| |
|
|
| from __future__ import annotations |
|
|
| import os |
| import pathlib |
| import random |
| import shlex |
| import subprocess |
|
|
| import gradio as gr |
| import torch |
| from huggingface_hub import snapshot_download |
|
|
| if os.getenv('SYSTEM') == 'spaces': |
| subprocess.run(shlex.split('pip uninstall -y modelscope')) |
| subprocess.run( |
| shlex.split( |
| 'pip install git+https://github.com/modelscope/modelscope.git@refs/pull/207/head' |
| )) |
|
|
| from modelscope.outputs import OutputKeys |
| from modelscope.pipelines import pipeline |
|
|
| model_dir = pathlib.Path('weights') |
| if not model_dir.exists(): |
| model_dir.mkdir() |
| snapshot_download('damo-vilab/modelscope-damo-text-to-video-synthesis', |
| repo_type='model', |
| local_dir=model_dir) |
|
|
| DESCRIPTION = '# [Text-to-Video Playground](https://modelscope.cn/models/damo/text-to-video-synthesis/summary)' |
| if (SPACE_ID := os.getenv('SPACE_ID')) is not None: |
| DESCRIPTION += f'\n<p>For faster inference without waiting in queue, you may duplicate the space and upgrade to GPU in settings. <a href="https://huggingface.co/spaces/{SPACE_ID}?duplicate=true"><img style="display: inline; margin-top: 0em; margin-bottom: 0em" src="https://bit.ly/3gLdBN6" alt="Duplicate Space" /></a></p>' |
|
|
| pipe = pipeline('text-to-video-synthesis', model_dir.as_posix()) |
|
|
|
|
| def generate(prompt: str, seed: int) -> str: |
| if seed == -1: |
| seed = random.randint(0, 1000000) |
| torch.manual_seed(seed) |
| return pipe({'text': prompt})[OutputKeys.OUTPUT_VIDEO] |
|
|
|
|
| examples = [ |
| ['An astronaut riding a horse.', 0], |
| ['A panda eating bamboo on a rock.', 0], |
| ['Spiderman is surfing.', 0], |
| ] |
|
|
| with gr.Blocks(css='style.css') as demo: |
| gr.Markdown(DESCRIPTION) |
| with gr.Row(): |
| with gr.Column(): |
| prompt = gr.Text(label='Prompt', max_lines=1) |
| seed = gr.Slider( |
| label='Seed', |
| minimum=-1, |
| maximum=1000000, |
| step=25, |
| value=-1, |
| info='If set to -1, a different seed will be used each time.') |
| run_button = gr.Button('Run') |
| with gr.Column(): |
| result = gr.Video(label='Result') |
|
|
| inputs = [prompt, seed] |
| gr.Examples(examples=examples, |
| inputs=inputs, |
| outputs=result, |
| fn=generate, |
| cache_examples=os.getenv('SYSTEM') == 'spaces') |
|
|
| prompt.submit(fn=generate, inputs=inputs, outputs=result) |
| run_button.click(fn=generate, inputs=inputs, outputs=result) |
|
|
| demo.queue(api_open=False, max_size=15).launch() |
|
|
