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README.md

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+---
+license: apache-2.0
+size_categories:
+- 10K<n<100K
+task_categories:
+- image-classification
+dataset_info:
+  features:
+  - name: image
+    dtype: image
+  - name: label
+    dtype:
+      class_label:
+        names:
+          '0': bouldering_area
+          '1': other
+  - name: stem
+    dtype: string
+  - name: suffix
+    dtype: string
+  splits:
+  - name: train
+    num_bytes: 2332064084.761
+    num_examples: 13679
+  - name: test
+    num_bytes: 805144625.12
+    num_examples: 3880
+  download_size: 3137306204
+  dataset_size: 3137208709.881
+configs:
+- config_name: default
+  data_files:
+  - split: train
+    path: data/train-*
+  - split: test
+    path: data/test-*
+tags:
+- bouldering
+- rock climbing
+- Boulderspot
+---
+
+# pszemraj/boulderspot
+
+These are aerial images of Switzerland classified into what could be a bouldering area (label: `bouldering_area`) or not (label: `other`). The test set has no labels (i.e. the column is `None`) and is randomly sampled from across the country.
+
+Sources:
+- data: [SWISSIMAGE 10 cm](https://www.swisstopo.admin.ch/en/orthoimage-swissimage-10)
+- labels: me
+
+Date created: 2021
+
+You can find some example CNN-based models trained on an earlier/smaller version of this dataset in [this repo](https://github.com/pszemraj/BoulderAreaDetector)
+
+If you are a member of **an organization** interested in details of how this was created/similar ideation related to AI applications for the outdoors/climbing, feel free to contact me (info on my [site](https://pszemraj.carrd.co/)). 
+
+---
+
+
+```yml
+dataset_info:
+  features:
+  - name: image
+    dtype: image
+  - name: label
+    dtype: string
+  - name: stem
+    dtype: string
+  - name: suffix
+    dtype: string
+  splits:
+  - name: train
+    num_bytes: 2881884752.62
+    num_examples: 13679
+  - name: test
+    num_bytes: 871464803.08
+    num_examples: 3880
+  download_size: 3137018901
+  dataset_size: 3753349555.7
+```

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