| 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. |