slider(
                                label="Guidance scale",
                                minimum=0,
                                maximum=10,
                                step=0.1,
                                value=3.5,
                            )
                            num_strength = gr.Slider(
                                label="strength",
                                minimum=0,
                                maximum=2,
                                step=0.01,
                                value=0.35,
                            )

                with gr.Tab("Styles"):
                    quality_select = gr.Checkbox(label="high quality")
                    sharpened_select = gr.Checkbox(label="Sharpened")
                    FooocusExpansion_select = gr.Checkbox(
                        label="FooocusExpansion")
                    styles_name = [
                        style["name"] for style in config.style_list
                    ]
                    styles_Radio = gr.Dropdown(styles_name,
                                               label="Styles",
                                               multiselect=True)
                with gr.Tab("Florence-2"):

                    input_img = gr.Image(label="Input Picture",
                                         show_label=False)

                    florence_btn = gr.Button(value="Florence")

                    output_text = gr.Textbox(label="Output Text",
                                             max_lines=12,
                                             show_label=False,
                                             container=False)
                    output_size = gr.Textbox(label="Output size",
                                             max_lines=1,
                                             show_label=False,
                                             container=False)
                    output_img = gr.Image(label="Input Picture",
                                          interactive=False,
                                          show_label=False)
            with gr.Column(scale=3, elem_id="col-container"):
                gr.ChatInterface(
                    feifeichat,
                    type="messages",
                    multimodal=True,
                    additional_inputs=[
                        gr.Checkbox(label="Feifei"),
                    ],
                )

        run_button.click(
            fn=feifeitexttoimg,  # Function to run for this button
            inputs=[
                prompt,
                quality_select,
                sharpened_select,
                styles_Radio,
                FooocusExpansion_select,
                seed,
                randomize_seed,
                width,
                height,
                num_inference_steps,
                guidancescale,
                num_strength,
            ],
            outputs=[result, seed],
        )

        florence_btn.click(
            fn=feifeiflorence,  # Function to run when the button is clicked
            inputs=[input_img],  # Input components for the function
            outputs=[output_text, output_size,
                     output_img],  # Output component for the function
        )
    return FeiFei