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3f65faf
1
Parent(s):
17abe49
Update app.py
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app.py
CHANGED
@@ -2,54 +2,60 @@ import gradio as gr
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from random import randint
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from all_models import models
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global models_load
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models_load = {}
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for model in models:
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num_models = 150
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default_models = models[:num_models]
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def extend_choices(choices):
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return choices + (num_models - len(choices))
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def update_imgbox(choices):
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choices_plus = extend_choices(choices)
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def
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if model_str == 'NA':
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return None
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noise = str(
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with gr.Blocks() as demo:
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with gr.Tab('The Dream'):
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txt_input = gr.Textbox(label
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gen_button = gr.Button('Generate up to 150 images in up to 3 minutes total')
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stop_button = gr.Button('Stop', variant
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gr.HTML(
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<div style="text-align: center; max-width: 1200px; margin: 0 auto;">
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<div>
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<body>
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@@ -58,27 +64,42 @@ with gr.Blocks() as demo:
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</body>
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</div>
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</div>
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with gr.Row():
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output = [gr.Image(label
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current_models = [gr.Textbox(m, visible
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for m, o in zip(current_models, output):
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with gr.Accordion('Model selection'):
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model_choice = gr.CheckboxGroup(
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model_choice.change(update_imgbox, model_choice, output)
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model_choice.change(extend_choices, model_choice, current_models)
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with gr.Row():
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gr.HTML(
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)
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demo.queue(concurrency_count
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demo.launch()
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from random import randint
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from all_models import models
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# Função para carregar os modelos e armazená-los em um dicionário
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def load_models(models):
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models_dict = {}
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for model in models:
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try:
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# Tente carregar o modelo e armazená-lo no dicionário
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model_obj = gr.load(f'models/{model}')
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models_dict[model] = model_obj
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except Exception as e:
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# Lidar com exceções ao carregar o modelo
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print(f"Erro ao carregar o modelo {model}: {e}")
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models_dict[model] = gr.Interface(lambda txt: None, ['text'], ['image'])
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return models_dict
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# Carregar os modelos e armazená-los na variável global
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models_load = load_models(models)
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num_models = 150
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default_models = models[:num_models]
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# Função para estender as escolhas com 'NA' se necessário
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def extend_choices(choices):
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return choices + ['NA'] * (num_models - len(choices))
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# Função para atualizar a caixa de imagens com base nas escolhas
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def update_imgbox(choices, output):
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choices_plus = extend_choices(choices)
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for m, o in zip(choices_plus, output):
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o.label = m
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o.visible = (m != 'NA')
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# Função para gerar imagens com base no modelo e prompt selecionados
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def generate_images(model_str, prompt, negative_prompt):
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if model_str == 'NA':
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return None
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noise = str(randint(0, 99999999999))
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prompt_with_noise = f'{prompt} {noise}'
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if negative_prompt:
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prompt_with_noise += ' Negative'
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return models_load[model_str](prompt_with_noise)
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# Interface Gradio
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with gr.Blocks() as demo:
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with gr.Tab('The Dream'):
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txt_input = gr.Textbox(label='Your prompt:', lines=4).style(container=False, min_width=1200)
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negative_prompt = gr.Checkbox(label='Negative Prompt', value=False)
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gen_button = gr.Button('Generate up to 150 images in up to 3 minutes total')
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stop_button = gr.Button('Stop', variant='secondary', interactive=False)
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# Evento de clique para iniciar a geração de imagens
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gen_button.click(lambda s: gr.update(interactive=True), None, stop_button)
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gr.HTML(
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"""
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<div style="text-align: center; max-width: 1200px; margin: 0 auto;">
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<div>
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<body>
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</body>
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</div>
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</div>
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"""
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)
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with gr.Row():
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output = [gr.Image(label=m, min_width=512) for m in default_models]
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current_models = [gr.Textbox(m, visible=False) for m in default_models]
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for m, o in zip(current_models, output):
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# Evento de clique para gerar imagens para cada modelo selecionado
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gen_event = gen_button.click(generate_images, [m, txt_input, negative_prompt], o)
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# Evento de clique para parar a geração de imagens
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stop_button.click(lambda s: gr.update(interactive=False), None, stop_button, cancels=[gen_event])
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with gr.Accordion('Model selection'):
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model_choice = gr.CheckboxGroup(
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models,
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label=f'Choose up to {num_models} different models from the available options!',
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value=default_models,
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multiselect=True,
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max_choices=num_models,
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interactive=True,
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filterable=False
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)
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# Evento de mudança para atualizar a caixa de imagens com base nas escolhas
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model_choice.change(update_imgbox, model_choice, output)
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model_choice.change(extend_choices, model_choice, current_models)
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with gr.Row():
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gr.HTML(
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"""
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<div class="footer">
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<p> Based on the <a href="https://huggingface.co/spaces/derwahnsinn/TestGen">TestGen</a> Space by derwahnsinn, the <a href="https://huggingface.co/spaces/RdnUser77/SpacIO_v1">SpacIO</a> Space by RdnUser77 and Omnibus's Maximum Multiplier!
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</p>
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"""
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)
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demo.queue(concurrency_count=200)
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demo.launch()
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