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README.md

@@ -1,29 +1,28 @@
 ---
-dataset_info:
-  features:
-  - name: image
-    dtype: image
-  - name: mask
-    dtype:
-      image:
-        mode: L
-  - name: image_id
-    dtype: string
-  - name: width
-    dtype: int32
-  - name: height
-    dtype: int32
-  - name: num_annotations
-    dtype: int32
-  splits:
-  - name: train
-    num_bytes: 51838878.0
-    num_examples: 125
-  download_size: 51844870
-  dataset_size: 51838878.0
-configs:
-- config_name: default
-  data_files:
-  - split: train
-    path: data/train-*
+license: mit
+tags:
+- computer-vision
+- image-segmentation
+- leaf-disease
+- in-the-wild
 ---
+
+# Cleaned_100
+
+This is a dataset of "in-the-wild" leaf images with segmentation masks generated by the **Segment Anything 2 (SAM 2)** model.
+
+## Dataset Description
+
+This dataset contains multi-leaf, "in-the-wild" images of plants. The segmentation masks were automatically generated using the `SAM2AutomaticMaskGenerator` and then processed to create a final binary mask for each image, highlighting the most prominent leaf structures. This dataset is intended for training and evaluating robust, automatic leaf segmentation models.
+
+### Features
+- `image`: The original RGB image.
+- `mask`: The binary, single-channel (grayscale) segmentation mask generated by SAM 2.
+- `image_id`: The original filename of the image.
+- `width`: The original width of the image.
+- `height`: The original height of the image.
+- `num_annotations`: The number of distinct leaf regions found in the mask, calculated via contour detection.
+
+## Dataset Structure
+
+The dataset consists of **125** image-mask pairs.