add hdf5 viewer
Browse files- .gitignore +1 -0
- README.md +2 -2
- app.py +73 -0
- requirements.txt +4 -0
.gitignore
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__*
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README.md
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---
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title: Visualization Turbulent Radiative Layer 2D
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emoji:
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colorFrom:
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colorTo: yellow
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sdk: gradio
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sdk_version: 4.44.0
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---
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title: Visualization Turbulent Radiative Layer 2D
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emoji: π π
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colorFrom: blue
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colorTo: yellow
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sdk: gradio
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sdk_version: 4.44.0
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app.py
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from functools import lru_cache
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import gradio as gr
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import h5py
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import numpy as np
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from fsspec import url_to_fs
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from matplotlib import cm
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from PIL import Image
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repo_id = "lhoestq/turbulent_radiative_layer_tcool_demo"
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set_path = f"hf://datasets/{repo_id}/**/*.hdf5"
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fs, _ = url_to_fs(set_path)
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paths = fs.glob(set_path)
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files = {path: h5py.File(fs.open(path, "rb", cache_type="none"), "r") for path in paths}
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def get_scalar_fields(path: str) -> list[str]:
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return list(files[path]["t0_fields"].keys())
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def get_trajectories(path: str, field: str) -> list[int]:
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return list(range(len(files[path]["t0_fields"][field])))
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@lru_cache(maxsize=4)
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def get_images(path: str, scalar_field: str, trajectory: int) -> list[Image.Image]:
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#The data is of shape (n_trajectories, n_timesteps, x, y)
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out = files[path]["t0_fields"][scalar_field][trajectory]
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out = np.log(out)
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out = (out - out.min()) / (out.max() - out.min())
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out = np.uint8(cm.RdBu_r(out) * 255)
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return [Image.fromarray(img) for img in out]
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default_scalar_fields = get_scalar_fields(paths[0])
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default_trajectories = get_trajectories(paths[0], default_scalar_fields[0])
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default_images = get_images(paths[0], default_scalar_fields[0], default_trajectories[0])
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with gr.Blocks() as demo:
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gr.Markdown(f"# π HDF5 Viewer for the [{repo_id}](https://huggingface.co/{repo_id}) Dataset π")
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gr.Markdown(f"Showing files at `{set_path}`")
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with gr.Row():
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files_dropdown = gr.Dropdown(choices=paths, value=paths[0], label="file", scale=4)
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scalar_fields_dropdown = gr.Dropdown(choices=default_scalar_fields, value=default_scalar_fields[0], label="scalar field")
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trajectory_dropdown = gr.Dropdown(choices=default_trajectories, value=default_trajectories[0], label="sample")
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gallery = gr.Gallery(default_images, preview=True, selected_index=len(default_images) // 2)
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gr.Markdown("_Tip: click on the image to go forward or backards_")
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@files_dropdown.select(inputs=[files_dropdown], outputs=[scalar_fields_dropdown, trajectory_dropdown, gallery])
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def _update_file(path: str):
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scalar_fields = get_scalar_fields(path)
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trajectories = get_trajectories(path, scalar_fields[0])
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images = get_images(path, scalar_fields[0], trajectories[0])
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yield {
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scalar_fields_dropdown: gr.Dropdown(choices=scalar_fields, value=scalar_fields[0]),
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trajectory_dropdown: gr.Dropdown(choices=trajectories, value=trajectories[0]),
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gallery: gr.Gallery(images)
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}
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yield {gallery: gr.Gallery(selected_index=len(default_images) // 2)}
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@scalar_fields_dropdown.select(inputs=[files_dropdown, scalar_fields_dropdown], outputs=[trajectory_dropdown, gallery])
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def _update_scalar_field(path: str, scalar_field: str):
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trajectories = get_trajectories(path, scalar_field)
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images = get_images(path, scalar_field, trajectories[0])
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yield {
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trajectory_dropdown: gr.Dropdown(choices=trajectories, value=trajectories[0]),
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gallery: gr.Gallery(images)
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}
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yield {gallery: gr.Gallery(selected_index=len(default_images) // 2)}
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@trajectory_dropdown.select(inputs=[files_dropdown, scalar_fields_dropdown, trajectory_dropdown], outputs=[gallery])
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def _update_trajectory(path: str, scalar_field: str, trajectory: int):
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images = get_images(path, scalar_field, trajectory)
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yield {gallery: gr.Gallery(images)}
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yield {gallery: gr.Gallery(selected_index=len(default_images) // 2)}
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demo.launch()
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requirements.txt
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1 |
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h5py
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2 |
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huggingface_hub
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3 |
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Pillow
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4 |
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numpy
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