Duplicate from renumics/cifar100-enriched

Co-authored-by: Marius Steger <Syoy@users.noreply.huggingface.co>

.gitattributes

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+*.7z filter=lfs diff=lfs merge=lfs -text
+*.arrow filter=lfs diff=lfs merge=lfs -text
+*.bin filter=lfs diff=lfs merge=lfs -text
+*.bz2 filter=lfs diff=lfs merge=lfs -text
+*.ckpt filter=lfs diff=lfs merge=lfs -text
+*.ftz filter=lfs diff=lfs merge=lfs -text
+*.gz filter=lfs diff=lfs merge=lfs -text
+*.h5 filter=lfs diff=lfs merge=lfs -text
+*.joblib filter=lfs diff=lfs merge=lfs -text
+*.lfs.* filter=lfs diff=lfs merge=lfs -text
+*.mlmodel filter=lfs diff=lfs merge=lfs -text
+*.model filter=lfs diff=lfs merge=lfs -text
+*.msgpack filter=lfs diff=lfs merge=lfs -text
+*.npy filter=lfs diff=lfs merge=lfs -text
+*.npz filter=lfs diff=lfs merge=lfs -text
+*.onnx filter=lfs diff=lfs merge=lfs -text
+*.ot filter=lfs diff=lfs merge=lfs -text
+*.parquet filter=lfs diff=lfs merge=lfs -text
+*.pb filter=lfs diff=lfs merge=lfs -text
+*.pickle filter=lfs diff=lfs merge=lfs -text
+*.pkl filter=lfs diff=lfs merge=lfs -text
+*.pt filter=lfs diff=lfs merge=lfs -text
+*.pth filter=lfs diff=lfs merge=lfs -text
+*.rar filter=lfs diff=lfs merge=lfs -text
+*.safetensors filter=lfs diff=lfs merge=lfs -text
+saved_model/**/* filter=lfs diff=lfs merge=lfs -text
+*.tar.* filter=lfs diff=lfs merge=lfs -text
+*.tflite filter=lfs diff=lfs merge=lfs -text
+*.tgz filter=lfs diff=lfs merge=lfs -text
+*.wasm filter=lfs diff=lfs merge=lfs -text
+*.xz filter=lfs diff=lfs merge=lfs -text
+*.zip filter=lfs diff=lfs merge=lfs -text
+*.zst filter=lfs diff=lfs merge=lfs -text
+*tfevents* filter=lfs diff=lfs merge=lfs -text

.gitignore

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+
+.venv/

Dockerfile

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+FROM python:3.9
+
+WORKDIR /code
+ENV HOME=/code
+# COPY ./requirements.txt /code/requirements.txt
+# RUN pip install --no-cache-dir --upgrade -r /code/requirements.txt
+
+RUN apt install curl
+RUN pip install pip -U
+
+RUN pip install renumics-spotlight==1.2.0rc2
+
+RUN pip install datasets
+
+COPY . .
+RUN mkdir -p /code/.cache
+RUN chmod -R 777 /code
+RUN python prepare.py
+CMD ["python", "run.py"]

README.md

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+---
+title: Explore CIFAR-100 Enriched with Spotlight
+emoji: 📊
+colorFrom: gray
+colorTo: blue
+sdk: docker
+pinned: false
+license: mit
+app_file: run.py
+datasets:
+- renumics/cifar100-enriched
+- cifar100
+tags:
+- renumics
+- spotlight
+- EDA
+- enriched
+duplicated_from: renumics/cifar100-enriched
+---
+
+Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference

prepare.py

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+import pickle
+import datasets
+import os
+
+if __name__ == "__main__":
+    cache_file = "dataset_cache.pkl"
+    if os.path.exists(cache_file):
+        # Load dataset from cache
+        with open(cache_file, "rb") as file:
+            dataset = pickle.load(file)
+        print("Dataset loaded from cache.")
+    else:
+        # Load dataset using datasets.load_dataset()
+        dataset = datasets.load_dataset("renumics/cifar100-enriched", split="train")
+        print("Dataset loaded using datasets.load_dataset().")
+
+        # Save dataset to cache
+        with open(cache_file, "wb") as file:
+            pickle.dump(dataset, file)
+
+        print("Dataset saved to cache.")
+

requirements.txt

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+renumics-spotlight
+datasets

run.py

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+import pickle
+import datasets
+from renumics import spotlight
+import os
+
+if __name__ == "__main__":
+    cache_file = "dataset_cache.pkl"
+    if os.path.exists(cache_file):
+        # Load dataset from cache
+        with open(cache_file, "rb") as file:
+            dataset = pickle.load(file)
+        print("Dataset loaded from cache.")
+    else:
+        # Load dataset using datasets.load_dataset()
+        dataset = datasets.load_dataset("renumics/cifar100-enriched", split="train")
+        print("Dataset loaded using datasets.load_dataset().")
+
+        # Save dataset to cache
+        with open(cache_file, "wb") as file:
+            pickle.dump(dataset, file)
+
+        print("Dataset saved to cache.")
+
+
+    df = dataset.to_pandas()
+    df_show = df.drop(columns=['embedding', 'probabilities'])
+    while True:
+        view = spotlight.show(df_show.sample(5000, random_state=1), port=7860, host="0.0.0.0", 
+                    dtype={"image": spotlight.Image, "embedding_reduced": spotlight.Embedding}, allow_filebrowsing=False)
+        view.close()

spotlight-layout.json

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