Duplicate from victor/autotrain-data-satellite-image-classification

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+# Audio files - uncompressed
+*.pcm filter=lfs diff=lfs merge=lfs -text
+*.sam filter=lfs diff=lfs merge=lfs -text
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+*.bmp filter=lfs diff=lfs merge=lfs -text
+*.gif filter=lfs diff=lfs merge=lfs -text
+*.png filter=lfs diff=lfs merge=lfs -text
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README.md

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+---
+task_categories:
+- image-classification
+
+---
+# AutoTrain Dataset for project: satellite-image-classification
+
+## Dataset Descritpion
+
+This dataset has been automatically processed by AutoTrain for project satellite-image-classification.
+
+### Languages
+
+The BCP-47 code for the dataset's language is unk.
+
+## Dataset Structure
+
+### Data Instances
+
+A sample from this dataset looks as follows:
+
+```json
+[
+  {
+    "image": "<256x256 CMYK PIL image>",
+    "target": 0
+  },
+  {
+    "image": "<256x256 CMYK PIL image>",
+    "target": 0
+  }
+]
+```
+
+### Dataset Fields
+
+The dataset has the following fields (also called "features"):
+
+```json
+{
+  "image": "Image(decode=True, id=None)",
+  "target": "ClassLabel(num_classes=1, names=['cloudy'], id=None)"
+}
+```
+
+### Dataset Splits
+
+This dataset is split into a train and validation split. The split sizes are as follow:
+
+| Split name   | Num samples         |
+| ------------ | ------------------- |
+| train        | 1200 |
+| valid        | 300 |

processed/dataset_dict.json

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