Init commit

.gitignore

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+
+.coverage
+.coverage.*
+.cache
+nosetests.xml
+coverage.xml
+*.cover
+*.py,cover
+.hypothesis/
+.pytest_cache/
+cover/
+
+# Translations
+*.mo
+*.pot
+
+# Django stuff:
+*.log
+local_settings.py
+db.sqlite3
+db.sqlite3-journal
+
+# Flask stuff:
+instance/
+.webassets-cache
+
+# Scrapy stuff:
+.scrapy
+
+# Sphinx documentation
+docs/_build/
+
+# PyBuilder
+.pybuilder/
+target/
+
+# Jupyter Notebook
+.ipynb_checkpoints
+
+# IPython
+profile_default/
+ipython_config.py
+
+# pyenv
+#   For a library or package, you might want to ignore these files since the code is
+#   intended to run in multiple environments; otherwise, check them in:
+# .python-version
+
+# pipenv
+#   According to pypa/pipenv#598, it is recommended to include Pipfile.lock in version control.
+#   However, in case of collaboration, if having platform-specific dependencies or dependencies
+#   having no cross-platform support, pipenv may install dependencies that don't work, or not
+#   install all needed dependencies.
+#Pipfile.lock
+
+# poetry
+#   Similar to Pipfile.lock, it is generally recommended to include poetry.lock in version control.
+#   This is especially recommended for binary packages to ensure reproducibility, and is more
+#   commonly ignored for libraries.
+#   https://python-poetry.org/docs/basic-usage/#commit-your-poetrylock-file-to-version-control
+#poetry.lock
+
+# pdm
+#   Similar to Pipfile.lock, it is generally recommended to include pdm.lock in version control.
+#pdm.lock
+#   pdm stores project-wide configurations in .pdm.toml, but it is recommended to not include it
+#   in version control.
+#   https://pdm.fming.dev/#use-with-ide
+.pdm.toml
+
+# PEP 582; used by e.g. github.com/David-OConnor/pyflow and github.com/pdm-project/pdm
+__pypackages__/
+
+# Celery stuff
+celerybeat-schedule
+celerybeat.pid
+
+# SageMath parsed files
+*.sage.py
+
+# Environments
+.env
+.venv
+env/
+venv/
+ENV/
+env.bak/
+venv.bak/
+
+# Spyder project settings
+.spyderproject
+.spyproject
+
+# Rope project settings
+.ropeproject
+
+# mkdocs documentation
+/site
+
+# mypy
+.mypy_cache/
+.dmypy.json
+dmypy.json
+
+# Pyre type checker
+.pyre/
+
+# pytype static type analyzer
+.pytype/
+
+# Cython debug symbols
+cython_debug/
+
+# PyCharm
+#  JetBrains specific template is maintained in a separate JetBrains.gitignore that can
+#  be found at https://github.com/github/gitignore/blob/main/Global/JetBrains.gitignore
+#  and can be added to the global gitignore or merged into this file.  For a more nuclear
+#  option (not recommended) you can uncomment the following to ignore the entire idea folder.
+#.idea/
+
+# VS Code
+.vscode/
+
+# pycache
+__pycache__/

app.py

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+import gradio as gr
+import matplotlib.pyplot as plt
+import numpy as np
+from sklearn.cluster import MeanShift, estimate_bandwidth
+from sklearn.datasets import make_blobs
+
+
+def get_clusters_plot(n_blobs, cluster_std):
+    X, _, centers = make_blobs(
+        n_samples=10000, cluster_std=cluster_std, centers=n_blobs, return_centers=True
+    )
+
+    bandwidth = estimate_bandwidth(X, quantile=0.2, n_samples=500)
+
+    ms = MeanShift(bandwidth=bandwidth, bin_seeding=True)
+    ms.fit(X)
+    labels = ms.labels_
+    cluster_centers = ms.cluster_centers_
+
+    labels_unique = np.unique(labels)
+    n_clusters_ = len(labels_unique)
+
+    colors = ["#dede00", "#377eb8", "#f781bf"]
+    markers = ["x", "o", "^"]
+
+    fig = plt.figure()
+
+    for k, col in zip(range(n_clusters_), colors):
+        my_members = labels == k
+        cluster_center = cluster_centers[k]
+        plt.plot(X[my_members, 0], X[my_members, 1], markers[k], color=col)
+        plt.plot(
+            cluster_center[0],
+            cluster_center[1],
+            markers[k],
+            markerfacecolor=col,
+            markeredgecolor="k",
+            markersize=14,
+        )
+
+    return fig
+
+
+demo = gr.Interface(
+    get_clusters_plot,
+    [
+        gr.Slider(
+            minimum=2, maximum=10, label="Number of clusters in data", step=1, value=3
+        ),
+        gr.Slider(
+            minimum=0.1,
+            maximum=1,
+            label="Cluster standard deviation",
+            step=0.1,
+            value=0.6,
+        ),
+    ],
+    gr.Plot(),
+    allow_flagging="never",
+)
+
+if __name__ == "__main__":
+    demo.launch()