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import gradio as gr | |
import os | |
import sys | |
from pathlib import Path | |
from all_models import models | |
from externalmod import gr_Interface_load | |
from prompt_extend import extend_prompt | |
from random import randint | |
import asyncio | |
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. | |
inference_timeout = 600 | |
MAX_SEED = 2**32-1 | |
current_model = models[0] | |
text_gen1 = extend_prompt | |
#text_gen1=gr.Interface.load("spaces/phenomenon1981/MagicPrompt-Stable-Diffusion") | |
#text_gen1=gr.Interface.load("spaces/Yntec/prompt-extend") | |
#text_gen1=gr.Interface.load("spaces/daspartho/prompt-extend") | |
#text_gen1=gr.Interface.load("spaces/Omnibus/MagicPrompt-Stable-Diffusion_link") | |
models2 = [gr_Interface_load(f"models/{m}", live=False, preprocess=True, postprocess=False, hf_token=HF_TOKEN) for m in models] | |
def text_it1(inputs, text_gen1=text_gen1): | |
go_t1 = text_gen1(inputs) | |
return(go_t1) | |
def set_model(current_model): | |
current_model = models[current_model] | |
return gr.update(label=(f"{current_model}")) | |
def send_it1(inputs, model_choice, neg_input, height, width, steps, cfg, seed): | |
output1 = gen_fn(model_choice, inputs, neg_input, height, width, steps, cfg, seed) | |
return (output1) | |
# https://huggingface.co/docs/api-inference/detailed_parameters | |
# https://huggingface.co/docs/huggingface_hub/package_reference/inference_client | |
async def infer(model_index, prompt, nprompt="", height=None, width=None, steps=None, cfg=None, seed=-1, timeout=inference_timeout): | |
from pathlib import Path | |
kwargs = {} | |
if height is not None and height >= 256: kwargs["height"] = height | |
if width is not None and width >= 256: kwargs["width"] = width | |
if steps is not None and steps >= 1: kwargs["num_inference_steps"] = steps | |
if cfg is not None and cfg > 0: cfg = kwargs["guidance_scale"] = cfg | |
noise = "" | |
if seed >= 0: kwargs["seed"] = seed | |
else: | |
rand = randint(1, 500) | |
for i in range(rand): | |
noise += " " | |
task = asyncio.create_task(asyncio.to_thread(models2[model_index].fn, | |
prompt=f'{prompt} {noise}', negative_prompt=nprompt, **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: {models2[model_index]}") | |
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_fn(model_index, prompt, nprompt="", height=None, width=None, steps=None, cfg=None, seed=-1): | |
try: | |
loop = asyncio.new_event_loop() | |
result = loop.run_until_complete(infer(model_index, prompt, nprompt, | |
height, width, steps, cfg, seed, inference_timeout)) | |
except (Exception, asyncio.CancelledError) as e: | |
print(e) | |
print(f"Task aborted: {models2[model_index]}") | |
result = None | |
finally: | |
loop.close() | |
return result | |
css=""" | |
.gradio-container {background-image: linear-gradient(#254150, #1e2f40, #182634) !important; | |
color: #ffaa66 !important; font-family: 'IBM Plex Sans', sans-serif !important;} | |
h1 {font-size: 6em; color: #ffc99f; margin-top: 30px; margin-bottom: 30px; | |
text-shadow: 3px 3px 0 rgba(0, 0, 0, 1) !important;} | |
h3 {color: #ffc99f; !important;} | |
h4 {display: inline-block; color: #ffffff !important;} | |
.wrapper img {font-size: 98% !important; white-space: nowrap !important; text-align: center !important; | |
display: inline-block !important; color: #ffffff !important;} | |
.wrapper {color: #ffffff !important;} | |
.text-gray-500 {color: #ffc99f !important;} | |
.gr-box {background-image: linear-gradient(#182634, #1e2f40, #254150) !important; | |
border-top-color: #000000 !important; border-right-color: #ffffff !important; | |
border-bottom-color: #ffffff !important; border-left-color: #000000 !important;} | |
.gr-input {color: #ffc99f; !important; background-color: #254150 !important;} | |
:root {--neutral-100: #000000 !important;} | |
.gr-button {color: #ffffff !important; text-shadow: 1px 1px 0 rgba(0, 0, 0, 1) !important; | |
background-image: linear-gradient(#76635a, #d2a489) !important; border-radius: 24px !important; | |
border: solid 1px !important; border-top-color: #ffc99f !important; border-right-color: #000000 !important; | |
border-bottom-color: #000000 !important; border-left-color: #ffc99f !important; padding: 6px 30px;} | |
.gr-button:active {color: #ffc99f !important; font-size: 98% !important; | |
text-shadow: 0px 0px 0 rgba(0, 0, 0, 1) !important; background-image: linear-gradient(#d2a489, #76635a) !important; | |
border-top-color: #000000 !important; border-right-color: #ffffff !important; | |
border-bottom-color: #ffffff !important; border-left-color: #000000 !important;} | |
.gr-button:hover {filter: brightness(130%);} | |
""" | |
with gr.Blocks(theme='John6666/YntecDark', fill_width=True, css=css) as myface: | |
gr.HTML(f""" | |
<div style="text-align: center; max-width: 1200px; margin: 0 auto;"> | |
<div> | |
<style> | |
h1 {{ | |
font-size: 6em; | |
color: #ffc99f; | |
margin-top: 30px; | |
