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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:
model_choice2 = gr.Dropdown(models, label = 'Choose model', value = models[0], filterable = False)
txt_input2 = gr.Textbox(label = 'Prompt text')
max_images = 6
num_images = gr.Slider(1, max_images, value = max_images, step = 1, label = 'Number of images')
gen_button2 = gr.Button('Generate')
stop_button2 = gr.Button('Stop', variant = 'secondary', interactive = False)
gen_button2.click(lambda s: gr.update(interactive = True), None, stop_button2)
with gr.Row():
output2 = [gr.Image(label = '') for _ in range(max_images)]
for i, o in enumerate(output2):
img_i = gr.Number(i, visible = False)
num_images.change(lambda i, n: gr.update(visible = (i < n)), [img_i, num_images], o)
gen_event2 = gen_button2.click(lambda i, n, m, t: gen_fn(m, t) if (i < n) else None, [img_i, num_images, model_choice2, txt_input2], o)
stop_button2.click(lambda s: gr.update(interactive = False), None, stop_button2, cancels = [gen_event2])
demo.queue(concurrency_count = 36)
demo.launch() |