FlowerNet: A Multi-Class Flower Image Dataset for Deep Learning-Based Classification

Description This dataset contains images of five different flower species Rose, Chrysanthemum, Hibiscus, Marigold, and Petunia collected from local gardens, nurseries, and agricultural fields. The dataset is curated for flower classification and recognition using computer vision techniques. It includes both original and augmented images, making it suitable for deep learning applications. Dataset Composition: Original Dataset: Rose: 268 images Chrysanthemum: 291 images Hibiscus: 197 images Marigold: 335 images Petunia: 309 images Augmented Dataset: Rose: 1,072 images Chrysanthemum: 1,164 images Hibiscus: 788 images Marigold: 1,340 images Petunia: 1,236 images Total Images: 7,000 File Format: JPG/PNG Potential Applications: Computer vision-based flower classification Plant quality and health assessment Deep learning model training for agricultural product classification