margin-bottom: 30px; | |
text-shadow: 3px 3px 0 rgba(0, 0, 0, 1) !important; | |
}} | |
h3 {{ | |
color: #ffc99f; !important; | |
}} | |
h4 {{ | |
display: inline-block; | |
color: #ffffff !important; | |
}} | |
.wrapper img {{ | |
font-size: 98% !important; | |
white-space: nowrap !important; | |
text-align: center !important; | |
display: inline-block !important; | |
color: #ffffff !important; | |
}} | |
.wrapper {{ | |
color: #ffffff !important; | |
}} | |
.gradio-container {{ | |
background-image: linear-gradient(#254150, #1e2f40, #182634) !important; | |
color: #ffaa66 !important; | |
font-family: 'IBM Plex Sans', sans-serif !important; | |
}} | |
.text-gray-500 {{ | |
color: #ffc99f !important; | |
}} | |
.gr-box {{ | |
background-image: linear-gradient(#182634, #1e2f40, #254150) !important; | |
border-top-color: #000000 !important; | |
border-right-color: #ffffff !important; | |
border-bottom-color: #ffffff !important; | |
border-left-color: #000000 !important; | |
}} | |
.gr-input {{ | |
color: #ffc99f; !important; | |
background-color: #254150 !important; | |
}} | |
:root {{ | |
--neutral-100: #000000 !important; | |
}} | |
</style> | |
<body> | |
<div class="center"><h1>Toy World</h1> | |
</div> | |
</body> | |
</div> | |
<p style="margin-bottom: 1px; color: #ffaa66;"> | |
<h3>{int(len(models))} Stable Diffusion models, but why? For your enjoyment!</h3></p> | |
<br><div class="wrapper">9.3 <img src="https://huggingface.co/Yntec/DucHaitenLofi/resolve/main/NEW.webp" alt="NEW!" style="width:32px;height:16px;">This has become a legacy backup copy of old <u><a href="https://huggingface.co/spaces/Yntec/ToyWorld">ToyWorld</a></u>'s UI! Newer models added dailty over there! 25 new models since last update!</div> | |
<p style="margin-bottom: 1px; font-size: 98%"> | |
<br><h4>If a model is already loaded each new image takes less than <b>10</b> seconds to generate!</h4></p> | |
<p style="margin-bottom: 1px; color: #ffffff;"> | |
<br><div class="wrapper">Generate 6 images from 1 prompt at the <u><a href="https://huggingface.co/spaces/Yntec/PrintingPress">PrintingPress</a></u>, and use 6 different models at <u><a href="https://huggingface.co/spaces/Yntec/diffusion80xx">Huggingface Diffusion!</a></u>! | |
</p></p> | |
</div> | |
""", elem_classes="gr-box") | |
with gr.Row(): | |
with gr.Column(scale=100): | |
#Model selection dropdown | |
model_name1 = gr.Dropdown(label="Select Model", choices=[m for m in models], type="index", | |
value=current_model, interactive=True, elem_classes=["gr-box", "gr-input"]) | |
with gr.Row(): | |
with gr.Column(scale=100): | |
with gr.Group(): | |
magic1 = gr.Textbox(label="Your Prompt", lines=4, elem_classes=["gr-box", "gr-input"]) #Positive | |
with gr.Accordion("Advanced", open=False, visible=True): | |
neg_input = gr.Textbox(label='Negative prompt', lines=1, elem_classes=["gr-box", "gr-input"]) | |
with gr.Row(): | |
width = gr.Slider(label="Width", info="If 0, the default value is used.", maximum=1216, step=32, value=0, elem_classes=["gr-box", "gr-input"]) | |
height = gr.Slider(label="Height", info="If 0, the default value is used.", maximum=1216, step=32, value=0, elem_classes=["gr-box", "gr-input"]) | |
with gr.Row(): | |
steps = gr.Slider(label="Number of inference steps", info="If 0, the default value is used.", maximum=100, step=1, value=0, elem_classes=["gr-box", "gr-input"]) | |
cfg = gr.Slider(label="Guidance scale", info="If 0, the default value is used.", maximum=30.0, step=0.1, value=0, elem_classes=["gr-box", "gr-input"]) | |
seed = gr.Slider(label="Seed", info="Randomize Seed if -1.", minimum=-1, maximum=MAX_SEED, step=1, value=-1, elem_classes=["gr-box", "gr-input"]) | |
run = gr.Button("Generate Image", elem_classes="gr-button") | |
with gr.Row(): | |
with gr.Column(): | |
output1 = gr.Image(label=(f"{current_model}"), show_download_button=True, | |
interactive=False, show_share_button=False, format=".png", elem_classes="gr-box") | |
with gr.Row(): | |
with gr.Column(scale=50): | |
input_text=gr.Textbox(label="Use this box to extend an idea automagically, by typing some words and clicking Extend Idea", lines=2, elem_classes=["gr-box", "gr-input"]) | |
see_prompts=gr.Button("Extend Idea -> overwrite the contents of the `Your Prompt´ box above", elem_classes="gr-button") | |
use_short=gr.Button("Copy the contents of this box to the `Your Prompt´ box above", elem_classes="gr-button") | |
def short_prompt(inputs): | |
return (inputs) | |
model_name1.change(set_model, inputs=model_name1, outputs=[output1]) | |
gr.on( | |
triggers=[run.click, magic1.submit], | |
fn=send_it1, | |
inputs=[magic1, model_name1, neg_input, height, width, steps, cfg, seed], | |
outputs=[output1], | |
) | |
use_short.click(short_prompt, inputs=[input_text], outputs=magic1) | |
see_prompts.click(text_it1, inputs=[input_text], outputs=magic1) | |
myface.queue(default_concurrency_limit=200, max_size=200) | |
myface.launch(show_api=False, max_threads=400) | |