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Runtime error
| 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() | |
| 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}') | |
| 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('') | |
| return models_load[model_str](f'{prompt} {noise}') | |
| 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)) | |
| 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 | |
| with lock: | |
| image = "https://huggingface.co/spaces/Yntec/ToyWorld/resolve/main/error.png" | |
| result = image | |
| finally: | |
| loop.close() | |
| return result | |
| def gen_fnsix(model_str, prompt): | |
| if model_str == 'NA': | |
| return None | |
| noisesix = str(randint(1941, 2023)) | |
| 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/pp.png" style="height:128px; width:482px; margin-top: -22px; margin-bottom: -44px;" span title="Free ai art image generator Printing Press"></center> | |
| </p> | |
| """ | |
| ) | |
| gr.HTML( | |
| """ | |
| <div> | |
| <p> <center>For negative prompts, Width and Height, and other features visit John6666's <a href="https://huggingface.co/spaces/John6666/PrintingPress4">Printing Press 4</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') | |
| 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) | |
| 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('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') | |
| 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 = 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) | |
| with gr.Row(): | |
| gr.HTML( | |
| """ | |
| <div class="footer"> | |
| <p> Based on the <a href="https://huggingface.co/spaces/derwahnsinn/TestGen">TestGen彼此 | |
| </p> | |
| """) |