Image Dataset on Chili Leaf Diseases in the Krishna River Basin of the Deccan Plateau, India

Overview
This dataset is a comprehensive resource for researchers and professionals in agriculture, machine learning, and computer vision, focusing on chili plant disease detection and growth stage classification. It provides high-resolution images of both healthy and diseased chili leaves, as well as samples representing various growth stages, making it highly suitable for deep learning and AI-based precision agriculture applications.
Data Collection
The images were systematically collected between October 2024 and February 2025 from chili plantations in the Bellary and Raichur districts of Karnataka, and the Prathipadu, Vatticherukuru, and Medikonduru of Guntur and Parchur, Yeddana Pudi, and MarturPrakasam districts of Andhra Pradesh, which are recognized as the global epicenters for red chili production. All field collection was conducted under the direct supervision of agricultural experts to ensure the pathological accuracy of the healthy and diseased leaf samples. The collection effort spanned across diverse agro-climatic zones of the Krishna River Basin within the Deccan Plateau.
This multi-regional coverage ensured that a wide range of environmental and cultivation conditions were represented, capturing real-world variability in chili plant health, disease manifestation, and growth patterns.
Using advanced digital cameras, high-resolution images were gathered, documenting different disease types and developmental stages to support robust AI-driven agricultural research.
Dataset Structure
The dataset is organized into two primary categories:

Chili Leaf Disease Dataset
This category includes images depicting six major leaf diseases affecting chili plants. Each image is meticulously labeled and verified by agricultural experts to enable precise classification and model training.

Original Dataset: 1,856 high-resolution images (.jpg)
Augmented Dataset: 12,000 enhanced images generated through data augmentation techniques (rotation, flipping, contrast adjustment, and zoom)
# Disease Classes Covered:
Bacterial Spot

Curl Virus

Cercospora Leaf Spot

Nutrition Deficiency

White Spot

Healthy Leaves
Specifically, this dataset enables:
✅ Early and Accurate Disease Detection — facilitating the identification of key foliar diseases such as Bacterial Spot, Curl Virus and Cercospora Leaf Spot at early stages, thereby preventing large-scale crop losses and improving disease management efficiency.
✅ Automated Growth Stage Monitoring — providing visual evidence of chili plants at various growth stages, enabling automated phenotyping, yield estimation and adaptive farm management strategies using AI and computer vision models.
✅ Benchmark for AI and Computer Vision Models — serving as a standardized dataset for training and benchmarking deep learning architectures such as CNNs, Vision Transformers and hybrid models for plant disease recognition, segmentation, and classification tasks.