| from __future__ import annotations | |
| import pathlib | |
| def find_exp_dirs() -> list[str]: | |
| repo_dir = pathlib.Path(__file__).parent | |
| exp_root_dir = repo_dir / "experiments" | |
| if not exp_root_dir.exists(): | |
| return [] | |
| exp_dirs = sorted(exp_root_dir.glob("*")) | |
| exp_dirs = [exp_dir for exp_dir in exp_dirs if (exp_dir / "model_index.json").exists()] | |
| return [path.relative_to(repo_dir).as_posix() for path in exp_dirs] | |
| def save_model_card( | |
| save_dir: pathlib.Path, | |
| base_model: str, | |
| training_prompt: str, | |
| test_prompt: str = "", | |
| test_image_dir: str = "", | |
| ) -> None: | |
| image_str = "" | |
| if test_prompt and test_image_dir: | |
| image_paths = sorted((save_dir / test_image_dir).glob("*.gif")) | |
| if image_paths: | |
| image_path = image_paths[-1] | |
| rel_path = image_path.relative_to(save_dir) | |
| image_str = f"""## Samples | |
| Test prompt: {test_prompt} | |
| """ | |
| model_card = f"""--- | |
| license: creativeml-openrail-m | |
| base_model: {base_model} | |
| training_prompt: {training_prompt} | |
| tags: | |
| - stable-diffusion | |
| - stable-diffusion-diffusers | |
| - text-to-image | |
| - diffusers | |
| - text-to-video | |
| - tune-a-video | |
| inference: false | |
| --- | |
| # Tune-A-Video - {save_dir.name} | |
| ## Model description | |
| - Base model: [{base_model}](https://huggingface.co/{base_model}) | |
| - Training prompt: {training_prompt} | |
| {image_str} | |
| ## Related papers: | |
| - [Tune-A-Video](https://arxiv.org/abs/2212.11565): One-Shot Tuning of Image Diffusion Models for Text-to-Video Generation | |
| - [Stable-Diffusion](https://arxiv.org/abs/2112.10752): High-Resolution Image Synthesis with Latent Diffusion Models | |
| """ | |
| with open(save_dir / "README.md", "w") as f: | |
| f.write(model_card) | |