Tomato Leaf Disease Classification Dataset in Pakistan
Description
This dataset comprises 7,200 images of tomato leaves collected from real-time agricultural field conditions in Pakistan. The images were captured using a smartphone camera under natural lighting, without controlled backgrounds, to reflect realistic field environments. The dataset includes six classes: Early Blight, Late Blight, Septoria Leaf Spot, Leaf Mold, Yellow Leaf Curl Virus, and Healthy leaves. All images are stored in JPG format with consistent resolution and were manually labeled based on visible disease symptoms. The dataset is intended to support research and development in machine learning, deep learning, and computer vision, particularly for tomato leaf disease detection and precision agriculture applications under real-world conditions.
Files
Steps to reproduce
1. Download and extract the dataset files. 2. Organize images according to the provided class folders. 3. Use standard image preprocessing techniques such as resizing and normalization. 4. Split the dataset into training, validation, and test sets as required. 5. Train machine learning or deep learning models using the prepared data for tomato leaf disease classification.