File size: 3,083 Bytes
6fef025 f5b8400 6fef025 f5b8400 6fef025 f5b8400 6fef025 f5b8400 6fef025 f5b8400 6fef025 f5b8400 fc42fea 6fef025 f5b8400 d2777ff 1485f13 6fef025 f5b8400 6b70d61 8f8f343 3977ac5 8f8f343 3977ac5 8f8f343 654d3d1 6ce4171 654d3d1 f5b8400 |
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 |
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('') #str(randint(0, 99999999999))
return models_load[model_str](f'{prompt} {noise}')
with gr.Blocks() as demo:
with gr.Tab('The Dream'):
txt_input = gr.Textbox(label = 'Your prompt:', lines=4).style(container=False,min_width=1200)
gen_button = gr.Button('Generate up to 6 images in up to 3 minutes total')
stop_button = gr.Button('Stop', variant = 'secondary', interactive = False)
gen_button.click(lambda s: gr.update(interactive = True), None, stop_button)
gr.HTML(
"""
<div style="text-align: center; max-width: 1200px; margin: 0 auto;">
<div>
<body>
<div class="center"><p style="margin-bottom: 10px; color: #000000;">Scroll down to see more images and select models.</p>
</div>
</body>
</div>
</div>
"""
)
with gr.Row():
output = [gr.Image(label = m, min_width=480) for m in default_models]
current_models = [gr.Textbox(m, visible = False) for m in default_models]
for m, o in zip(current_models, output):
gen_event = gen_button.click(gen_fn, [m, txt_input], o)
stop_button.click(lambda s: gr.update(interactive = False), None, stop_button, cancels = [gen_event])
with gr.Accordion('Model selection'):
model_choice = gr.CheckboxGroup(models, label = f'Choose up to {num_models} different models from the 686 available!', value = default_models, multiselect = True, max_choices = num_models, interactive = True, filterable = False)
model_choice.change(update_imgbox, model_choice, output)
model_choice.change(extend_choices, model_choice, current_models)
with gr.Row():
gr.HTML(
"""
<div class="footer">
<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!
</p>
"""
)
demo.queue(concurrency_count = 200)
demo.launch() |