Annotated_Benchmarks400

This is a comprehensive collection of annotated "In-The-Lab" Tomato Leaf Images. Each Image has only one single leaf collected from the train split of Tomato subset from the PlanVillage Dataset from the Kaggle. The Precise Annotations are done using Segment Anything 2.0 model with CVAT. The dataset contains Binary segmentation masks for each image.

Dataset Description

This dataset is a combination of four individual leaf disease datasets, intended for training robust computer vision models for segmentation tasks in agriculture. It includes images of tomato leaves affected by various common diseases.

The original datasets included are:

• Septoria Leaf Spot
• Yellow Leaf Curl Virus
• Early Blight
• Late Blight

Here's the number of samples from each class:

Features

The dataset contains the following features for each example:

• image: The original RGB image of the plant leaf.
• mask: The binary, single-channel (grayscale) segmentation mask where the leaf/disease area is highlighted.
• image_id: The original filename of the image, which can be used for traceability.
• width: The original width of the image in pixels.
• height: The original height of the image in pixels.
• num_annotations: The number of individual polygons annotated in the image.

Dataset Structure

The dataset consists of a single split ('train') with a total of 401 image-mask pairs.