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| from functools import lru_cache | |
| import gradio as gr | |
| import h5py | |
| import numpy as np | |
| from fsspec import url_to_fs | |
| from matplotlib import cm | |
| from PIL import Image | |
| repo_id = "lhoestq/turbulent_radiative_layer_tcool_demo" | |
| set_path = f"hf://datasets/{repo_id}/**/*.hdf5" | |
| fs, _ = url_to_fs(set_path) | |
| paths = fs.glob(set_path) | |
| files = {path: h5py.File(fs.open(path, "rb", cache_type="none"), "r") for path in paths} | |
| def get_scalar_fields(path: str) -> list[str]: | |
| return list(files[path]["t0_fields"].keys()) | |
| def get_trajectories(path: str, field: str) -> list[int]: | |
| return list(range(len(files[path]["t0_fields"][field]))) | |
| def get_images(path: str, scalar_field: str, trajectory: int) -> list[Image.Image]: | |
| #The data is of shape (n_trajectories, n_timesteps, x, y) | |
| out = files[path]["t0_fields"][scalar_field][trajectory] | |
| out = np.log(out) | |
| out = (out - out.min()) / (out.max() - out.min()) | |
| out = np.uint8(cm.RdBu_r(out) * 255) | |
| return [Image.fromarray(img) for img in out] | |
| default_scalar_fields = get_scalar_fields(paths[0]) | |
| default_trajectories = get_trajectories(paths[0], default_scalar_fields[0]) | |
| default_images = get_images(paths[0], default_scalar_fields[0], default_trajectories[0]) | |
| with gr.Blocks() as demo: | |
| gr.Markdown(f"# π HDF5 Viewer for the [{repo_id}](https://huggingface.co/datasets/{repo_id}) Dataset π") | |
| gr.Markdown(f"Showing files at `{set_path}`") | |
| with gr.Row(): | |
| files_dropdown = gr.Dropdown(choices=paths, value=paths[0], label="file", scale=4) | |
| scalar_fields_dropdown = gr.Dropdown(choices=default_scalar_fields, value=default_scalar_fields[0], label="scalar field") | |
| trajectory_dropdown = gr.Dropdown(choices=default_trajectories, value=default_trajectories[0], label="sample") | |
| gallery = gr.Gallery(default_images, preview=True, selected_index=len(default_images) // 2) | |
| gr.Markdown("_Tip: click on the image to go forward or backards_") | |
| def _update_file(path: str): | |
| scalar_fields = get_scalar_fields(path) | |
| trajectories = get_trajectories(path, scalar_fields[0]) | |
| images = get_images(path, scalar_fields[0], trajectories[0]) | |
| yield { | |
| scalar_fields_dropdown: gr.Dropdown(choices=scalar_fields, value=scalar_fields[0]), | |
| trajectory_dropdown: gr.Dropdown(choices=trajectories, value=trajectories[0]), | |
| gallery: gr.Gallery(images) | |
| } | |
| yield {gallery: gr.Gallery(selected_index=len(default_images) // 2)} | |
| def _update_scalar_field(path: str, scalar_field: str): | |
| trajectories = get_trajectories(path, scalar_field) | |
| images = get_images(path, scalar_field, trajectories[0]) | |
| yield { | |
| trajectory_dropdown: gr.Dropdown(choices=trajectories, value=trajectories[0]), | |
| gallery: gr.Gallery(images) | |
| } | |
| yield {gallery: gr.Gallery(selected_index=len(default_images) // 2)} | |
| def _update_trajectory(path: str, scalar_field: str, trajectory: int): | |
| images = get_images(path, scalar_field, trajectory) | |
| yield {gallery: gr.Gallery(images)} | |
| yield {gallery: gr.Gallery(selected_index=len(default_images) // 2)} | |
| demo.launch() |