Spaces:
Running
Running
File size: 10,148 Bytes
b3f2e04 9405fcc 400833e 01de3f3 e9ee4ce ea4f9ff 9405fcc e95c543 9405fcc ea4f9ff 9405fcc e9ee4ce 9405fcc 02001b9 9405fcc ea4f9ff b7236f0 931a3c8 a29b766 9405fcc 07eca3d 2ba3409 9405fcc 2ba3409 9405fcc 7d6469d 636b6d7 2cbe8d3 636b6d7 a089483 636b6d7 a089483 b46ae9a 9405fcc edd0581 5a8de00 edd0581 4bb6bc1 a709435 c48d832 a601a45 b46ae9a bd650f6 b46ae9a bd650f6 b46ae9a ea4f9ff 4a7ad4a b46ae9a ea4f9ff b46ae9a a089483 8421023 a089483 25466a0 636b6d7 a089483 efec6dd a089483 6f9fd0f c84f54b 636b6d7 c84f54b 34903bd a089483 b46ae9a a601a45 b46ae9a a47abbb b46ae9a ea4f9ff 59e2eb4 b46ae9a 4a7ad4a bd650f6 4a7ad4a ea4f9ff a2459f1 9405fcc d0bf66f 9405fcc ea4f9ff |
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 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 |
import gradio as gr
from random import randint
from all_models import models
from externalmod import gr_Interface_load
import asyncio
import os
from threading import RLock
lock = RLock()
HF_TOKEN = os.environ.get("HF_TOKEN") if os.environ.get("HF_TOKEN") else None # If private or gated models aren't used, ENV setting is unnecessary.
def load_fn(models):
global models_load
models_load = {}
for model in models:
if model not in models_load.keys():
try:
m = gr_Interface_load(f'models/{model}', hf_token=HF_TOKEN)
except Exception as error:
print(error)
m = gr.Interface(lambda: None, ['text'], ['image'])
models_load.update({model: m})
load_fn(models)
num_models = 1
default_models = models[:num_models]
inference_timeout = 600
MAX_SEED=3999999999
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}')
#def gen_fnseed(model_str, prompt, useseed, **kwargs):
# kwargs = {}
# if model_str == 'NA':
# return None
# noise = str('') #str(randint(0, 99999999999))
# kwargs["seed"] = useseed
# return models_load[model_str](f'{prompt} {noise}', **kwargs)
async def infer(model_str, prompt, seed=1, timeout=inference_timeout):
from pathlib import Path
kwargs = {}
noise = ""
kwargs["seed"] = seed
task = asyncio.create_task(asyncio.to_thread(models_load[model_str].fn,
prompt=f'{prompt} {noise}', **kwargs, token=HF_TOKEN))
await asyncio.sleep(0)
try:
result = await asyncio.wait_for(task, timeout=timeout)
except (Exception, asyncio.TimeoutError) as e:
print(e)
print(f"Task timed out: {model_str}")
if not task.done(): task.cancel()
result = None
if task.done() and result is not None:
with lock:
png_path = "image.png"
result.save(png_path)
image = str(Path(png_path).resolve())
return image
return None
def gen_fnseed(model_str, prompt, seed=1):
if model_str == 'NA':
return None
try:
loop = asyncio.new_event_loop()
result = loop.run_until_complete(infer(model_str, prompt, seed, inference_timeout))
except (Exception, asyncio.CancelledError) as e:
print(e)
print(f"Task aborted: {model_str}")
result = None
finally:
loop.close()
return result
def gen_fnsix(model_str, prompt):
if model_str == 'NA':
return None
noisesix = str(randint(1941, 2023)) #str(randint(0, 99999999999))
return models_load[model_str](f'{prompt} {noisesix}')
with gr.Blocks() as demo:
gr.HTML(
"""
<div>
<p> <center><img src="https://huggingface.co/Yntec/OpenGenDiffusers/resolve/main/mpp.png" style="height:128px; width:469px; margin-top: -22px; margin-bottom: -64px;" span title="Free ai art image generator Printing Press"></center>
</p>
"""
)
gr.HTML(
"""
<div>
<p> <center>For more than 900 models visit the <a href="https://huggingface.co/spaces/Yntec/PrintingPress">Printing Press</a>!</center>
</p></div>
"""
)
with gr.Tab('One Image'):
model_choice = gr.Dropdown(models, label = f'Choose a model from the {len(models)} available! Try clearing the box and typing on it to filter them!', value = models[0], filterable = True)
txt_input = gr.Textbox(label = 'Your prompt:')
max_imagesone = 1
num_imagesone = gr.Slider(1, max_imagesone, value = max_imagesone, step = 1, label = 'Nobody gets to see this label so I can put here whatever I want!', visible = False)
gen_button = gr.Button('Generate')
#stop_button = gr.Button('Stop', variant = 'secondary', interactive = False)
gen_button.click(lambda s: gr.update(interactive = True), None)
with gr.Row():
output = [gr.Image(label = '') for _ in range(max_imagesone)]
for i, o in enumerate(output):
img_in = gr.Number(i, visible = False)
num_imagesone.change(lambda i, n: gr.update(visible = (i < n)), [img_in, num_imagesone], o, show_progress = False)
gen_event = gen_button.click(lambda i, n, m, t: gen_fn(m, t) if (i < n) else None, [img_in, num_imagesone, model_choice, txt_input], o, concurrency_limit=None, queue=False)
#stop_button.click(lambda s: gr.update(interactive = False), None, stop_button, cancels = [gen_event])
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, Omnibus's Maximum Multiplier, <a href="https://huggingface.co/spaces/Yntec/Diffusion60XX">Diffusion60XX</a> and <a href="https://huggingface.co/spaces/Yntec/ToyWorld">Toy World</a>!
