File size: 4,943 Bytes
77a862a
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
ba36264
77a862a
 
ba36264
 
 
 
 
 
77a862a
 
 
 
 
ba36264
77a862a
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
864da09
77a862a
 
 
 
 
 
 
864da09
77a862a
 
 
ba36264
77a862a
864da09
 
77a862a
 
3168fad
864da09
77a862a
864da09
77a862a
3168fad
77a862a
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
3168fad
77a862a
 
 
 
ba36264
77a862a
 
 
 
864da09
 
 
 
 
77a862a
 
 
864da09
 
77a862a
 
 
 
864da09
77a862a
 
 
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
155
import gradio as gr
# import os
# import sys
# from pathlib import Path
import time

models =[
    "CompVis/stable-diffusion-v1-4",
    "runwayml/stable-diffusion-v1-5",
    "prompthero/openjourney",
    "stabilityai/stable-diffusion-2-1",
    "stabilityai/stable-diffusion-2-1-base",
    "andite/anything-v4.0",
    "Linaqruf/anything-v3.0",
    "eimiss/EimisAnimeDiffusion_1.0v",
    "nitrosocke/Nitro-Diffusion",
    "wavymulder/portraitplus",
    "22h/vintedois-diffusion-v0-1",
    "dreamlike-art/dreamlike-photoreal-2.0",
    "dreamlike-art/dreamlike-diffusion-1.0",
    "wavymulder/Analog-Diffusion",
    "nitrosocke/redshift-diffusion",
    "claudfuen/photorealistic-fuen-v1",
    "prompthero/openjourney-v2",
    "johnslegers/epic-diffusion",
    "nitrosocke/Arcane-Diffusion",
    "darkstorm2150/Protogen_x5.8_Official_Release",
]


model_functions = {}
model_idx = 1
for model_path in models:
    try:
        model_functions[model_idx] = gr.Interface.load(f"models/{model_path}", live=False, preprocess=True, postprocess=False)
    except Exception as error:
        def the_fn(txt):
            return None
        model_functions[model_idx] = gr.Interface(fn=the_fn, inputs=["text"], outputs=["image"])
    model_idx+=1


def send_it_idx(idx):
    def send_it_fn(prompt):
        output = (model_functions.get(str(idx)) or model_functions.get(str(1)))(prompt)
        return output
    return send_it_fn

def get_prompts(prompt_text):
    return prompt_text

def clear_it(val):
    if int(val) != 0:
        val = 0
    else:
        val = 0
        pass
    return val

def all_task_end(cnt,t_stamp):
    to = t_stamp + 60
    et = time.time()
    if et > to and t_stamp != 0:
        d = gr.update(value=0)
        tog = gr.update(value=1)
        #print(f'to: {to}  et: {et}')
    else:
        if cnt != 0:
            d = gr.update(value=et)
        else:
            d = gr.update(value=0)
        tog = gr.update(value=0)
        #print (f'passing:  to: {to}  et: {et}')
        pass
    return d, tog

def all_task_start():
    print("\n\n\n\n\n\n\n")
    t = time.gmtime()
    t_stamp = time.time()
    current_time = time.strftime("%H:%M:%S", t)
    return gr.update(value=t_stamp), gr.update(value=t_stamp), gr.update(value=0)

def clear_fn():
    nn = len(models)
    return tuple([None, *[None for _ in range(nn)]])



with gr.Blocks(title="SD Models") as my_interface:
    with gr.Column(scale=12):
        # with gr.Row():
        #     gr.Markdown("""- Primary prompt: 你想画的内容(英文单词,如 a cat, 加英文逗号效果更好;点 Improve 按钮进行完善)\n- Real prompt: 完善后的提示词,出现后再点右边的 Run 按钮开始运行""")
        with gr.Row():
            with gr.Column(scale=6):
                primary_prompt=gr.Textbox(label="Prompt", value="happy dogs")
                # real_prompt=gr.Textbox(label="Real prompt")
            with gr.Column(scale=6):
                # improve_prompts_btn=gr.Button("Improve")
                with gr.Row():
                    run=gr.Button("Run",variant="primary")
                    clear_btn=gr.Button("Clear")
        with gr.Row():
            sd_outputs = {}
            model_idx = 1
            for model_path in models:
                with gr.Column(scale=3, min_width=320):
                    with gr.Box():
                        sd_outputs[model_idx] = gr.Image(label=model_path)
                    pass
                model_idx += 1
                pass
            pass

        with gr.Row(visible=False):
            start_box=gr.Number(interactive=False)
            end_box=gr.Number(interactive=False)
            tog_box=gr.Textbox(value=0,interactive=False)

        start_box.change(
            all_task_end,
            [start_box, end_box],
            [start_box, tog_box],
            every=1,
            show_progress=False)

        primary_prompt.submit(all_task_start, None, [start_box, end_box, tog_box])
        run.click(all_task_start, None, [start_box, end_box, tog_box])
        runs_dict = {}
        model_idx = 1
        for model_path in models:
            runs_dict[model_idx] = run.click(model_functions[model_idx], inputs=[primary_prompt], outputs=[sd_outputs[model_idx]])
            model_idx += 1
            pass
        pass

        # improve_prompts_btn_clicked=improve_prompts_btn.click(
        #     get_prompts,
        #     inputs=[primary_prompt],
        #     outputs=[primary_prompt],
        #     cancels=list(runs_dict.values()))
        clear_btn.click(
            clear_fn,
            None,
            [primary_prompt, *list(sd_outputs.values())],
            cancels=[*list(runs_dict.values())])
        tog_box.change(
            clear_it,
            tog_box,
            tog_box,
            cancels=[*list(runs_dict.values())])

my_interface.queue(concurrency_count=600, status_update_rate=1)
my_interface.launch(inline=True, show_api=False)