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import gradio as gr
from random import randint
from all_models import models
def load_fn(models):
global models_load
models_load = {}
for model in models:
if model not in models_load.keys():
try:
m = gr.load(f'models/{model}')
except Exception as error:
m = gr.Interface(lambda txt: None, ['text'], ['image'])
models_load.update({model: m})
load_fn(models)
num_models = 6
default_models = models[:num_models]
def extend_choices(choices):
return choices + (num_models - len(choices)) * ['NA']
def update_imgbox(choices):
choices_plus = extend_choices(choices)
return [gr.Image(None, label = m, visible = (m != 'NA')) for m in choices_plus]
def gen_fn(model_str, prompt):
if model_str == 'NA':
return None
noise = str(randint(0, 99999999999))
return models_load[model_str](f'{prompt} {noise}')
with gr.Blocks() as demo:
with gr.Tab('Multiple models'):
with gr.Accordion('Model selection'):
model_choice = gr.Dropdown(models, label = f'Choose up to {num_models} different models', value = default_models, multiselect = True, max_choices = num_models, interactive = True)
txt_input = gr.Textbox(label = 'Prompt text')
gen_button = gr.Button('Generate')
with gr.Row():
output = [gr.Image(label = m) for m in default_models]
current_models = [gr.Textbox(m, visible = False) for m in default_models]
model_choice.change(update_imgbox, model_choice, output)
model_choice.change(extend_choices, model_choice, current_models)
for m, o in zip(current_models, output):
gen_button.click(gen_fn, [m, txt_input], o)
with gr.Tab('Single model'):
model_choice2 = gr.Dropdown(models, label = 'Choose model', value = models[0], filterable = False)
txt_input2 = gr.Textbox(label = 'Prompt text')
gen_button2 = gr.Button('Generate')
with gr.Row():
num_images = 6
output2 = [gr.Image(label = '') for _ in range(num_images)]
for o in output2:
gen_button2.click(gen_fn, [model_choice2, txt_input2], o)
demo.queue(concurrency_count = 36)
demo.launch() |