</p>
"""
)
with gr.Tab('Seed it!'):
model_choiceseed = gr.Dropdown(models, label = f'Choose a model from the {len(models)} available! Try clearing the box and typing on it to filter them!', value = models[0], filterable = True)
txt_inputseed = gr.Textbox(label = 'Your prompt:')
seed = gr.Slider(label="Use a seed to replicate the same image later", info="Max 3999999999", minimum=0, maximum=MAX_SEED, step=1, value=1)
max_imagesseed = 1
num_imagesseed = gr.Slider(1, max_imagesone, value = max_imagesone, step = 1, label = 'One, because more would make it produce identical images with the seed', visible = False)
gen_buttonseed = gr.Button('Generate an image using the seed')
#stop_button = gr.Button('Stop', variant = 'secondary', interactive = False)
gen_button.click(lambda s: gr.update(interactive = True), None)
with gr.Row():
outputseed = [gr.Image(label = '') for _ in range(max_imagesseed)]
for i, o in enumerate(outputseed):
img_is = gr.Number(i, visible = False)
num_imagesseed.change(lambda i, n: gr.update(visible = (i < n)), [img_is, num_imagesseed], o, show_progress = False)
#gen_eventseed = gen_buttonseed.click(lambda i, n, m, t, n1: gen_fnseed(m, t, n1) if (i < n) else None, [img_is, num_imagesseed, model_choiceseed, txt_inputseed, useseed], o, concurrency_limit=None, queue=False)
gen_eventseed = gr.on(triggers=[gen_buttonseed.click, txt_inputseed.submit],
fn=lambda i, n, m, t, n1: gen_fnseed(m, t, n1) if (i < n) else None,
inputs=[img_is, num_imagesseed, model_choiceseed, txt_inputseed, seed], outputs=[o],
concurrency_limit=None, queue=False) # Be sure to delete ", queue=False" when activating the stop button
#stop_button.click(lambda s: gr.update(interactive = False), None, stop_button, cancels = [gen_event])
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, Omnibus's Maximum Multiplier, and <a href="https://huggingface.co/spaces/Yntec/ToyWorld">Toy World</a>!
</p>
"""
)
with gr.Tab('Up To Six'):
model_choice2 = gr.Dropdown(models, label = f'Choose a model from the {len(models)} available! Try clearing the box and typing on it to filter them!', value = models[0], filterable = True)
txt_input2 = gr.Textbox(label = 'Your prompt:')
max_images = 6
num_images = gr.Slider(1, max_images, value = max_images, step = 1, label = 'Number of images (if you want less than 6 decrease them slowly until they match the boxes below)')
gen_button2 = gr.Button('Generate up to 6 images in up to 3 minutes total')
#stop_button2 = gr.Button('Stop', variant = 'secondary', interactive = False)
gen_button2.click(lambda s: gr.update(interactive = True), None)
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 (they generate in a random order).</p>
</div>
</body>
</div>
</div>
"""
)
with gr.Column():
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, show_progress = False)
gen_event2 = gen_button2.click(lambda i, n, m, t: gen_fnsix(m, t) if (i < n) else None, [img_i, num_images, model_choice2, txt_input2], o, concurrency_limit=None, queue=False)
#stop_button2.click(lambda s: gr.update(interactive = False), None, stop_button2, cancels = [gen_event2])
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, Omnibus's Maximum Multiplier and <a href="https://huggingface.co/spaces/Yntec/ToyWorld">Toy World</a>!
</p>
"""
)
demo.queue(default_concurrency_limit=200, max_size=200)
demo.launch(show_api=False, max_threads=400) |