A Medicinal Plant Leaf Image Dataset from Bangladesh for Deep Learning–Based Recognition

The dataset titled “A Medicinal Plant Leaf Image Dataset from Bangladesh for Deep Learning–Based Recognition” comprises a total of 6,419 high-resolution JPG images of six medicinal plant species collected from the rural jungle area of Guadanga village, Phulpur, Mymensingh, Bangladesh.
Leaf samples were photographed indoors under controlled lighting conditions with varied natural backgrounds using Google Pixel 5 and Google Pixel 6a smartphones to ensure consistent color fidelity and sharpness suitable for computer-vision and deep-learning research.

The dataset is organized into six species-specific folders, each representing a commonly found medicinal plant in Bangladesh:

• Centella Asiatica
• Coccinia Grandis
• Eclipta Prostrata
• Mikania Micrantha
• Murraya Koenigii
• Stephania Japonica

The collection includes 1,678 original images, 1,678 annotated images, and 3,063 augmented images generated through horizontal and vertical flipping, grayscale conversion, and geometric transformations.
All images were auto-oriented and resized uniformly to 640 × 640 pixels to maintain consistency across the dataset.
These augmentations increase data diversity and support the development of robust deep-learning models for medicinal-leaf classification, detection, and segmentation.