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| import gradio as gr | |
| from random import randint | |
| from all_models import models | |
| from externalmod import gr_Interface_load, randomize_seed | |
| 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 = 6 | |
| default_models = models[:num_models] | |
| inference_timeout = 600 | |
| MAX_SEED=3999999999 | |
| starting_seed = randint(1941, 2024) | |
| def extend_choices(choices): | |
| return choices[:num_models] + (num_models - len(choices[:num_models])) * ['NA'] | |
| def update_imgbox(choices): | |
| choices_plus = extend_choices(choices[:num_models]) | |
| return [gr.Image(None, label=m, visible=(m!='NA')) for m in choices_plus] | |
| 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 | |
| with gr.Blocks() as demo: | |
| gr.HTML( | |
| """ | |
| <div> | |
| <p> <center>For more options like negative prompts, single model x6 or seeds up to 4294967295 check out <a href="https://huggingface.co/spaces/John6666/Diffusion80XX4sg">Diffusion80XX4sg</a> by John6666!</center> | |
| </p></div> | |
| """ | |
| ) | |
| with gr.Tab('🤗 Huggingface Diffusion 🤗'): | |
| txt_input = gr.Textbox(label='Your prompt:', lines=4) | |
| gen_button = gr.Button('Generate up to 6 images in up to 3 minutes total') | |
| with gr.Row(): | |
| seed = gr.Slider(label="Use a seed to replicate the same image later (maximum 3999999999)", minimum=0, maximum=MAX_SEED, step=1, value=starting_seed, scale=3) | |
| seed_rand = gr.Button("Randomize Seed 🎲", size="sm", variant="secondary", scale=1) | |
| seed_rand.click(randomize_seed, None, [seed], queue=False) | |
| #stop_button = gr.Button('Stop', variant = 'secondary', interactive = False) | |
| gen_button.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 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 = gr.on(triggers=[gen_button.click, txt_input.submit], fn=gen_fnseed, | |
| inputs=[m, txt_input, seed], outputs=[o], concurrency_limit=None, queue=False) | |
| #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 {int(num_models)} different models from the {len(models)} available!', value=default_models, interactive=True) | |
| #model_choice = gr.CheckboxGroup(models, label = f'Choose up to {num_models} different models from the 2 available! Untick them to only use one!', 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/John6666/hfd_test_nostopbutton">Huggingface NoStopButton</a> Space by John6666, <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! For 6 images with the same model check out the <a href="https://huggingface.co/spaces/Yntec/PrintingPress">Printing Press</a>, for the classic UI with prompt enhancer try <a href="https://huggingface.co/spaces/Yntec/blitz_diffusion">Blitz Diffusion!</a> | |
| </p> | |
| """ | |
| ) | |
| demo.queue(default_concurrency_limit=200, max_size=200) | |
| demo.launch(show_api=False, max_threads=400) |