WinterCropWeedDB-Sample: A Benchmark Dataset for Weed Classification in Winter Crops

This repository provides a sample version of the WinterCropWeedDB dataset, designed for weed classification research in winter crop fields. The complete dataset contains 1136 high-resolution images of six major winter crops (Wheat, Chickpea, Pea, Lentil, Mustard, Grass Pea) and four prevalent weed species (Common Vetch, Lesser Canary Grass, Goosefoot, Euphorbia Clementei).

In this sample release, we provide:
35 images per crop class
20 images per weed class

The images were collected directly from winter crop fields in Bilaspur and Mungeli districts, Chhattisgarh, India, using a 50 MP smartphone camera in Pro Mode under diverse lighting conditions (sunlight, shade) and camera perspectives to reflect real-world variability.

This subset provides a structured, annotated, and high-resolution resource that can be used for testing classification models, developing machine learning pipelines, or conducting preliminary research in weed detection, smart spraying, and sustainable crop management.

⚠️ Note: This is a sample release. The full dataset of 1136 images will be made available in future versions.

Data format: images.zip → Contains all images in .jpg format, organized by class folders
Use cases: Crop–weed classification, precision agriculture, machine learning benchmarking
Geographic Location: Bilaspur & Mungeli, Chhattisgarh, India

Value of the Data (Sample Version):

-Offers an initial benchmark for model testing and reproducibility

-Supports machine learning applications in smart agriculture

-Demonstrates variability in lighting, angle, and crop–weed morphology